Orthorectifying DigitalGlobe Imagery in ERDAS Imagine ...

Orthorectifying DigitalGlobe Imagery in ERDAS Imagine using the Rational Polynomial Coefficient (RPC) model

The Rational Polynomial Coefficient DigitalGlobe’s QuickBird, WorldView-1 and WorldView-2 satellite images are built up of groups of scan lines acquired as the satellites moves forward in its orbit. As a result, different parts of the same image are acquired from different sensor positions. In order to rigorously describe the transformation from image coordinates to Earth surface coordinates, a mathematical sensor model that incorporates all of the physical elements of the imaging system can be exceedingly long and complex. Rational Polynomial Coefficients (RPCs) are simpler empirical mathematical models relating image space (line and column position) to latitude, longitude, and surface elevation. The name Rational Polynomial derives from the fact that the model is expressed as the ratio of two cubic polynomial expressions. Actually, a single image involves two such rational polynomials, one for computing line position and one for the column position. The coefficients of these two rational polynomials are computed by DigitalGlobe from the satellite’s orbital position and orientation and the rigorous physical sensor model. Using the georeferenced satellite image, its rational polynomial coefficients, and a DEM to supply the elevation values, ERDAS IMAGINE can compute the proper geographic position for each image cell, producing an Orthorectified image. Orthorectification is the process of removing distortion in the image based on the factors previously mentioned. It’s important to note that using the RPC’s is just one way to transform from image coordinates to Earth surface coordinates. This process can also be done using the Rigorous Sensor Model; although not all 3rd party remote sensing software packages have access to DigitalGlobe’s Rigorous Sensor Model for its satellites. In this workflow you are going to orthorectify a WorldView-2 image by using an RPC model. Both QuickBird and WorldView-1 Level 1B and Ortho Ready 2A products contain an RPC file; therefore this same process can be accomplished using these sensors as well. This file should be located in the same directory as the image(s) you intend to use in orthorectification. Note: Prior to Calibrating with Sensor Model and Terrain check the folder where your imagery resides. If there are multiple images in the folder you can reassemble the image tiles into one image for processing (see fig. 1 as an example). To do so please reference the WorldView2 Basics and ERDAS IMAGINE located in http://www.digitalglobe.com/partners/software-partners under the

http://www.digitalglobe.com/partners/software-partners

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ERDAS/Intergraph tab. In that document there is a section titled “Import DigitalGlobe tile data (.TIL) with ERDAS IMAGINE.”

Fig.1. Multiple Image Tiles example

Calibrate WorldView Image with RPCs

1. Open ERDAS IMAGINE and select the Raster Tab. Click the Geometric Calibration pull down and select Orthorectify without GCP

Fig.2. Select Orthorectify without GCP

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2. Select the image file to be Orthorectified in the file chooser

Fig.3. Geo Correction Input File

3. Select the WorldView RPC model in the Set Geometric Model dialog

Note: WorldView RPC will serve both WorldView-1 and WorldView-2 sensors. You’ll also notice QuickBird RPC is also available.

Fig.4.Set Geometric Model

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4. In the WorldView RPC Model Properties, select the corresponding RPB file and specify

the elevation source.

Fig.5. WorldView RPC Model Properties

5. Elevation Source: Specify an elevation source to be used in the geocorrection. An elevation source can improve your results. Note: Elevation will be a separate file that is not supplied by DigitalGlobe with the Basic (1B) and OrthoReady (2A) products.

File Click this radio button if elevation information is coming from a separate file, such

as a DEM. You select the file in the Elevation File field, below. Constant Click this radio button to input an average elevation value for the scene. You

enter that value in the Elevation Value field, below. Elevation Library Click this radio button to use the data in the Elevation Library as

the source. See additional info below on using the Elevation Library Note: you need to change Files of type to RPC in the Files of type dropdown menu

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Fig.6. Select RPC (.RPB) file

6. Click Apply. Done

Add elevation source to the Elevation Library Manager The Elevation Library Manager provides a method to collect and manage your elevation source files, including Digital Elevation Model data (DEM), as well as Digital Terrain Elevation Data (DTED) used by the U.S. National Geospatial-Intelligence Agency. Concept: Many companies and agencies maintain data holdings of elevation data used for ortho-rectifying data and other terrain-related purposes. The elevation data is generally of multiple resolutions covering different spatial locations - perhaps a global elevation dataset which covers everywhere the company might be interested in at a lower resolution and then a patchwork of higher resolution data sets and tiles covering locations which have been studied in more depth.

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How do you select (or even find) the best elevations source data for the locations you are interested in and how do you patch together potentially multiple tiles (at potentially multiple resolutions)? ERDAS IMAGINE 2010 provides a potential solution to this issue - the Elevation Library Manager. The Elevation Library Manager provides a method to collect and manage your elevation source files, including Digital Elevation Model data (DEM), as well as Digital Terrain Elevation Data (DTED) used by the U.S. National Geospatial-Intelligence Agency. The Elevation Library Manager simplifies elevation source file organization by storing the locations and relevant files of elevation data in a prioritized list. You can store multiple directories containing multiple elevation source files in the list, and store individual elevation source files.

7. Click on the Terrain Tab and select Elevation Library

Fig.7. Elevation Library Tab

8. In the Elevation Library Manager, click the Add Elevation Source icon

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Fig.8. Elevation Library Manager

9. Navigate to the directory with you DEM file, select Elevation file you wish to use and click OK

Fig.9. Select Elevation File

10. You should now see the new elevation source in the Elevation Library Manager. Click OK

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Fig.10. Elevation Library Manager

Note: If you do not have a DEM that you can use you have the option to use the default globaldem2.jp2 that is supplied with the software by ERDAS. Once the elevation source has been selected the Resample Window will appear. Here you will select the output file name. This will be the image that is orthorectified.

11. Navigate to a folder where you want the image to reside and give it a name. It will be given the .img extension.

12. Select the Elevation Library as the Elevation source. This is the file you have identified in

the previous section of Add Elevation Source to Elevation Library.

Fig.11. Resample Window (Orthorectification)

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Under Resample Method you have a few options, Nearest Neighbor, Bilinear Interpolation and Cubic Convolution. The Nearest Neighbor method provides the most spectral fidelity. It is the best option for scientific applications and spectral classification where the user may want the ‘most pure’ pixel. The 4X4 Cubic Convolution method provides a good balance between smoothness and sharpness. Bilinear interpolation results in an improvement in image quality over nearest-neighbor interpolation, but may still result in less-than-desirable smoothing effects. You may want to play with these methods and see which one produces the most desirable product for your purposes.

13. In this case we’ll select Nearest Neighbor as the default. For the remaining parameters we’ll leave the defaults.

14. When you are ready select OK and run your orthorectification. Navigate to your output folder and open your image in the IMAGINE Viewer to view your output Ortho Image.

15. In the file menu select File > Open> Raster Layer and navigate to the folder where your Ortho image resides.

For more information on ERDAS IMAGINE go to http://erdas.com/service/support/ERDASSupport.aspx For more technical information on DigitalGlobe Products and Services please visit the Resources tab at http://www.digitalglobe.com/

http://erdas.com/service/support/ERDASSupport.aspx

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Feature Extraction in ENVI EX using DigitalGlobe Multispectral Imagery

Introduction Feature Extraction is a module for extracting information from high-resolution panchromatic or multispectral imagery based on spatial, spectral, and texture characteristics. One can extract multiple features at a time, including vehicles, buildings, roads, bridges, rivers, lakes, and fields. Feature Extraction works well with DigitalGlobe image data in an optimized, user-friendly, and reproducible fashion so users can spend less time with processing details and more time interpreting results. Feature Extraction in ENVI EX uses an object-based approach to classify imagery. An object is a region of interest with spatial, spectral (brightness and color), and/or texture characteristics that describe the region. Traditional remote sensing classification techniques are pixel-based, meaning that spectral information in each pixel is used to classify imagery. While a pixel-based method works well in some situations, there are instances in which the object-based approach may be the best method. This tutorial focuses on the Object based approach. With high-resolution panchromatic or multispectral imagery, such as DigitalGlobe’s QuickBird, WorldView-1, and WorldView-2* satellites, an object-based method offers more flexibility in the types of features to be extracted. The Feature Extraction Workflow Feature Extraction is the combined process of segmenting an image into regions of pixels, computing attributes for each region to create objects, and classifying the objects (with rule-based or supervised classification) based on attributes to extract features. Extracting Impervious Features with Supervised Classif ication This tutorial simulates the workflow of a city planner who must identify all of the impervious surfaces in a neighborhood. Impervious surfaces include paved surfaces, rooftops, and other structures that replace naturally pervious soil with impervious materials. The total coverage by impervious surfaces in a given area affects urban air and water resources. City government officials often use the area of impervious surface on a given property as input into assessing its property tax. You will learn how to use Feature Extraction to extract impervious surfaces using supervised classification and save it to a polygon shapefile.

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Supervised classification in Feature Extraction is an iterative process. Best results are obtained by collecting a wide range of training samples, modifying classification parameters, and modifying computed attributes, all while previewing results on-the-fly. The process is not meant to be a quick-and-dirty, simple, linear workflow when the imagery is highly textured and consists of many spatially and spectrally heterogeneous features. *The eight (8) spectral bands of WorldView-2 provide greater accuracy in multispectral analysis applications. Since more of the visible spectrum is detected, more information is present in the imagery that comes from this sensor. For more information on WorldView-2’s eight spectral bands please refer to http://www.digitalglobe.com/sites/default/files/DG-8SPECTRAL-WP-WEB.pdf Opening and Displaying the Image

1. Start ENVI EX.

2. Double-click Feature Extraction in the Toolbox, which is the lower-left corner of the ENVI EX interface.

Fig.1. ENVI EX Toolbox

The Select Fx Input Files dialog appears.

3. Click Open File. The Open dialog appears.

4. Navigate to the folder where your DigitalGlobe Multispectral image resides. In this example, we select an image file named qb_colorado, and click Open. This image is a QuickBird, 4 band pan-sharpened, 0.6-m spatial resolution, subset saved to ENVI raster

http://www.digitalglobe.com/sites/default/files/DG-8SPECTRAL-WP-WEB.pdf

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format. You can create spectral and spatial subsets for use with Feature Extraction, but we will not do those steps in this exercise.

5. Click OK in the Select Fx Input files dialog. The Find Objects: Segment panel appears. You can drag this panel outside of the ENVI EX interface if it's obscuring the image.

Segmenting the Image

1. In the Find Objects: Segment panel, enable the Preview option to display a Preview Portal. ENVI EX segments the image into regions of pixels based on their spatial, spectral, and texture information. The Preview Portal shows the current segmentation results for a

portion of the image.

Fig.2. Find Objects Segment Panel

If you move your cursor to the top of the Portal, the Portal toolbar appears. You can use the Blend, Flicker, and Swipe tools on the Preview Portal toolbar to view the underlying layer. You can also use the Pan, Zoom, and Transparency tools on the main toolbar, although these are for display purposes only; they do not affect Feature Extraction results. You cannot adjust the Contrast,

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Brightness, Stretch, or Sharpen values in a Preview Portal. You can move the Preview Portal around the image or resize it to look at different areas.

2. Type 30.0 in the Scale Level field, and click Next to segment the entire image using this value.

ENVI EX creates a Region Means image, adds it to the Layer Manager, and displays it in the Image window. The new layer name is qb_coloradoRegionMeans. The Region Means image is a raster file that shows the results of the segmentation process. Each segment is assigned the mean band values of all the pixels that belong to that region. Feature Extraction proceeds to the Find Objects: Merge panel.

3. Merging allows you to group similar adjacent segments by re-assembling over-segmented or highly textured results. Type 90.0 in the Merge Level field, and press Enter. The Preview Portal updates to show how the new Merge Level affects the segments.

Fig.3. Merge Level Preview Portal

4. Click Next. Feature Extraction proceeds to the Find Objects: Refine panel.

5. The Refine step is an optional, advanced step that uses a technique called thresholding to

further adjust the segmentation of objects. Thresholding works best with point objects that have a high contrast relative to their background (for example, bright aircraft against a dark tarmac). You do not need to perform any thresholding on the image to extract impervious surfaces. Accept the default selection of No Thresholding, and click Next. Feature Extraction proceeds to the Find Objects: Compute Attributes panel.

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6. For this exercise, we will compute all available attributes. Ensure that all attribute

categories are selected under both the Attributes and Advanced tabs, and click Next. ENVI EX computes the attributes; this process takes a few minutes to complete. These attributes will be available for supervised classification. If you choose not to compute selected attributes when using Feature Extraction, you will save time in this step but will be unable to use those attributes for classification.

7. Feature Extraction proceeds to the Extract Features: Classify or Export panel. Select

Choose by Selecting Examples, and click next. Supervised Classification Supervised classification is the process of using training data to assign objects of unknown identity to one or more known features. The more features and training samples you select, the better the results from supervised classification. Training data consist of objects that you select as representative samples of known features. The Extract Features: Supervised Classification panel begins with one undefined feature (Feature_1, see figure below). As you move the mouse around the Region Means image, the objects underlying your cursor are highlighted with the color assigned to that feature. You may need to click once in the Image window to activate this function. This is normally how you would begin the process of collecting training data.

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Fig.4. Extract Features Panel Adding a New Feature and Collecting Training Data

1. In the Supervised Classification panel, click the Add Feature button . A new feature called “Feature_4” is added to the list. It contains no objects because you have not yet collected training data for this feature.

2. Right-click on Feature_4 and select Properties. The Properties dialog appears.

3. In this example we’ll change the Feature Name to Dirt Road, and click OK. You can also

change the color if you wish. The Feature List should look similar to the following:

Fig.5. Feature List

4. In this example we go back to the upper part of this particular image with a dirt road

5. The Dirt Road feature is selected by default. If the Preview Portal is still open, move it out of

the way before continuing since you cannot select training data through the Preview Portal. Click once in the Image window to activate the process of collecting training data for this feature. As you move around the image, the objects underlying the cursor are highlighted with the color assigned to the Dirt Road Feature.

6. Click to select objects representing the dirt road, as shown in the following figure. The color

of the objects change to the feature color, and the feature name updates to show the number of objects you added. Move around the entire image and choose a variety of different objects that represent dirt roads.

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Fig.6. Dirt Road Objects example

Here are a few more tips for selecting objects as training data:

To select multiple objects at once, click and drag the cursor to draw a box around the objects. ENVI EX assigns all of the segments that are completely enclosed within the selection box to the feature. Ctrl-Z undoes the box selection. Be careful using the selection box because you can easily select too many features, which will slow the performance of the Preview Portal.

To remove an individual object from the selection, click on the object. The feature name

updates to show one less object.

To see the boundaries of the individual objects, enable the Show Boundaries option in the Feature Extraction dialog.

Notice how the Preview Portal updates to show the new classification results in other parts of the image each time you select a new object and add to the training data set.

7. In the Feature Extraction dialog, select the Impervious feature.

8. Experiment with selecting more training data for the impervious feature, and possibly adding a new feature of your choice. Evaluate how these changes affect the classification of impervious surfaces.

Importing Ground Truth Data If you have access to Ground Truth Data for your data set you can optionally import this in the form of point and polygon shapefiles, when performing supervised classification. Ground truth data represent locations that researchers have visited and verified known feature types, thus it represents a true classification for specific areas of the image. In this exercise, we will open a sample ground truth file. If you do not have ground truth you may by-pass this section.

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1. Click the Import Truth Data from Shapefile button . The Select Vector Data for Import dialog appears.

2. Click Open File. A file selection dialog appears.

3. Navigate to the folder where your ground truth shapefiles reside, in this case we’ll select a

shapefile named qb_colorado_groundtruth.shp, and click Open.

4. Click OK in the Select Shapefile for Import dialog. The shapefile appears in the Image window (in the upper-right portion of the scene, outlined with a red box) and in the Layer Manager. The shapefile will remain in the Layer Manager throughout the rest of the Feature Extraction workflow.

Fig.7. Overview Window with ground truth shapefile

5. In the Image window, we’ll pan to the area of the shapefile (pixel coordinates for this example are approximately 1248, 218) and zoom in so we can better see the individual records.

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Fig.8. Ground Truth Shapefile

This shapefile is a fictional example of ground truth data that represents a GPS survey of different surface features on a single property. An Import Attributes dialog also appears, when you open the shapefile. This dialog is similar to the Vector Attributes dialog in ENVI EX. In the next step, we will use the Import Attributes dialog to associate shapefile records to the features you have defined in the Supervised Classification dialog.

6. You first need to indicate which feature you will associate a shapefile record with. In this example, we select the Dirt Road feature in the Supervised Classification dialog.

Fig.9. Features List Dirt Road Selection

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7. In the Import Attributes dialog, use the Shift key to select rows 7-10, which both contain

records named “dirt road.” The associated points are highlighted with a cyan color in the Image window.

Fig.10. Import Attributes Dialog

8. In the Import Attributes dialog, click Import Selected. ENVI EX adds the selected vector records to the Dirt Road feature by matching the points’ spatial locations with specific objects in the Region Means image (which is still available through the Layer Manager).

Note that three new objects were selected and colored dark blue, which is the color currently assigned to the Dirt Road feature. The feature name in the Supervised Classification dialog also updates to show the number of new objects added.

Fig.11. Dirt Roads Selection

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If you find that ENVI EX adds some unwanted or incorrect objects to a given feature, you can correct it with one of the following options:

You can remove an unwanted object from the Dirt Road feature by clicking on it, which removes the blue color. You can also continue with manually adding and deleting training samples for the feature, as described in "Adding a New Feature and Collecting Training Data" on pages 6 and 7.

We will not complete this step in this tutorial, but another option is to go

back to the Segment step and experiment with a lower Merge Level value,

which will result in more segments/objects.

9. Try selecting different records in the Import Attribute dialog (such as “field”) and

importing them into a different feature (such as Fields_Grasses). Remember, you first have to select the Fields_ Grasses feature in the Supervised Classification dialog so that ENVI EX will associate the selected records with that feature.

Modifying Attributes

1. Click the Attributes tab in the Supervised Classification panel. The attributes you computed earlier in the Compute Attribute step are used to further classify features. The training data file that you restored was created using all computed attributes (shown in the Selected Attributes list). Some attributes are more useful than others when differentiating objects. Classification results may not be as accurate when you use all attributes equally because the irrelevant attributes can introduce noise into the results.

2. Click the Auto Select Attributes button . ENVI EX selects the best attributes to use for classifying features.

Did this improve the classification of impervious surfaces? Remember that this is an iterative process and if you are not happy with your results you can try experimenting with your own set of attributes by following these steps:

3. Select one or more attributes from the Selected Attributes list, then click the Unselect

button to remove them from consideration. Again, the Preview Portal updates to show the changes to the classification.

4. To select individual attributes for classification, expand the Spectral, Texture, and Spatial

folders to see their respective attributes. Each attribute is shown with an icon. (The

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“Customized” folder contains the Color Space and Band Ratio attributes.) Click the Select

button to add the attribute to the Selected Attribute list.

5. Experiment with different combinations of spatial, spectral, texture, and customized attributes to determine the best results for classifying impervious surfaces. If you do not have time to select your own attributes, the Auto Select Attributes button often provides good results.

Modifying Classification Parameters

1. In the Supervised Classification panel, click the Algorithm tab.

2. From the Classification Algorithm drop-down list, select K Nearest Neighbor.

3. Click the Update button and examine the classification results in the Preview Portal. How did changing the supervised classification algorithm affect the classification of impervious surfaces?

4. Experiment with the two classification algorithms and try different values for each of their

associated parameters. Evaluate how these changes affect the classification of impervious surfaces, by clicking the Update button to update the Preview Portal. Following are some tips on using the parameters.

5. To restore the default values for all of the parameters, click the Reset button.

Saving Your Changes to a New Training Data File If you significantly improved the delineation of impervious surface boundaries by adding features, selecting more training data, importing ground truth data, experimenting with different attributes, and modifying classification parameters, you can choose to save your updated training data set to a new training data file.

1. In the Feature Extraction dialog, click the Features tab.

2. Click the Save Training Data As button . The Training Data dialog appears.

3. Select an output location and a new file name. Do not overwrite the training data file you restored earlier. This allows you to save an “iteration” of a training data set that you like in case you want to make further changes later. Click OK.

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If you ever want to revert back to the classification results from the original training data file, you can click the Restore Training Data button and select your training data. In this case we would select qb_colorado_supervised.xml. Creating a Shapefile of Impervious Surfaces

1. Click Next in the Supervised Classification panel. ENVI EX classifies the entire image. Feature Extraction proceeds to the Export Features panel.

2. The Export Vector Results option is selected by default so that you can output each feature

to separate shapefiles. Because you are only interested in extracting impervious surfaces, leave the Impervious option checked and un-select all of the other features. (Use the small scroll bar to see the other features.)

3. Feature Extraction provides an option to smooth your vector shapefiles using the Douglas-

Peucker line-simplification algorithm*. This Line simplification works best with highly curved features such as rivers and roads. In this example we select the Smoothing option and leave the default Smoothing Threshold value of 1.

4. Select an output directory to save your shapefile. By default, the shapefile will be named

according to the associated Feature name.

5. Ensure the Display Datasets After Export option is enabled. *More information may be found online by simply doing a search for “Douglas Peucker line-simplification algorithm”

6. Click Next. ENVI EX creates a shapefile of the impervious feature, adds it as a new vector layer to the Layer Manager, and displays it in the Image window.

Fig.12. Impervious features shapefile

7. In the Layer Manager, right-click on Impervious.shp (or whatever you named the output

shapefile) and select Properties. The Properties dialog appears.

8. Double-click inside the Fill Interior field, and select True.

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9. Choose a Fill Color, and close the dialog. The polygon shapefile is filled with color, which

makes the boundaries of impervious surfaces easier to discern. Exiting Feature Extraction After you export your classification results, you are presented with a summary of the processing options and settings you used throughout the Feature Extraction workflow. The Report tab lists the details of your settings, and the Statistics tab gives a summary of your feature name, feature count, and area statistics for the polygon shapefile you created. You can save this information to a text file by clicking the Save Text Report button. After viewing the processing summary, you can click Finish to exit the Feature Extraction workflow. Or, click Back to go back to the Export Features panel and change the output options for classification results. If you click Back, any output that you created is removed from the Data Manager and Layer Manager. If you click Next from the Export Features panel without making any changes, Feature Extraction will not re-create the output. You must make at least one change in the Export Features panel for Feature Extraction to create new shapefiles and/or classification images. For more information on ExelisVis ENVI EX product please visit http://www.exelisvis.com/ProductsServices/ENVIProducts.aspx For more technical information on DigitalGlobe Products and Services please visit the Resources tab at http://www.digitalglobe.com/

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Imagery Support Data (ISD) Documentation

v. 1.1.2

2 DigitalGlobe Imagery Support Data (ISD) Documentation v. 1.1.2 October 2014

Disclaimer & Copyright

Copyright © 2014

DigitalGlobe, Inc. All rights reserved.

Access to DigitalGlobe products and sensors is limited to existing re-seller terms and conditions.

THIS PUBLICATION IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NON-INFRINGEMENT.

THIS PUBLICATION COULD INCLUDE TECHNICAL INACCURACIES OR TYPOGRAPHICAL ERRORS. CHANGES ARE PERIODICALLY ADDED TO THE INFORMATION HEREIN; THESE CHANGES WILL BE INCORPORATED IN NEW EDITIONS OF THE PUBLICATION. DIGITALGLOBE MAY MAKE IMPROVEMENTS AND/OR CHANGES TO THE PRODUCT(S) AND/OR THE PROGRAM(S) DESCRIBED IN THIS PUBLICATION AT ANY TIME.


Contents Disclaimer & Copyright ........................................................................................................................... 2 List of Figures .......................................................................................................................................... 4 List of Tables ........................................................................................................................................... 5 1 Introduction ......................................................................................................................................... 6 2 Image Support Data ............................................................................................................................. 7

2.1 ISD File Description ..................................................................................................................................... 8 2.2 File Layout ................................................................................................................................................... 8

3 General Format and Conventions ..................................................................................................... 10 3.1 General File Format ................................................................................................................................... 10 3.2 PVL Format ................................................................................................................................................ 10 3.3 XML Format ............................................................................................................................................... 10 3.4 Coordinate Conventions ........................................................................................................................... 10

3.4.1 Earth Coordinates (E) ..................................................................................................................... 10 3.4.2 Image Coordinates ......................................................................................................................... 11 3.4.3 Time ............................................................................................................................................... 12

4 Delivery Level Support Data .............................................................................................................. 13 4.1 Delivery Index (README) Contents ........................................................................................................... 13 4.2 Delivery Layout File ................................................................................................................................... 16 4.3 Delivery Geographic Location Map Files ................................................................................................... 16

5 Product Component-Level Support Data .......................................................................................... 21 5.1 Product Component Index (README) ....................................................................................................... 21

6 Image Metadata ................................................................................................................................ 23 6.1 Image Metadata Content .......................................................................................................................... 23

6.1.1 Heights Above Ellipsoid (HAE) ....................................................................................................... 40 6.1.2 Product Level to Product Type Relationships ................................................................................ 41

6.2 Product Browse File .................................................................................................................................. 41 6.3 Tile Map .................................................................................................................................................... 42 6.4 Rational Polynomial Coefficients .............................................................................................................. 46 6.5 Product Component XML File ................................................................................................................... 49 6.6 Manifest File .............................................................................................................................................. 51 6.7 Stereo File ................................................................................................................................................. 52

Appendix A: Example PVL Format ........................................................................................................ 55 Appendix B: Example XML Format ....................................................................................................... 58 Appendix C: Example Tile Map File ...................................................................................................... 61 Glossary ................................................................................................................................................ 62 Index ..................................................................................................................................................... 68


List of Figures Figure 2.1 File Layout Diagram ................................................................................................................................................... 9 Figure 3.1 Earth Coordinate System ......................................................................................................................................... 11 Figure 3.2 Image Coordinate System ........................................................................................................................................ 11 Figure 6.1 Sample Product Browse File .................................................................................................................................... 41 Figure 6.2 Stereo Geometry Angles .......................................................................................................................................... 52


List of Tables Table 2.1 Image Support Data (ISD) Files Delivered by Product Type ........................................................................................ 7 Table 4.1 Top-Level Delivery Index (README) Contents (ISDF.DEL.README) .......................................................................... 13 Table 4.2 STRIP Shapefile Delivery Names and Attributes ........................................................................................................ 16 Table 4.3 ORDER Shapefile Delivery Names and Attributes ..................................................................................................... 17 Table 4.4 TILE Shapefile Delivery Names and Attributes .......................................................................................................... 18 Table 4.5 PRODUCT Shapefile Delivery Names and Attributes ................................................................................................. 18 Table 4.6 PIXEL Shapefile Delivery Names and Attributes ........................................................................................................ 19 Table 4.7 MOSAIC_CLOSEDPOLYGONS Shapefile Delivery Names and Attributes ................................................................... 19 Table 5.1 Product Component Index (README) Contents ....................................................................................................... 21 Table 6.1 Image Metadata Contents ........................................................................................................................................ 23 Table 6.2 Product Level to Product Type Relationships ............................................................................................................ 41 Table 6.3 Tile Map Contents ..................................................................................................................................................... 42 Table 6.4 RPC Terms ................................................................................................................................................................. 47 Table 6.5 RPC00B Contents ....................................................................................................................................................... 47 Table 6.6 Stereo File Contents .................................................................................................................................................. 53


1 Introduction This document describes the Image Support Data (ISD) format for DigitalGlobe Imagery products. These products are available in a variety of product types, and contain different ISD depending on the type of the product. This document describes the ISD, overall structure of files and specifies the data content and format of individual fields for the following DigitalGlobe product types: • Basic Products • Stereo Products • Standard Products • Orthorectified Products • Digital Elevation Model Products

This document also presents some technical information to explain the significance of the data.

The term “image” in this document often refers to a general two-dimensional image product, including a Digital Elevation Model (DEM) or another form of height model, as well as an image in the stricter sense. The context and the use of specific product type names should make it clear which meaning is intended.


2 Image Support Data All Imagery Products are delivered with a set of metadata files called Image Support Data (ISD). The number and types of files delivered varies depending on the product ordered. The ISD files can be viewed as a collection point for all useful ancillary data. Table 2.1 lists the Image Support Data files that are delivered with each product type.

Table 2.1 Image Support Data (ISD) Files Delivered by Product Type

FILE NAME EXTENSION BASIC IMAGERY STANDARD IMAGERY

ORTHORECTIFIED IMAGERY

Delivery-Level ISD

Top-Level Index (Readme) File .TXT XX XX XX

Top-Level Index (XML) File .XML XX XX XX

Layout File .JPG XX XX XX

Geographic Location Map Files .shx, .shp, .dbf XX XX XX

Manifest File .MAN FTP only FTP only FTP only

End of Transfer File .TXT FTP only FTP only FTP only

Product Component-Level ISD

Product Component Index (Subdirectory Readme) File .TXT XX XX XX

License File .TXT XX XX XX

Image Metadata File .IMD XX XX XX

Product Browse File .JPG XX XX XX

Tile Map File .TIL XX XX XX

Attitude File1 .ATT XX

Ephemeris File .EPH XX

Geometric Calibration File .GEO XX

RPC00B File .RPB XX XX

XML File .XML XX XX XX

1 For users of Basic products, refer to DigitalGlobe Imagery Support Data (ISD) Supplemental Documentation for Basic Products for information regarding the .ATT, .EPH, and .GEO.


FILE NAME EXTENSION BASIC IMAGERY STANDARD IMAGERY

ORTHORECTIFIED IMAGERY

Stereo Data File .STE XX XX

2.1 ISD File Description Products include Image Support Data (ISD) at two levels: one set of Delivery ISD, and one set of Product Component ISD for each product option ordered. The number of product components depends on the layout of the order polygon with respect to scene or strip boundaries. If the order polygon is entirely contained within a single scene or strip, then only one product component will be delivered. If an order polygon crosses strip or scene boundaries, then the imagery product will be divided into multiple product components. Product options include panchromatic, multispectral, or pan-sharpened.

The Delivery ISD (one set per delivery) consists of: • Top-Level Index (Readme) File. This file contains a list of names of the product files and the ISD files, along with copyright

information for the entire product delivery. • Top-Level Index XML File. This file contains the same information as the Top Level Index (README) file but in XML format. • Layout File. This file spatially illustrates how the delivery order is spread out across the media including product and order

polygon extents. The map includes volume and product labels. The file is in the standard JPEG format. Media volume information is not included for electronic deliveries.

• Geographic Location Map Files. These files spatially illustrate the product layout in a similar way to the layout file except in shapefile format. The files represent the order polygon, strip boundaries, product boundaries, and tile boundaries.

• Manifest File. The manifest file is included with electronic (FTP) deliveries only. The file contains the directory listing of the files delivered with the product.

• End of Transfer File. The end of transfer file is included with electronic (FTP) deliveries only. The appearance of this file on the FTP site indicates that DigitalGlobe has completed transferring all product files. It is a zero length file.

The Product Component ISD (one set per product component option) consists of: • Product Component Index (Subdirectory Readme) File. The README file provides copyright information and the names of the

ISD files for a single product within a delivery. • License File. The license file contains the text of the selected license. • Image Metadata File. The image metadata file describes key attributes about the image product, including product level,

corner coordinates, and projection information, and time of acquisition. • Product Browse File. The product browse file is a JPEG compressed browse image of the delivered product. • Tile Map. The tile map file assists the customer in determining what tile to ingest to look at a specific part of the order polygon. • Attitude File. The attitude file includes the time of first data point, the number of points, and the interval between the points

and attitude information. • Ephemeris File. The ephemeris file includes the time of first data point, the number of points, and the interval between the

points and ephemeris information. • Geometric Calibration File. The geometric calibration file contains the standard photogrammetric parameters of a virtual

camera that models the corresponding camera and optical system for Basic Imagery products. • RPC00B File. The RPC00B file contains the RPC information, which can be used to rectify the image. This is a mathematical

mapping from object space coordinates to image space coordinates. • XML File. This file contains the same information as the combined README, Licensing, Image Metadata, Tile Map and RPC00B

files, in XML format. For Basic Imagery Products, the attitude, ephemeris, and geometric calibration file are included as well. • Stereo File. This file is provided with Stereo pairs. It identifies each image in the stereo pair and describes the stereo ground

coverage and viewing geometry.

2.2 File Layout This section describes the structure by which the Image Support Data (ISD) files are organized for delivery. Figure 2.1 displays the layout as it applies to delivery of imagery and ISD files for all media types. Product Level Directories are


identified with the product ID and a three-character descriptor: PAN for Panchromatic, MUL for Multispectral, PSH for Pansharpened, and MOS for Mosaicked products.

Figure 2.1 File Layout Diagram


3 General Format and Conventions 3.1 General File Format Image Support Data (ISD) files are provided in the Parameter Value Language (PVL). The information in PVL format is provided in multiple files while the information in XML is provided in a single file. The information provided in PVL and XML are the same semantically but differ only in syntax.

3.2 PVL Format Each tag consists of a variable length parameter name and a parameter value, in the form parameterName = value followed by a semi-colon. The value can be an integer (decimal, binary, octal, or hexadecimal), a floating-point number, a character string (one or more characters), a coordinate universal time (UTC), a set, or a list. The format for UTC time is YYYY-MM-DDThh:mm:ss.ddddddZ. Character strings values must be enclosed in double quotation marks. Sets are delimited by { }, and lists are delimited by ( ). Nested sets and lists are allowed. Comments in the file begin with a slash-asterisk (/*) and end with an asterisk-slash (*/).

Named groups begin with BEGIN_GROUP = GROUPNAME and end with END_GROUP = GROUPNAME. Nested groups are allowed. The end of a PVL module is indicated by the keyword END, followed by a semi-colon.

Only required fields need to be specified in the ISD files.

For an example of the PVL-formatted file, please see Appendix A: Example PVL-Format on page 55.

3.3 XML Format All the information contained in the PVL ISD files is also provided in XML format. For an example of the possible XML formatted file, please see Appendix B: Example XML Format on page 58.

3.4 Coordinate Conventions For geolocation purposes, Image Support Data (ISD), for all product types, references both image coordinates and earth coordinates as described in the following sections.

3.4.1 Earth Coordinates (E)

Earth coordinates are expressed relative to an earth-centered fixed (ECF) reference system that rotates with the earth. In particular, all ECF coordinates in ISD files are given in the WGS 84 reference system, including geocentric cartesian coordinates (XE, YE, ZE) and geodetic coordinates (latitude, longitude). The WGS 84 ZE-axis points in the direction of the Conventional Terrestrial Pole (CTP); the XE-axis lies along the intersection of the meridian plane and the CTP equator, pointing outward at Greenwich; the YE-axis completes the right-handed orthogonal coordinate system.


Figure 3.1 Earth Coordinate System

All heights are in meters with respect to the WGS 84 ellipsoid.

All easting and northing values in any of the ISD are specified in the projection determined by the datum and map projection fields in the image metadata file.

3.4.2 Image Coordinates

An image address is specified as a (column, row) pair. When the image is displayed, column numbers increase toward the right and row numbers increase in the downward direction. Address (0, 0) corresponds to the pixel displayed in the upper left corner. Adherence to these display conventions ensures that a displayed image will have the same sense as an aerial view of the ground—differing from an aerial view by a proper rotation.

0 1 2 3 N-14 column numbers

012

M-1 (N-1, M-1)

(0,0)

rownumbers

Figure 3.2 Image Coordinate System

YE

ZE

XE

Equatorial planePrime meridian


The detector in column 0 of a detector array produces the pixels in column 0 of the corresponding Basic image.

The ground location of a specific pixel in the image is the geolocation of the center of that pixel.

3.4.3 Time

All absolute times are in Coordinated Universal Time (UTC) in the format YYYY-MM-DDThh:mm:ss.ddddddZ.

Relative time offsets from a fixed absolute time are measured in seconds, unless specified otherwise.

An example of both absolute UTC time and relative time is the time-tagged line count (TLC) data in the image metadata file. The TLC data, which are pairs of line numbers and the associated exposure times, provide a way to accurately estimate the time of exposure of any line in the image. The first such timing event for an image is reported in the image metadata file as an absolute UTC time, but subsequent events are reported as time offsets, in seconds, relative to this initial time.


4 Delivery Level Support Data 4.1 Delivery Index (README) Contents The Delivery Index contains a list of names of the product files and the Image Support Data (ISD) files, along with copyright information for the entire product delivery. The Delivery Index is found in a Top Level README file and a Top Level XML file delivered with each delivery, and each describes all of the files for all of the products delivered within that delivery. The README file and the XML file contain the same information. The Top Level README File is named for the 12-digit DigitalGlobe Order Item number and the 2-digit delivery increment, for example: 000000077583_01_README.TXT and 000000077583_01_README.XML. Table 4.1 defines the Top Level Delivery Index (README) contents.

Table 4.1 Top-Level Delivery Index (README) Contents (ISDF.DEL.README)

FIELD FIELD NAME / DESCRIPTION

FORMAT RANGE / VALUE [DG RANGE / VALUE, IF DIFFERENT FROM

FORMAT RANGE / VALUE]

CONDITIONS / COMMENTS

version Version of the ISD. “20.0” to “99.99”

copyrightText Copyright and restricted use text.

“Use, duplication or disclosure by the government is subject to the restrictions as set forth in subparagraph (c)(1)(ii) of the Rights in Technical Data and Computer Software Clause contained in D.F.A.R.S. 252.227-7013, and subparagraphs (c)(1) and (2) of the Commercial Computer Software-Restricted Rights contained in 48 C.F.R. 52.227-19. Contractor/manufacturer is DigitalGlobe, Incorporated at 1601 Dry Creek Drive, Suite 260, Longmont, CO 80503-6493. Copyright YYYY DigitalGlobe Incorporated, Longmont CO USA 80503-6493 DigitalGlobe and the DigitalGlobe logo are trademarks of DigitalGlobe, Incorporated. The use and/or dissemination of this data and/or of any product in any way derived there from are restricted. Unauthorized use and/or dissemination is prohibited. DigitalGlobe WWW Reference: http://www.digitalglobe.com”

2nd paragraph Copyright YYYY DigitalGlobe ... Where yyyy is the current year

mediaCreationDate Time of media creation. YYYY-MM-DDThh:mm:ss.dddddZ

The time in this tag has precision to 6 decimal places.

orderNumber

12-digit DigitalGlobe Order Item number, underscore, and 2-digit delivery increment.

“nnnnnnnnnnnn_mm” Example: “052265559010_01”






fileList A list of all files in the delivery including path directories.

Lists all filenames such as: GIS files Metadata files Product files

This field will vary depending on product type.

areaDesc

Customer supplied description of order. “Null” if no information supplied by the customer.

Example: “IS_05”

dgOrderNo DigitalGlobe Order Number. Example: “052265559”

dgOrderItemNo 12-digit DigitalGlobe Order Item Number. Example: “05226559010”

custOrderNo

Customer supplied order number. ‘Null’ if no information supplied by the customer.

Example: “IS_05”

custOrderItemNo

Customer supplied order item number. ‘Null’ if no information supplied by the customer.

Example: “40005” “40009” “1” “Null”

collectionStart Date of first image acquisition. YYYY-MM-DDThh:mm:ss.ddddddZ

collectionStop Date of final image acquisition. YYYY-MM-DDThh:mm:ss.ddddddZ

countryCode Two letter country code of center point of order polygon.

Example: “ ” Currently blank.

productScale The NMAS mapping scale of Orthorectified Products.

Level 3A: “1:50,000” Level 3D: “1:12,000” Level 3E: “1:10,000” Level 3F: “1:5,000” Level 3G: “1:4,800” Level 3X: “Custom”

Only applicable to Orthorectified (level 3) products.






numberOfLooks Indicates whether this is a single product or a stereo pair.

“1” for single, “2” for stereo pair

cloudCover

Estimate of the max cloud-covered fraction of the delivery. For mosaic products, this calculation is based on the intersection of the polygons contained in the MOSAIC_CLOSEDPOLYGONS shapefile with the cloud polygons associated with that part of the relevent input imagery.

0.000 to 1.000 Precision: 3 decimal places -999.0 if not assessed

nwLat

Latitude of NW corner of the minimum bounding rectangle (MBR) of the order polygon.

Range: ± 90.00000000 Precision: 8 decimal places

nwLong

Longitude of NW corner of the minimum bounding rectangle (MBR) of the order polygon.


seLat

Latitude of SE corner of the minimum bounding rectangle (MBR) of the order polygon.


seLong

Longitude of SE corner of the minimum bounding rectangle (MBR) of the order polygon.



4.2 Delivery Layout File The Layout file illustrates the following: • Outline of the Product area (order polygon) • Outline of the Product Component areas (product polygon) • Distribution of the above areas on the delivery media

The Layout file is an image file in JPEG format, without any additional attributes. The information contained in this file is not duplicated in the Top Level XML file.

4.3 Delivery Geographic Location Map Files Geographic Location Map files are similar to the Product Component Data files (Section 5) but in Shapefile format, projected to WGS84 Geographic (Lat/Lon). Table 4.2 through Table 4.7 define the Delivery Shapefiles contents. These product shapefiles are delivered as read/writable ASCII text files.

DigitalGlobe provides the following Geographic Location Map files with every delivery: • Strip or Substrip Area. This file shows the vertices and boundaries of the strips or substrips used to generate the

product, as well as the catalog ID for each of these areas. For example: 052265559010_01_STRIP_SHAPE.dbf • Product Area. This file shows the vertices and boundaries of the complete product as ordered by the customer. For

example: 052265559010_01_ORDER_SHAPE.dbf • Product Component Areas. This file shows the vertices and boundaries of the product components that make up the

delivery, and the allocation of the product components to media. For example: 052265559010_01_PRODUCT_SHAPE.dbf

• Product Subcomponent Areas. This file shows the vertices, boundaries, name, and filename of each tile or sub-strip in the product components, as well as the product component to which each belongs. Example filename: 052265559010_01_TILE_SHAPE.dbf

• Product Pixel Area. This file shows the vertices and boundaries of actual imagery pixels of the product components that make up the delivery (non-blackfill pixels.) In the Product Pixel area shapefile, the 12-digit DigitalGlobe Order Item number and the 2-digit delivery increment (SOLI) is pre-pended by an acquisition date-time of one of the contributing raw images along with a mnemonic that describes the product level as in the following example: 08JUL30153254-P2AS-052265559010_01_P001_PIXEL_SHAPE.dbf

For ortho-mosaic products, DigitalGlobe delivers an additional Geographic Location Map file for each product: • Mosaic seamlines. This file shows the vertices and boundaries of each image strip that contributed to the generation of

the mosaic. The Mosaic seamline <shapefile name> has the DigitalGlobe order’s part ID (for example, P001) pre-pended. For example: 052270931010_01_P001_MOSAIC_CLOSEDPOLYGONS_SHAPE.dbf

Table 4.2 STRIP Shapefile Delivery Names and Attributes

FIELD FIELD NAME / DESCRIPTION FORMAT RANGE / VALUE [DG RANGE / VALUE, IF

DIFFERENT FROM FORMAT RANGE / VALUE]


stripDesc Catalog ID corresponding with associated strip or substrip Example: “10100100017C2400”


FIELD FIELD NAME / DESCRIPTION FORMAT RANGE / VALUE [DG RANGE / VALUE, IF



sunAzimuth Azimuth angle of the sun measured from north clockwise, in degrees, at the time the strip or substrip was acquired.

Range: 0.0 – 360.0 Decimal precision may vary.

offNadir

The spacecraft elevation angle measured from nadir to the image center as seen from the spacecraft at the time the strip or substrip was acquired.

Range: ≥ 0.0 Decimal precision may vary.

acquisitio Populated with the strip acquisition date-time. Example: “2002-12-29T15:58:08.626765Z”

Table 4.3 ORDER Shapefile Delivery Names and Attributes


FORMAT RANGE / VALUE [DG RANGE / VALUE, IF DIFFERENT

FROM FORMAT RANGE / VALUE]


orderDesc Item number corresponding with associated order polygon.

Example: “052265559010” This is the 12-digit DigitalGlobe Order Item number. Required, if available.

custOrd Optional order number supplied by the customer at time of order placement.

Example: “IS_46” Only if customer has supplied order number. Required, if available.

custOrdItm Optional order item number supplied by the customer at time of order placement.

Example: “40005” Only if customer has supplied order item. Required, if available.

datum The Datum in which the product was ordered.

“WE” (WGS84) “NAR” (NAD83) “NAS” (NAD27) “TOYM” (Toyko Mean) “GRS80” (GRS80)

Blank for Basic (1B) products.

projection The projection in which the product was ordered.

“UTM” “State Plane Coordinates” “Japan RCS Coordinates” “Geographic (Lat/Long)”

Blank for Basic (1B) products.

createDate Start date of product creation. YYYY-MM-DDThh:mm:ss.ddddddZ


Table 4.4 TILE Shapefile Delivery Names and Attributes





tileName Tile Name

If R or C ≤ 9: “RnCn” If R or C ≤ 99: “RnnCnn” If R or C ≤ 999: “RnnnCnnn” Examples: “R1C1” “R19C3” RegionTile Example: “iz_20071231_uncl_ci_ 322230n1153730w_imagery.tif”

Rows and Columns do not have to be of the same order of magnitude. For example: A tile of a mosaic with 6 columns and 15 rows would be displayed as: RnnCn

fileName Name of the image file. Example: “02JUN25001236-2AS_R1C1-000000092184_01_P001.NTF”

prodDesc Unique product identifier Example: “P001” Required, if available.

volNum Volume number of the media on which the tile is located.

Example: “Vol. 1”

Table 4.5 PRODUCT Shapefile Delivery Names and Attributes

FIELD FIELD NAME / DESCRIPTION FORMAT RANGE / VALUE [DG RANGE / VALUE, IF DIFFERENT



prodDesc Unique product identifier Example: “P001”

volNum Volume number of the media on which the tile is located. Example: “Vol. 1-2”

bandInfo Defines type of spectral bands in product. (PanSharp, Multispectral, All Band, Panchromatic).

“PanSharp” “Multispectral” “All Band” “Panchromatic”


Table 4.6 PIXEL Shapefile Delivery Names and Attributes

FIELD FIELD NAME / DESCRIPTION FORMAT RANGE / VALUE [DG RANGE / VALUE, IF DIFFERENT FROM



prodDesc Unique product identifier Example: “3AUG27021804-M2AS-005357007010_01_P001_PIXEL_SHAPE”

volNum Volume number of the media on which the tile is located. Example: “Vol. 1-2”

Table 4.7 MOSAIC_CLOSEDPOLYGONS Shapefile Delivery Names and Attributes




imageIdStr Imagery identifier Example: “10100100012BEA00”

acqDate Imagery acquisition date YYYY-MM-DDThh:mm:ss.ddddddZ

gsd Ground sample distance in meters Range: 0.10000 – 100.00000 Precision: 5 decimal places

For validation, this range is 0.10000 to 100.00000.

horError Requested product accuracy from the order

Range: 0.00000 – 15.44000 Precision: 5 decimal places

cloudCover

Cloud cover percentage is calculated by intersecting the closed polygon with cloud polygons from the underlying image strips.

Range: 0.00000 to 100.00000 Precision: 5 decimal places

offNadir Angle from s/c to strip crosstract center.


Can be exceeded with reduced image quality.

scanAz Image scan azimuth.

Examples for cardinal direction, but allow for all permutation including angles: “North-to-South” “South-to-North” “East-to-West” “West-to-East”

scanDir Image scan direction. “Forward” “Reverse”

collectAz The orientation angle of the generated collection strip relative to true north.






collectEl

The collection elevation is the angle between the horizontal and the ray originating from the optical center to the point of incidence.


sunAz Sun azimuth. Range: 0.00000 – 360.00000 Precision: 5 decimal places

sunEl Sun elevation. Range: 0.00000 – 90.00000 Precision: 5 decimal places

satellite Satellite mnemonic “QB02”, “WV01”, “WV02”, “Aerial”, “GE01”, “WV03”

prodDate Production generation date “YYYYMMDD”

currDate Production generation date “YYYYMMDD”

collDate Date of image collection “YYYYMMDD”

absAcc Product absolute accuracy Range: 0.00000 – 100.00000 Precision: 5 decimal places

absAccUnit Absolute accuracy units “Meters”

relAcc Product relative accuracy Range: 0.00000 – 100.00000 Precision: 5 decimal places

relAccUnit Relative accuracy units “Meters”


5 Product Component-Level Support Data 5.1 Product Component Index (README) The Product Component Index lists the names of the image, browse, and ISD files in each product component subdirectory of a delivery. Other ISD files may or may not be included in a delivery depending on the type of the products in the order. One Product Component Index is provided for each product component of each delivery within the product component subdirectory. Table 5.1 defines the Product Component Index contents.

Table 5.1 Product Component Index (README) Contents





copyrightText Copyright and restricted use text

“(C) COPYRIGHT yyyy DigitalGlobe, Inc., Longmont CO USA 80503. DigitalGlobe and the DigitalGlobe logos are trademarks of DigitalGlobe, Inc. The use and/or dissemination of this data and/or of any product in any way derived there from are restricted. Unauthorized use and/or dissemination is prohibited.”

Where yyyy is the current year

version Version of the ISD “20.0” to “99.99”

intro

Introduction. General textual information about the product and file contents.

“Thank you for ordering from DigitalGlobe! This directory contains both an Imagery Product and the corresponding Image Support Data (ISD) files that fulfill your order. The naming convention for the image is <acquisition time>-<product info>-<product id>.<format extension>”

BEGIN_GROUP=PROUDCT_1

XMLFilename Product Component XML file

“productname.XML”

licenseTxtFilename Licensing text file name

“BASE.TXT” “GROUP.TXT” “ENTERPRISE.TXT” “ENTERPRISE_PREM.TXT” “EDUCATIONAL.TXT” “DEMONSTRATION.TXT”

Predicated on license order parameter.

IMFFilename Image metadata file name “productname.IMD”

ephemFilename Ephemeris file name “productname.EPH” Only for Basic (1B) products.

attFilename Attitude file name “productname.ATT” Only for Basic (1B) products.






tilFilename Tile map file name “productname.TIL”

geoCalFilename Geometric calibration file name “productname.GEO” Only for Basic

(1B) products.

stereoFilename Stereo file name “productname.STE” Only valid for stereo products

RPC00BFilename RPC00B file name “productname.RPB” Not applicable to Orthorectified (level 3) products.

END_GROUP=PRODUCT_1

END;


6 Image Metadata 6.1 Image Metadata Content For ortho-mosaics, if an input image is not used as part of the final product, it will not be represented in the Image Metadata Data (IMD). All other input images will be represented in the IMD and will appear in order of their acquisition date-timestamp with the oldest image appearing first. The date-timestamp of the oldest image will be used as part of the product filenames.

The Image Metadata specifies the basic characteristics of an image or a DEM as specified in Table 6.1.

Table 6.1 Image Metadata Contents


FORMAT RANGE / VALUE

[DG RANGE / VALUE, IF DIFFERENT FROM



version Version of the ISD “20.0” to “99.99”

generationTime Time of file generation. YYYY-MM-DDThh:mm:ss.ddddddZ

productOrderId Order Item ID of product Example: “052270730010_01_P001”

Optional if product does not originate from DigitalGlobe or co-producer.

productCatalogID ID for the corresponding record in DG’s catalog. In multi-set products this would be the “group catalog id”.

Example: “903001004AA74B00” “None”

“None” if catalog not kept in DigitalGlobe archive.

childCatalogID

ID for the corresponding record in DG’s catalog (for multi-set products this would be the “child” or “subset” catalog id). In cases where children products do not have separate IMD files, this field may be repeated.

Example: “210001004AA74C00” “None”

Used only with multi-set products

imageDescriptor This is a combination of product name and product type.

“Basic1B", "Standard2A", "ORStandard2A", "OrthoRectified3", "Stereo1B", “StereoOR2A”, "DEM4”







productScale This is the NMAS mapping scale of the Orthorectified Product

Values: Level 3A: “1:50,000” Level 3D: “1:12,000” Level 3E: “1:10,000” Level 3F: “1:5,000” Level 3G: “1:4,800” Level 3X: “Custom”

Only applicable to Orthorectified (level 3) products. For validation purposes, this shoudl be evaluted as a text string tha tis not bound by enumeration.

productAccuracy Identifies the worst case CE90% in meters for the associated productScale.

Values: Level 3A: 25.40 Level 3D: 10.16 Level 3E: 8.47 Level 3F: 4.23 Level 3G: 4.06 “unavailable”

Only applicable to Orthorectified (level 3) products. For validation purposes, the actuals may range from 0.1 to 100.00.

RMSE2D Two Dimensional Root Mean Square Error

Values: Level 3A: 15.44 Level 3D: 6.18 Level 3E: 5.15 Level 3F: 2.57 Level 3G: 2.47 Level 3X: 0.00 Precision: 2 decimal places

Only applicable for Orthorectified (level 3) products. Level 3X uses customer supplied data. For example, DEM(s), GCPs or both. Therefore, DG does not guarantee accuracy. For validation purposes, the actual values range from 0.1 to 99.00.







bandId

Identifies the spectral band. “P” = Panchromatic, “Multi” = all VNIR Multi-spectral bands (4 for QB02,GE01 and 8 for WV02, WV03) “N” = Near–InfraRed “R” = Red “G” = Green “B” = Blue "RGB" = Red + Green + Blue "NRG" = Near-IR + Red + Green, “BGRN” = Blue + Green + Red + Near-IR RGB, NRG, and BGRN are pan-sharpened color images, stored at the panchromatic spatial resolution. For WorldView-2 and WorldView-3 there are also the following bands: “N2”=NIR2 “RE”=Red Edge “Y”=Yellow “C”=Coastal “MS1”=First 4 bands (N,R,G,B) “MS2”=Second 4 bands (N2,RE,Y,C) For a DEM, this field indicates the spectral band (Pan) used to create the product.

“P” “Multi” “N” “R” “G” “B” “RGB” “NRG” “BGRN” “N2“ “RE“ “Y“ “C“ “MS1“ “MS2“

N2, RE, Y and C in any band combination are available for WorldView-2 and WorldView-3 only. For validation, this field is constrained by the following definition: A-Za-z0-9 (alphanumeric) plus '-' for up to 7 (1 to 7) characters.

panSharpenAlgorithm

Identifies the algorithm used to create pan-sharpened products: UNB = University of New Brunswick

“UNB” “None”

numRows Number of rows. 1 – N

numColumns Number of columns. 1 – N

productLevel

Product level that indicates the radiometric and geometric corrections for backward compatibility in terms of Product Type.

“LV1B”, “LV2A”, “LV3A”, “LV3D”, “LV3E”, “LV3F”, “LV3G”, “LV3X”, “LV4”, “Stereo 1B”, “Stereo 2A”, “Stereo OR2A”

Refer to Table 4.5 for a definition of Product Levels.







productType Product type “Basic”, “Stereo”, “Standard”, “Ortho”, “DEM”

numberOfLooks Indicates whether this is a single product or a stereo pair

Non-Stereo: 1 Stereo Pair: 2

radiometricLevel Options for radiometric correction. “Corrected” Not applicable for a DEM product.

radiometricEnhancement

Option for Color Correction and Contrast Enhancement

“DRA/Color” “DRA/Contrast” “Off”

Standard (level2), Stereo OR2A (level2A), and Orthorectified (level 3) Products only.

bitsPerPixel

The number of bits per pixel in the product image files. If the product is compressed, this value is the original bits per pixel, before compression. This value will be either 8 or 16, depending on the product. Note that this is the number of bits stored in the image file for each pixel value as opposed to the number of significant bits that define the pixel brightness value. That is, for a product which is delivered as 16 bits per pixel, only 11 bits define the brightness value of each pixel.

8 16

restrictedAreaIntersect

Portions of the strip intersecting the restricted area have been modified to meet the allowable GSD.

“Yes”

This field will only be included if the strip intersects the restricted area and has been modified to meet the allowable GSD.

compressionType The type of compression, if any, applied to the product imagery.

“None” “JPEG2000”

This field will not be included in Metadata products.

jpegProfileName Name of the DigitalGlobe JPEG2000 profile applied.

“DG commercial 2.5” “DG commercial 12” “DG commercial 10:1” “DG commercial 8:1” “DG commercial 4:1”

Included only when the compression type is JPEG2000.







The following group is repeated for each spectral band in the delivered image product. The index b in the group name is one of (P,N,R,G,B, N2,RE,Y,C) to differentiate the band group names. In this group, latitudes (Lat) and longitudes (Lon) are in degrees and heights above the

WGS 84 ellipsoid (HAE) are in meters.

BEGIN_GROUP=BAND_b

ULLon Geodetic longitude of the upper left pixel of the image.


ULLat Geodetic latitude of the upper left pixel of the image.


ULHAE Height above the ellipse of the upper left pixel of the image. Precision: 2 decimal places

URLon Geodetic longitude of the upper right pixel of the image.


URLat Geodetic latitude of the upper right pixel of the image.


URHAE Height above the ellipse of the upper right pixel of the image. Precision: 2 decimal places

LRLon Geodetic longitude of the lower right pixel of the image.


LRLat Geodetic latitude of the lower right pixel of the image.


LRHAE Height above the ellipse of the lower right pixel of the image. Precision: 2 decimal places

LLLon Geodetic longitude of the lower left pixel of the image.


LLLat Geodetic latitude of the lower left pixel of the image.


LLHAE Height above the ellipse of the lower left pixel of the image. Precision: 2 decimal places







absCalFactor

The conversion factor, KnTDI, that converts the relative radiance values in an image file into corresponding absolute radiance, measured in watts/sq m/ster. This is calibrated 6000 °K blackbody radiance, integrated over the appropriate spectral window.

Example: 6.447600e-02 -999 = “None” when radiometricEnhancement = “DRA”.

effectiveBandwidth

The effective bandwidth is associated with the absCalFactor and it's value is required to calculate top-of-atmosphere spectral radiance.

0.0000 to 1.0000 scientific notation

TDILevel Level of the time-delayed integration, as commanded to the spacecraft.

Values: PAN: 6, 8, 10, 13, 16, 18, 24, 32, 48, 56, 64 MS: 1, 3, 6, 10, 14, 18, 21, 24 GE01 Pan: 8, 16, 32, 48, 64 MS (mode 13/24): 3, 6, 10 , 14, 18, 21, 24

1 only valid for QuickBird MS image.

END_GROUP=BAND_b

outputFormat

External product format. GeoTIFF and NITF are image formats for Basic, Stereo, Standard and Orthorectified products. CIB is an image format for orthorectified 1:24,000 and 1:12,000, while DTED, USGS DEM, and ASCII DTM are digital elevation model formats for DEM products.

“GeoTIFF” “NITF20” “NITF21” “NITF21NCDRD” “TIFF” “CIB” “DTED” “USGS DEM” “ASCII DTM” “J2K” “GeoJP2” “GeoPDF” “MrSID” “RPF” “KIP” “IMG”







The following group is repeated for each n = 1,…,numImagesInProduct. That is, for all images used to create the image product. For single image products (Basic) there is one .IMD file per source image or strip, so the group will appear only once for each product component. For multiple image products (Stereo, Standard, and Orthorectified), the following group will be repeated for each source image in the image product. The index “n” in the group name is a sequential number of the image used to produce the product (1,2,3,…,n) to differentiate the image group names. The image with the earliest aquisition time will be assigned n = 1, and incremented in ascending order.

BEGIN_GROUP=IMAGE_n

satId Satellite Id. “QB02”, “WV01”, “WV02”, “GE01”, “WV03”

mode Sensor Mode. “FullSwath”, “CenterSwath”

Only “FullSwath” for QuickBird.

scanDirection Sensor scan direction. “Forward”, “Reverse” Only “Forward” for QuickBird

CatId

DigitalGlobe catalog Id for the raw data used in this product. For mosaics, only strips used in the mosaic creation should be listed. The catalog ids are ordered from earliest aquisition to latest.

Example: “1020010007AF7100”

For each sub-strip or area based product.

TLCTime Absolute time of the first time-tagged line count record, used in the product component.

YYYY-MM-DDThh:mm:ss.ddddddZ

Only for Level 1B products.

numTLC Number of time-tagged line count records in the TLCList used in the product component.

Range: ≥ 1 Only for Level 1B products.







TLCList

List of time-tagged line count (TLC) records. Each TLC record consists of lineNumber (Short) timeOffset (Float) lineNumber is the image line number for a line in the product component. This number will be negative if the TLC record precedes the product component. timeOffset is the recorded time tag for this line, in seconds after TLCTime. The timeOffset will be negative if the image is in the reverse scan direction.

Example: ( (-256, 0.000000) , (768, 0.148404), ... (N, N.nnnnnn) ) Precision: TLCTime will have 6 decimal places precision.

Only for Level 1B products.

firstLineTime Exposure time for the first line in the strip used for the product component.


avgLineRate Average number of image lines exposed per second. Precision: 2 decimal places

For Pan-Sharpened products, this will be equal to the average MS line rate.

exposureDuration Duration of the exposure interval for each line.

Value: 1/avgLineRate for VNIR Precision: up to 9 decimal places

Precision may not run to 9 if there are trailing zeroes.

minCollectedRowGSD

Minimum original collected GSD of the product in the row direction.

Range: 0.100-100.000 Precision: 3 decimal places The Pan GSD is used for

Panchromatic and Pan-sharpened products; the MS GSD is used for MS products. These value ranges are based on 0 to 45 degrees off nadir for all sensors with regard to VNIR. For validation all GSD values will range from 0.1 to 100.000 which allows for a range of subsampling.

maxCollectedRowGSD

Maximum original collected GSD of the product in the row direction.

Range: 0.100-100.000 Precision: 3 decimal places

meanCollectedRowGSD

Mean original collected GSD of the product in the row direction.


minCollectedColGSD

Minimum original collected GSD of the product in the column direction.


maxCollectedColGSD

Maximum original collected GSD of the product in the column direction.


meanCollectedColGSD

Mean original collected GSD of the product in the column direction.








meanCollectedGSD Mean GSD of the original, collected row and column GSD.


meanProductRowGSD

Mean GSD of the product in the row direction.


Applicable to Level 1B products only.

meanProductColGSD

Mean GSD of the product in the column direction.



meanProductGSD Mean GSD of the product row and column GSD.



rowUncertainty Mean position uncertainty in line and pixel directions. These are 3-sigma, one-dimensional values.

Precision: 2 decimal places

colUncertainty Mean position uncertainty in line and pixel directions These are 3-sigma, one-dimensional values.


minSunAz Minimum azimuth angle of the sun measured from north clockwise.

Range: 0.0 to 360.0 Precision: One decimal point

maxSunAz Maximum azimuth angle of the sun measured from north clockwise.


meanSunAz Mean azimuth angle of the sun measured from north clockwise.


minSunEl Minimum elevation angle of the sun from horizontal.

Range: ± 90.0 Precision: One decimal point

maxSunEl Maximum elevation angle of the sun from horizontal.


meanSunEl Mean elevation angle of the sun from horizontal.








minSatAz Minimum azimuth angle of the satellite with respect to the center line, in degrees.


maxSatAz Maximum azimuth angle of the satellite with respect to the center line.


meanSatAz Mean azimuth angle of the satellite with respect to the center line.


minSatEl Minimum elevation angle of the satellite with respect to the center line.


maxSatEl Maximum elevation angle of the satellite with respect to the center line.


meanSatEl Mean elevation angle of the satellite with respect to the center line.


minInTrackViewAngle

Minimum dihedral angle measured at the spacecraft from the nominal spacecraft YZ plane to the plane that contains the ground projection of the product center-line and the spacecraft Y-axis. A positive angle indicates the sensor is looking forward.


maxInTrackViewAngle

Maximum dihedral angle measured at the spacecraft from the nominal spacecraft YZ plane to the plane that contains the ground projection of the product center-line and the spacecraft Y-axis. A positive angle indicates the sensor is looking forward.








meanInTrackViewAngle

Mean dihedral angle measured at the spacecraft from the nominal spacecraft YZ plane to the plane that contains the ground projection of the product center-line and the spacecraft Y-axis. A positive angle indicates the sensor is looking forward.


minCrossTrackViewAngle

Minimum dihedral angle measured at the spacecraft from the nominal spacecraft XZ plane to the plane that contains the ground projection of the product center-line and the spacecraft X-axis. A positive angle indicates the sensor is looking to the right.


maxCrossTrackViewAngle

Maximum dihedral angle measured at the spacecraft from the nominal spacecraft XZ plane to the plane that contains the ground projection of the product center-line and the spacecraft X-axis. A positive angle indicates the sensor is looking to the right.


meanCrossTrackViewAngle

Mean dihedral angle measured at the spacecraft from the nominal spacecraft XZ plane to the plane that contains the ground projection of the product center-line and the spacecraft X-axis. A positive angle indicates the sensor is looking to the right.


minOffNadirViewAngle

The minimum spacecraft elevation angle measured from nadir to the product center-line as seen from the spacecraft.

Range: 0.0 to 90.0 Precision: One decimal place

maxOffNadirViewAngle

The maximum spacecraft elevation angle measured from nadir to the product center-line as seen from the spacecraft.








meanOffNadirViewAngle

The mean spacecraft elevation angle measured from nadir to the product center-line as seen from the spacecraft.


PNIIRS

Mean predicted image quality on the National Imagery Interpretability Rating Scale (NIIRS), as computed by the General Image Quality Equation (GIQE).

0.0 to 9.0

cloudCover

Estimate of the max cloud-covered fraction of the product component. . For mosaic products, this calculation is based on the intersection of the polygons contained in the MOSAIC_CLOSEDPOLYGONS shapefile with the cloud polygons associated with that part of the relevent input imagery.

0.000 to 1.000 -999.000 -999.000 if not assessed

resamplingKernel

Method used to resample the image. ”NULL”=no resampling kernel “NN”=nearest neighbor “CC”=cubic convolution “MTF”=Modulation Transfer Function “PS”=Pan sharpening “ENH”=Enhanced (Boost) kernel “UserDefined”

“NULL” “NN” “CC” “MTF” “PS” “ENH” “UserDefined”

Only valid when doing radiometric correction.

positionKnowledgeSrc

Source of knowledge of the satellite position. “R” = Refined

“R”

attitudeKnowledgeSrc

Source of knowledge of the satellite attitude. “R” = Refined

“R”

revNumber Orbit revolution number at the time of exposure. Range: 1 to 99999

BEGIN_GROUP=IMAGE_n

BEGIN_GROUP=MAP_PROJECTED_PRODUCT Only for map-projected

(LV2A, LV3 and DEM) and Stereo OR2A products.







earliestAcqTime Acquisition time (UTC) of the first line of the earliest image contained in the product component.


latestAcqTime Acquisition time (UTC) of the first line of the latest image contained in the product component.


For a single image product this value will be the same as earliestAcqTime.

datumName Name of the datum specified for the map projection when the product was ordered.

Value: WGS84: “WE” GRS 80: “GRS80” NAD83: “NAR” NAD27: “NAS” Tokyo-Mean: “TOKYO Mean Solution”

NAD83 uses a GRS 80 ellipsoid. NAD27 uses a Clarke 1866 ellipsoid. Tokyo-Mean uses a Bessel 1841 ellipsoid. Validation should support a 2 to 40 character length.

semiMajorAxis Length of semi-major axis of the datum ellipsoid, in meters.

Value: WGS84/NAD83/GRS80: 6378137.0000 NAD27: 6378206.4000 Tokyo-M: 6377397.1550 Precision: 4 decimal places

inverseFlattening

Inverse flattening of the datum ellipsoid, 1/f. Some useful relationships between flattening (f), semi-major axis (a), semi-minor axis (b), and eccentricity squared (e2) are: f = (a - b) / a e2 = (a2 - b2) / a2 = 2f - f2 b = a (1 - f)

Value: WGS84: 298.257223563 NAD83: 298.257222101 NAD27: 294.978698200 Tokyo-M: 299.152812800 Precision: 9 decimal places







datumOffset X, Y, Z offset of the center of the reference ellipsoid relative to the origin of the WGS 84 system.

Values: For WGS84 & NAD83: ( 0.000, 0.000, 0.000 ); For NAD27: ( -8.000, 160.000, 176.000 ); For Tokyo-Mean: ( -128.000, 481.000 664.000 ) Precision: 3 decimal places

mapProjName Name of the map projection specified when the product was ordered.

“UTM” “State Plane Coordinates” “Japan RCS Zone xx” “Geographic (Lat/Long)”

For Japan RCS Zone, valid zone number range from 1 to 19.

mapProjCode Integer code for the map projection that was used.

Values: UTM: 1 State Plane Coordinates: 2 Geographic (Lat/Long): 17

mapZone Zone used for the map projection. Values: UTM: 1 to 60 State Plane: 0101 – 5105

Only for UTM and State Plane projections. State Plane must have all four digits present. For validation purposes, this should be evaluated as a whole number from 1-4 digits.

mapHemi Code indicating the hemisphere used for the map projection.

“N” “S” Only for UTM projection

mapProjParam

A list of 15 parameters that describe the particular map projection. The meaning of each parameter depends on the map projection selected in mapProjCode.








productUnits Units of projected product

Precision: “DD” = Decimal Degrees “M” = Meters “F” = Feet “USF” = US Survey Feet

originX Easting of the center of the upper left pixel of the image. Precision: 8 decimal places

This is equal to ULX unless an origin is specified by the customer.

originY Northing of the center of the upper left pixel of the image. Precision: 8 decimal places

This is equal to ULY unless an origin is specified by the customer.

orientationAngle

Azimuth angle measured clockwise from map north to the “up” direction at the center of the image. This is a rotation between raster image and the map coordinate systems. Since map-projected products are always Map-North up, this is always zero.

0.0

colSpacing GSD of the image in the column direction.

Values: colSpacing: 2 decimal places for non-geographic projected products colSpacing: scientific notation for geographic projected products

Not applicable to DEMs.

rowSpacing GSD of the image in the row direction.

Values: rowSpacing: 2 decimal places for non-geographic projected products rowSpacing: scientific notation for geographic projected products

Not applicable to DEMs.







productGSD GSD of the product. Range: .1-100.00 Precision: 2 decimal places

Standard (level 2A) and higher products only. The GSD of a MultiSpectral image needs to equal 4x the GSD of the PAN image. For example, if the productGSD of a PAN image is 0.50, then the productGSD of the MultiSpectral image will be 2.00. For validation, this shall range from 0.10 to 99.9.

edgeMatch Indication of the use of edge matching for ortho-mosaic products. In other words, bundle-adjusted.

“On” “Off”

Orthorectified (level 3) products only.

colorBalance Indication of the use of color balance for ortho-mosaic products.

“On” “Off”

Orthorectified (level 3) products only.

postSpacing Post spacing on the DEM, in m. Precision: 2 decimal places Only applicable to DEMs.

ULX Easting of the upper left pixel of the image in the specified datum and map projection. Includes blackfill.

Precision: 8 decimal places This value will be equal to originX.

ULY Northing of the upper left pixel of the image in the specified datum and map projection. Includes blackfill.

Precision: 8 decimal places This value will be equal to originY.

ULH

Height above the ellipsoid of the upper left pixel of the image in the specified datum and map projection. Includes blackfill.


URX Easting of the upper right pixel of the image in the specified datum and map projection. Includes blackfill.


URY Northing of the upper right pixel of the image in the specified datum and map projection. Includes blackfill.








URH

Height above the ellipsoid of the upper right pixel of the image in the specified datum and map projection. Includes blackfill.


LRX Easting of the lower right pixel of the image in the specified datum and map projection. Includes blackfill.


LRY Northing of the lower right pixel of the image in the specified datum and map projection. Includes blackfill.


LRH

Height above the ellipsoid of the lower right pixel of the image in the specified datum and map projection. Includes blackfill.


LLX Easting of the lower left pixel of the image in the specified datum and map projection. Includes blackfill.


LLY Northing of the lower left pixel of the image in the specified datum and map projection. Includes blackfill.


LLH

Height above the ellipsoid of the lower left pixel of the image in the specified datum and map projection. Includes blackfill.


horizontalAccuracy Accuracy in location position on finished DEM product. (1.6 sigma, 90% circular error)

0.0 to 200.0 DEM Products only.

verticalAccuracy Accuracy of elevation determination on finished DEM product. (1.6 sigma, 90% linear error)

0.0 to 200.0 DEM Products only.







DEMCorrection Level of the DEM used for the terrain correction.

“none” “Base Elevation” “Coarse DEM” “Fine DEM” “Customer Supplied DEM” “DTED1” “DTED2” “DTED3” “DTED4” “DTED5” “DTED6”

Not applicable to DEMs. Stereo OR2A and Standard OR2A Products use only “Base Elevation”. Standard (level 2A) and Orthorectified (level 3) Products use anything except “none”. All other products use “none”.

terrainHAE The constant value of the height above the ellipsoid that was used for the terrain correction, in meters.

Range: -50000 to 50000 Only when DEMCorrection = “Base Elevation”.

numGCP Number of ground control points used to create this product. Range: ≥ 0

END_GROUP=MAP_PROJECTED_PRODUCT

END;

6.1.1 Heights Above Ellipsoid (HAE)

The heights above the ellipsoid listed in the band section of the Image Metadata Data (IMD) may vary from the heights above the ellipsoid listed in the map projection section depending on the datum and the DEM correction used. For example: • Case 1: DEM = Base Elevation; and datum = WGS-84

In this case the band and the map heights will all be the same, equivalent to the value of terrainHAE.

• Case 2: DEM = Base Elevation; but datum ≠ WGS-84 (that is, Tokyo Mean) In this case the map heights will all be the same, and equivalent to the value listed in terrainHAE. However, the heights listed in the band section may not equal this value (although they may appear to be equal, but differ in decimal places not shown due to the decimal precision). This difference is due to a conversion using the WGS84 ellipsoid, which changes the height values slightly.

• Case 3: DEM = Coarse/Fine DEM; and datum = WGS-84 In this case, the heights listed in the map section will vary, as will the heights in the band section. However, the corresponding heights will be equal. For example, ULHAE will be the same as ULH.

• Case 4: DEM = Coarse/Fine DEM; but datum ≠ WGS-84 (that is, Tokyo Mean) All heights listed are likely to vary for the same reason listed in Case 2.


6.1.2 Product Level to Product Type Relationships

Table 6.2 Product Level to Product Type Relationships

PRODUCT LEVEL PRODUCT TYPE MAP ACCURACY

LV1B Basic N/A

LV2A Standard N/A

LV3A Orthorectified 1:50,000

LV3D Orthorectified 1:12,000

LV3E Orthorectified 1:10,000

LV3F Orthorectified 1:5,000

LV3G Orthorectified 1:4,800

LV3X Orthorectified Custom

Stereo 1B Basic Stereo pair N/A

Stereo OR2A Ortho-ready Standard N/A

LV4 Various: DEM or Value-Added Various

6.2 Product Browse File The product browse file is a compressed JPEG file of the delivered product. The product browse file will be consistent with the bands ordered for the final product, except for multispectral and 4-band pan-sharpened products for which natural color browse imagery will be supplied. Figure 6.1 is sample of a natural color-product browse file.

Figure 6.1 Sample Product Browse File


6.3 Tile Map Large images are tiled into sub-images and distributed as a group of sub-image files, called tiles. Tiles are not uniform in size. If the image does not fill the whole tile, blackfill will be added to the top and left of the imagery, but removed from the bottom and right of the imagery in order to maintain a uniform upper left pixel and reduce tile sizes. Blackfill will only be present in the upper left corner of a product if a tiling origin is specified that does not correspond to the upper left corner of the Minimum Bounding Rectangle of the order polygon. If no tiling origin is specified, the upper left corner of the order poly will be the tiling origin by default. This section describes the PVL-format tile map file and part of the XML file. It provides the row and column offset for the upper left corner of each tile, relative to the upper left corner of the base image product. For map-projected image products (Standard and Orthorectified), it also provides the latitude and longitude of the upper left pixel in the tile. Table 6.3 defines the Tile Map contents.

Table 6.3 Tile Map Contents


FORMAT RANGE / VALUE [DG RANGE / VALUE, IF



bandId

Identifies the spectral band. “P” = Panchromatic, “Multi” = all Multi-spectral bands (4 for QB02, GE01 and 8 for WV02, WV03) “N” = Near–InfraRed “R” = Red, “G” = Green “B” = Blue "RGB" = Red + Green + Blue “NRG” = Near-IR + Red + Green “BGRN” = Blue + Green + Red + Near-IR RGB, NRG, and BGRN are pan-sharpened color images, stored at the panchromatic spatial resolution. For WorldView-2 and WorldView-3 there are also the following bands: “N2”=NIR2 “RE”=Red Edge “Y”=Yellow “C”=Coastal “MS1”=First 4 bands (N,R,G,B) “MS2”=Second 4 bands (N2,RE,Y,C) For a DEM, this field indicates the spectral band used to create the product.

“P” “Multi” “N” “R” “G” “B” “RGB” “NRG” “BGRN” “N2“ “RE“ “Y“ “C“ “MS1“ “MS2“

N2, RE, Y and C in any band combination are available for WorldView-2 and WorldView-3 only. For validation, this field is constrained by the following definition: A-Za-z0-9 (alphanumeric) plus '-' for up to 7 (1 to 7) characters

numTiles The number of tiles for this product. Range: ≥ 1

tileSizeX Size of the X component (columns) of each tile. Range: ≥ 1






tileSizeY Size of the Y component (lines) of each tile. Range: ≥ 1

tileUnits Units of tiles

“Pixels” “Meters” “Feet” “Degrees”

Degrees only applicable for DOQQ products.

tileOverlap Overlap of tiles. Range: ≥ 0

The following group is repeated for n = 1,…,numTiles. That is, once for each of the tiles.

BEGIN_GROUP=TILE_n

filename Filename of the tile. Example: “10JUL04165542-P2AS-052380211010_01_P001.NTF”

ULColOffset

Column offset of the upper left pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: (columnNum-1)*tileSizeX The columnNum can be found in the filename. For example, “2” in R1C2.]

Range: 0 to ((maxCol-1)*tileSizeX)

ULRowOffset

Row offset of the upper left pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: (rowNum-1) * tileSizeY The rowNum can be found in the filename. For example, “1” in R1C2.]

Range: 0 to ((maxRows-1)*tileSizeY)

URColOffset

Column offset of the upper right pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: MIN((columnNum*tileSizeX), maximumProductTtileSizeX)-1 The columnNum can be found in the filename. For example, “2” in R1C2.]

Range: – (tileSizeX-1) to (maximumProductTileSizeX-1)

URRowOffset Row offset of the upper right pixel of this tile, relative to the upper left pixel of the base image.

Range: 0 to ((maxRows-1)*tileSizeY)






[This field is calculated as: (rowNum-1)*tileSizeY The rowNum can be found in the filename. For example, “1” in R1C2.]

LRColOffset

Column offset of the lower right pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: MIN((columnNum*tileSizeX), maximumProductTtileSizeX)-1 The columnNum can be found in the filename. For example, “2” in R1C2.]

Range: – (tileSizeX-1) to (maximumProductTileSizeX-1)

LRRowOffset

Row offset of the lower right pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: MIN((rowNum*tileSizeY), maximumProductTtileSizeY)-1 The rowNum can be found in the filename. For example, “1” in R1C2.]

Range: – (tileSizeY-1) to (maximumProductTileSizeY-1)

LLColOffset

Column offset of the lower left pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: (columnNum -1)*tileSizeX The columnNum can be found in the filename. For example, “2” in R1C2.]

Range: 0 to ((maxCol-1)*tileSizeX)

LLRowOffset

Row offset of the lower left pixel of this tile, relative to the upper left pixel of the base image. [This field is calculated as: MIN(rowNum*tileSizeY), maximumProductTtileSizeY)-1 The rowNum can be found in the filename. For example, “1” in R1C2.]

Range: – (tileSizeY-1) to (maximumProductTileSizeY-1)

ULLon The geodetic longitude of the center of the upper left pixel in the tile.


ULLat The geodetic latitude of the center of the upper left pixel in the tile.







URLon The geodetic longitude of the center of the upper right pixel in the tile.


URLat The geodetic latitude of the center of the upper right pixel in the tile.


LRLon The geodetic longitude of the center of the lower right pixel in the tile.


LRLat The geodetic latitude of the center of the lower right pixel in the tile.


LLLon The geodetic longitude of the center of the lower left pixel in the tile.


LLLat The geodetic latitude of the center of the lower left pixel in the tile, in degrees.


ULX

Easting of the center of the upper left pixel of the tile in the specified map projection, datum, and units of the product.

Value: Precision: 8 decimal places

ULY

Northing of the center of the upper left pixel of the tile in the specified map projection, datum, and units of the product.


URX

Easting of the center of the upper right pixel of the tile in the specified map projection, datum, and units of the product.


URY

Northing of the center of the upper right pixel of the tile in the specified map projection, datum, and units of the product.


LRX

Easting of the center of the lower right pixel of the tile in the specified map projection, datum, and units of the product.


LRY Northing of the center of the lower right pixel of the tile in the specified map Precision: 8 decimal places






projection, datum, and units of the product.

LLX

Easting of the center of the lower left pixel of the tile in the specified map projection, datum, and units of the product.


LLY

Northing of the center of the lower left pixel of the tile in the specified map projection, datum, and units of the product.


END_GROUP=TILE_n

END;

6.4 Rational Polynomial Coefficients This section describes the content of the PVL-format RPC00B file and the corresponding part of the XML file. It contains the coefficients for Rapid Positioning Capability, also called Rational Polynomial Coefficients (RPC). This is a mathematical mapping from object space coordinates to image space coordinates. This mapping includes non-ideal imaging effects, such as lens distortion, light aberration, and atmospheric refraction.

RPC00Bs express the normalized column and row values in an image, (cn, rn), as a ratio of polynomials of the normalized geodetic latitude, longitude, and height, (P, L, H). Normalized values are used instead of actual values in order to minimize numerical errors in the calculation. The scales and offset of each parameter are selected so that all normalized values fall in the range [-1, 1]. The normalization used is as follows: • P = (Latitude - LAT_OFF) / LAT_SCALE • L = (Longitude - LONG_OFF) / LONG_SCALE • H = (Height - HEIGHT_OFF) / HEIGHT_SCALE • rn = (ROW - LINE_OFF) / LINE_SCALE • cn = (Column - SAMP_OFF) / SAMP_SCALE

Each polynomial is up to third order in (P, L, H), having as many as 20 terms. The rational functions are:

LINE_NUM_COEF, LINE_DEN_COEF, SAMP_NUM_COEF, and SAMP_DEN_COEF are 20-term vectors of coefficients that are given in the RPC00B file. p(P,L,H) is a 20-term vector with the following terms:

∑

∑

∑

∑

=

=

=

=

•

•

=

•

•

=20

1

20

120

1

20

1

),,(__

),,(__

),,(__

),,(__

iii

iii

n

iii

iii

n

HLPpCOEFDENSAMP

HLPpCOEFNUMSAMPcand

HLPpCOEFDENLINE

HLPpCOEFNUMLINEr


Table 6.4 RPC Terms

I pi (P,L,H) I pi (P,L,H)

1 1 11 PLH

2 L 12 L3

3 P 13 LP2

4 H 14 LH2

5 LP 15 L2P

6 LH 16 P3

7 PH 17 PH2

8 L2 18 L2H

9 P2 19 P2H

10 H2 20 H3

For example, for a generic set of polynomial coefficients Ci, the corresponding 20-term cubic polynomial has the form:

f(P, L, H) = C1 + C2 L + C3 P + C4 H + C5 LP + C6 LH + C7 PH + C8 L2 + C9 P

2 + C10 H2 + C11 PLH + C12 L

3 + C13 LP2 + C14 LH2 + C15 L2P +

C16P3 + C17PH2 + C18L2H + C19P2H + C20H3

The image coordinates are expressed in pixels. The ground coordinates are latitude and longitude in decimal degrees, and geodetic elevations (height above the ellipsoid) in meters.

There is only one set of coefficients for Basic, Stereo, and Standard products since their multi-spectral bands are co-registered and the images are geometrically continuous within each band. The range of values for each numeric parameter is as specified in The Compendium of Controlled Extensions (CE) for the National Imagery Transmission Format (NITF); NIMA document STDI-0002, Version 2.1, 16 November 2000. Out-of-range coefficients are set to zero. Table 6.5 defines the RPC00B contents.

Table 6.5 RPC00B Contents





satId Satellite Id. “QB02”, “WV01”, “WV02”, “GE01”, “WV03”

bandId Identifies the spectral band. “P” = Panchromatic,

“P” “Multi” “N”

N2, RE, Y and C in any band combination are available for






“Multi” = all Multi-spectral bands (4 for QB02, GE01 and 8 for WV02, WV03), “N” = Near–InfraRed, “R” = Red, “G” = Green, “B” = Blue, "RGB" = Red + Green + Blue, "NRG" = Near-IR + Red + Green, “BGRN” = Blue + Green + Red + Near-IR. RGB, NRG, and BGRN are pan-sharpened color images, stored at the panchromatic spatial resolution. For WorldView-2 and WorldView-3 there are also the following bands, “N2”=NIR2, “RE”=Red Edge, “Y”=Yellow, “C”=Coastal “MS1” “MS2” For a DEM, this field indicates the spectral band used to create the product.

“R” “G” “B” “RGB” “NRG” “BGRN” “N2” “RE” “Y” “C” “MS1” “MS2”

WorldView-2 and WorldView-3 only.

SpecId

Identification of the specification which defines the RPC implementation used for generating and/or interpreting the coefficients

“RPC00B”

BEGIN_GROUP = IMAGE

Standard (level 2A) and Orthorectified (level 3) products only.

errBias Bias error. 68% non time-varying error estimate for correlated images.


errRand Random error. 68% time-varying error estimate for correlated images.


lineOffset LINE_OFFSET. Range: 0 – 999999

sampOffset SAMP_OFFSET. Range: -9999 to 99999






latOffset LAT_OFFSET. Range: ± 90.0000 Precision: 4 decimal places

longOffset LONG_OFFSET. Range: ± 180.0000 Precision: 4 decimal places

heightOffset HEIGHT_OFFSET. Range: ± 9999

lineScale LINE_SCALE Range: 1 – 999999

sampScale SAMP_SCALE Range: 1 – 99999

latScale LAT_SCALE Range: ± 90.0000 Precision: 4 decimal places

longScale LONG_SCALE Range: ± 180.0000 Precision: 4 decimal places

heightScale HEIGHT_SCALE Range: ± 9999

lineNumCoef LINE_NUM_COEF. Twenty coefficients for the polynomial in the numerator of the rn equation.

Range: ± 9.999999 * 10± 9

lineDenCoef LINE_DEN_COEF. Twenty coefficients for the polynomial in the denominator of the rn equation.

Range: ± 9.999999 * 10± 9

sampNumCoef SAMP_NUM_COEF. Twenty coefficients for the polynomial in the numerator of the cn equation.

Range: ± 9.999999 * 10± 9

sampDenCoef SAMP_DEN_COEF. Twenty coefficients for the polynomial in the denominator of the cn equation.

Range: ± 9.999999 * 10± 9

END;

6.5 Product Component XML File The XML file contains the same information as the combined product component level README, Licensing, Image Metadata, Tile Map, and RPC00B files, except in XML format. For Basic Imagery Products, the attitude, ephemeris, and geometric calibration file are included as well. One Product Component XML file is provided for each product component of each delivery within the product component subdirectory.

Listed below is an example of this file for a Bundle Standard Imagery Product.


<?xml version="1.0" encoding="UTF-8" ?> - <README> <VERSION>AA</VERSION> <COPYRIGHT>Use, duplication or disclosure by the government is subject to the restrictions as set forth in subparagraph (c)(1)(ii) of the Rights in Technical Data and Computer Software Clause contained in D.F.A.R.S. 252.227-7013, and subparagraphs (c)(1) and (2) of the Commercial Computer Software-Restricted Rights contained in 48 C.F.R. 52.227-19. Contractor/manufacturer is DigitalGlobe, Incorporated at 1601 Dry Creek Drive, Suite 260, Longmont, CO 80503-6493. Copyright YYYY DigitalGlobe Incorporated, Longmont CO USA 80503-6493 DigitalGlobe and the DigitalGlobe logo are trademarks of DigitalGlobe, Incorporated. The use and/or dissemination of this data and/or of any product in any way derived there from are restricted. Unauthorized use and/or dissemination is prohibited. DigitalGlobe WWW Reference: http://www.digitalglobe.com</COPYRIGHT> <MEDIACREATIONDATE>2006-01-18T23:03:43.492Z</MEDIACREATIONDATE> <ORDERNO>005366076010_01</ORDERNO> - <FILELIST> <FILE>005366076010_01_README.TXT</FILE> <FILE>005366076010_01_README.XML</FILE> <FILE>005366076010_01_LAYOUT.JPG</FILE> <FILE>GIS_FILES/005366076010_01_ORDER_SHAPE.shx</FILE> <FILE>GIS_FILES/005366076010_01_ORDER_SHAPE.shp</FILE> <FILE>GIS_FILES/005366076010_01_ORDER_SHAPE.dbf</FILE> <FILE>GIS_FILES/005366076010_01_PRODUCT_SHAPE.shx</FILE> <FILE>GIS_FILES/005366076010_01_PRODUCT_SHAPE.shp</FILE> <FILE>GIS_FILES/005366076010_01_PRODUCT_SHAPE.dbf</FILE> <FILE>GIS_FILES/005366076010_01_STRIP_SHAPE.shx</FILE> <FILE>GIS_FILES/005366076010_01_STRIP_SHAPE.shp</FILE> <FILE>GIS_FILES/005366076010_01_STRIP_SHAPE.dbf</FILE> <FILE>GIS_FILES/005366076010_01_TILE_SHAPE.shx</FILE> <FILE>GIS_FILES/005366076010_01_TILE_SHAPE.shp</FILE> <FILE>GIS_FILES/005366076010_01_TILE_SHAPE.dbf</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001_README.TXT</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.IMD</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.EPH</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.ATT</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.TIL</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.GEO</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.RPB</FILE> <FILE>005366076010_01_P001_MUL/CIVIL_ORG_EULA_SERVICES.TXT</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.XML</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001-BROWSE.JPG</FILE> <FILE>005366076010_01_P001_MUL/02DEC15023811-M1BS-005366076010_01_P001.TIF</FILE> <FILE>005366076010_01_P001_PAN/CIVIL_ORG_EULA_SERVICES.TXT</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001_README.TXT</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.IMD</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.EPH</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.ATT</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.TIL</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.GEO</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.RPB</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.XML</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001-BROWSE.JPG</FILE> <FILE>005366076010_01_P001_PAN/02DEC15023811-P1BS-005366076010_01_P001.TIF</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002_README.TXT</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.IMD</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.EPH</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.ATT</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.TIL</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.GEO</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.RPB</FILE> <FILE>005366076010_01_P002_MUL/CIVIL_ORG_EULA_SERVICES.TXT</FILE>


<FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.XML</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002-BROWSE.JPG</FILE> <FILE>005366076010_01_P002_MUL/03AUG09021839-M1BS-005366076010_01_P002.TIF</FILE> <FILE>005366076010_01_P002_PAN/CIVIL_ORG_EULA_SERVICES.TXT</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002_README.TXT</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.IMD</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.EPH</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.ATT</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.TIL</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.GEO</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.RPB</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.XML</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002-BROWSE.JPG</FILE> <FILE>005366076010_01_P002_PAN/03AUG09021839-P1BS-005366076010_01_P002.TIF</FILE> </FILELIST> <AREADESCRIPTION>PS_WV_02</AREADESCRIPTION> <DGORDERNO>005366076</DGORDERNO> <DGORDERITEMNO>005366076010</DGORDERITEMNO> <CUSTOMERORDERNO>PS_02 1B+ BA XML Taipei</CUSTOMERORDERNO> <CUSTOMERORDERITEMNO>40009</CUSTOMERORDERITEMNO> <COLLECTIONSTART>2002-12-15T02:38:08.618201Z</COLLECTIONSTAR> <COLLECTIONSTOP>2003-08-09T02:18:48.385340Z</COLLECTIONSTOP> <COUNTRYCODE>TW</COUNTRYCODE> <NUMBEROFLOOKS>1</NUMBEROFLOOKS> <CLOUDCOVER>-999.0</CLOUDCOVER> <NWLAT>25.12000000</NWLAT> <NWLONG>121.60000000</NWLONG> <SELAT>25.04000000</SELAT> <SELONG>121.73000000</SELONG> </README>

6.6 Manifest File The manifest file outlines the directory structure for products delivered by FTP. Below is an example of the manifest file delivered for a Standard Pansharpened Imagery product.

./005510916010_01.MAN

./005510916010_01

./005510916010_01/005510916010_01_README.TXT

./005510916010_01/005510916010_01_README.XML

./005510916010_01/005510916010_01_LAYOUT.JPG

./005510916010_01/GIS_FILES

./005510916010_01/GIS_FILES/005510916010_01_ORDER_SHAPE.shx

./005510916010_01/GIS_FILES/005510916010_01_ORDER_SHAPE.shp

./005510916010_01/GIS_FILES/005510916010_01_ORDER_SHAPE.dbf

./005510916010_01/GIS_FILES/005510916010_01_PRODUCT_SHAPE.shx

./005510916010_01/GIS_FILES/005510916010_01_PRODUCT_SHAPE.shp

./005510916010_01/GIS_FILES/005510916010_01_PRODUCT_SHAPE.dbf

./005510916010_01/GIS_FILES/005510916010_01_STRIP_SHAPE.shx

./005510916010_01/GIS_FILES/005510916010_01_STRIP_SHAPE.shp

./005510916010_01/GIS_FILES/005510916010_01_STRIP_SHAPE.dbf

./005510916010_01/GIS_FILES/005510916010_01_TILE_SHAPE.shx

./005510916010_01/GIS_FILES/005510916010_01_TILE_SHAPE.shp

./005510916010_01/GIS_FILES/005510916010_01_TILE_SHAPE.dbf

./005510916010_01/005510916010_01_P001_PSH

./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001_README.TXT ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001.IMD ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001.TIL ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001.RPB ./005510916010_01/005510916010_01_P001_PSH/COMMERCIAL.TXT ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001.XML


./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS-005510916010_01_P001-BROWSE.JPG ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R1C1-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R1C2-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R1C3-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R2C1-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R2C3-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R3C2-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R4C1-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R4C3-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R4C2-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R3C3-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R3C1-005510916010_01_P001.TIF ./005510916010_01/005510916010_01_P001_PSH/03MAR13174755-S2AS_R2C2-005510916010_01_P001.TIF

6.7 Stereo File This file is provided only for Stereo Pair Imagery products, and describes information about individual stereo models. The stereo file contains three angular measures of convergent stereo imaging geometry: the convergence angle, the asymmetry angle, and the bisector elevation angle (BIE). These measure the geometrical relationship between two rays that intersect at a common ground point, one from the fore image and one from the aft image. These intersecting rays define a plane, called the convergence plane. The convergence angle is the angle between the two rays in the convergence plane. The asymmetry angle is the angle between the ray bisector (also in the convergence plane), and the projection of a vertical from the ground point onto the convergence plane. The BIE is the elevation of the bisector. That is, the angle from the horizontal plane containing the ground point to the bisector. Each angle is computed at a ground target point near the beginning of the stereo overlap, and at another point near the end of the stereo overlap. Table 6.6 defines the Stereo File contents.

Figure 6.2 Stereo Geometry Angles

Stereo geometry is often described in terms of convergence angle and asymmetry angle at a ground point defined by radius vector, as illustrated in Figure 6.2. These angles are measured in the plane formed by the two lines of sight (one for each image) to the ground point.


Table 6.6 Stereo File Contents





numPair Number of stereo pairs in this file. 1

The following group is repeated for n = 1,…,numPair (for all stereo pairs).

BEGIN_GROUP=STEREO_PAIR_n

firstId Image file name of the first image (image acquired at the earlier time) of a stereo pair.

For products produced by DigitalGlobe, this name will follow the standard product naming conventions.

secondId Image file name of the second image of the stereo pair. See firstID.

overlap Fractional overlap: overlap area, measured on the ground, divided by the ground area of the second image.

0.00 to 1.00

ULLat Geodetic latitude of the upper left corner of the minimum-bounding rectangle that covers the stereo model.

Range: ± 90.000000 Precision: Six decimal places

ULLon Geodetic longitude of the upper left corner of the minimum-bounding rectangle that covers the stereo model.


LRLat Geodetic latitude of the lower right corner of the minimum-bounding rectangle that covers the stereo model.


LRLon Geodetic longitude of the lower right corner of the minimum-bounding rectangle that covers the stereo model.


B_Conv Beginning convergence angle. This is measured at the first lines of the stereo overlap.

Range: 0.00 to 180.00 Precision: Two decimal places

E_Conv Ending convergence angle. This is measured at the last lines of the stereo overlap.


B_Asym Beginning asymmetry angle. This is measured at the first lines of the stereo overlap.







E_Asym Ending asymmetry angle. This is measured at the last lines of the stereo overlap.


B_BIE Beginning BIE less convergence angle of stereo mate. This is measured at the first lines of the stereo overlap.

Range: -90.00 to 90.00 Precision: Two decimal places

E_BIE Ending BIE less convergence angle of stereo mate. This is measured at the last lines of the stereo overlap.

Range: -90.00 to 90.00 Precision: Two decimal places

END_GROUP=STEREO_PAIR_n

END;


Appendix A: Example PVL Format

The following is an example PVL format. It is for illustration purposes only. version = "21.0"; /* ISD Version */ generationTime = 2003-12-18T17:54:28.000000Z; productOrderId = "T-111-C"; productCatalogId = “2030011234567801”; imageDescriptor = "Standard2A"; bandId = "P"; panSharpenAlgorithm = "None"; numRows = 22472; numColumns = 14384; productLevel = "LV2A"; productType = “Standard“; numberOfLooks = 1; radiometricLevel = "Corrected"; radiometricEnhancement = "Off"; bitsPerPixel = 8; compressionType = "None"; BEGIN_GROUP = BAND_P ULLon = -158.26477950; ULLat = 21.59936003; ULHAE = 0.00; URLon = -158.13533250; URLat = 21.59936003; URHAE = 0.00; LRLon = -158.13533250; LRLat = 21.39712529; LRHAE = 0.00; LLLon = -158.26477950; LLLat = 21.39712527; LLHAE = 0.00; absCalFactor = 4.734886e-01; effectiveBandwidth = 3.9800e-01; END_GROUP = BAND_P outputFormat = "GeoTIFF"; BEGIN_GROUP = IMAGE_1 satId = "QB02"; mode = “FullSwath“; CatId = "101001000173E700"; minCollectedRowGSD = 0.618; maxCollectedRowGSD = 0.621; meanCollectedRowGSD = 0.619; minCollectedColGSD = 0.629; maxCollectedColGSD = 0.630; meanCollectedColGSD = 0.629; meanCollectedGSD = 0.624; rowUncertainty = 166.70; colUncertainty = 292.81; minSunAz = 155.3; maxSunAz = 156.8; meanSunAz = 155.8; minSunEl = 43.2; maxSunEl = 44.2; meanSunEl = 43.7; minSatAz = 119.7; maxSatAz = 119.9; meanSatAz = 119.8; minSatEl = 80.0; maxSatEl = 82.0; meanSatEl = 81.1; minInTrackViewAngle = -3.4;


maxInTrackViewAngle = -1.4; meanInTrackViewAngle = -2.4; minCrossTrackViewAngle = 8.6; maxCrossTrackViewAngle = 15.6; meanCrossTrackViewAngle = 11.8; minOffNadirViewAngle = 9.2; maxOffNadirViewAngle = 17.2; meanOffNadirViewAngle = 12.2; PNIIRS = 3.8; cloudCover = 0.000; imageQuality = "Fair"; TDILevel = 13; positionKnowledgeSrc = "R"; attitudeKnowledgeSrc = "R"; revNumber = 6279; END_GROUP = IMAGE_1 BEGIN_GROUP = MAP_PROJECTED_PRODUCT earliestAcqTime = 2002-11-30T21:06:27.161677Z; latestAcqTime = 2002-11-30T21:06:27.161677Z; datumName = "INTERNATIONAL 1924"; semiMajorAxis = 6378388.0000; inverseFlattening = 297.000000000; datumOffset = ( 0.000, 0.000, 0.000 ); mapProjName = "Geographic (Lat/Long)"; mapProjCode = 17; mapProjParam = ( 6366197.723675813, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000, 0.000000000 ); productUnits = "DD"; originX = -158.26477950; originY = 21.59992350; orientationAngle = 0.0; colSpacing = 0.00; rowSpacing = 0.00; productGSD = 0.60; edgeMatch = "Off"; colorBalance = "On"; ULX = -158.26477950; ULY = 21.59992350; ULH = 0.00; URX = -158.13533250; URY = 21.59992350; URH = 0.00; LRX = -158.13533250; LRY = 21.39768450; LRH = 0.00; LLX = -158.26477950; LLY = 21.39768450; LLH = 0.00;


DEMCorrection = "none"; numGCP = 4; END_GROUP = MAP_PROJECTED_PRODUCT END; /* END OF MODULE */


Appendix B: Example XML Format

The following is an example XML format. It is for illustration purposes only. <?xml version="1.0" encoding="UTF-8" ?> <version>”21.0”</version> <generationTime>2003-12-18T17:54:28.000000Z</generationTime> <productOrderId>”T-111-C”</productOrderId> <productCatalogId> = “2030011234567801” </productCatalogId> <imageDescriptor>”Standard2A”</imageDescriptor> <bandId>”P”</bandId> <panSharpenAlgorithm>”None”</panSharpenAlgorithm> <numRows>22472 </numRows> <numColumns>14384</numColumns> <productLevel>”LV2A” </productLevel> <productType>”Standard” </productType> <numberOfLooks>1 </numberOfLooks> <radiometricLevel>”Corrected”</radiometricLevel> <radiometricEnhancement>”Off”</radiometricEnhancement> <bitsPerPixel>8</bitsPerPixel> <compressionType>”None”</compressionType> <Band_P> <ULLon>-158.26477950</ULLon> <ULLat> 21.59936003</ULLat> <ULHAE> 0.00</ULHAE> <URLon> -158.13533250</URLon> <URLat> 21.59936003</URLat> <URHAE> 0.00</URHAE> <LRLon> -158.13533250</LRLon> <LRLat> 21.39712529</LRLat> <LRHAE> 0.00</LRHAE> <LLLon> -158.26477950</LLLon> <LLLat> 21.39712527</LLLat> <LLHAE> 0.00</LLHAE> <absCalFactor> 4.734886e-01</absCalFactor> <effectiveBandwidth> 3.9800e-01 <effectiveBandwidth> </Band_P> <outputFormat>”GeoTIFF”</outputFormat> <Image_List> <satId>”QB02”</satId> <mode>”FullSwath”</mode> <catId>”101001000173E700”</catId> <minCollectedRowGSD>0.618</minCollectedRowGSD> <maxCollectedRowGSD>0.621</maxCollectedRowGSD> <meanCollectedRowGSD>0.619</meanCollectedRowGSD> <minCollectedColGSD>0.629</minCollectedColGSD> <maxCollectedColGSD>0.630</maxCollectedColGSD> <meanCollectedColGSD>0.629</meanCollectedColGSD> <meanCollectedGSD>0.624</meanCollectedGSD> <rowUncertainty>166.70</rowUncertainty> <colUncertainty>292.81</colUncertainty> <minSunAz>155.3</minSunAz> <maxSunAz>156.8</maxSunAz> <meanSunAz>155.8</meanSunAz> <minSunEl>43.2</minSunEl> <maxSunEl>44.2</maxSunEl> <meanSunEl>43.7</meanSunEl> <minSatAz>119.7</minSatAz> <maxSatAz>119.9<maxSatAz> <meanSatAz>119.8<meanSatAz> <minSatEl>80.0</minSatEl> <maxSatEl>82.0</maxSatEl>


<meanSatEl>81.1</maxSatEl> <minInTrackViewAngle>-3.4</minInTrackViewAngle> <maxInTrackViewAngle>-1.4</maxInTrackViewAngle> <meanInTrackViewAngle>-2.4</meanInTrackViewAngle> <minCrossTrackViewAngle>8.6</minCrossTrackViewAngle> <maxCrossTrackViewAngle>15.6<maxCrossTrackViewAngle> <meanCrossTrackViewAngle>11.8<meanCrossTrackViewAngle> <minOffNadirViewAngle>9.2</minOffNadirViewAngle> <maxOffNadirViewAngle>17.2</maxOffNadirViewAngle> <meanOffNadirViewAngle>12.2<meanOffNadirViewAngle> <PNIIRS>3.8</PNIIRS> <cloudCover>0.000</cloudCover> <imageQuality>”Fair”</imageQuality> <TDILevel>13</TDILevel> <positionKnowledgeSrc>R</positionKnowledgeSrc> <attitudeKnowledgeSrc>R</attitudeKnowledgeSrc> <revNumber>6279</revNumber> </Image_List> <mapProjected> <earliestAcqTime>2002-11-30T21:06:27.161677Z</earliestAcqTime> <latestAcqTime>2002-11-30T21:06:27.161677Z</latestAcqTime> <datumName>“INTERNATIONAL 1924“</datumName> <semiMajorAxis>6378388.0000</semiMajorAxis> <inverseFlattening>297.000000000</inverseFlattening> <datumOffset> <offset>0.000</offset> <offset>0.000</offset> <offset>0.000</offset> </datumOffset> <mapProjName>"Geographic (Lat/Long)" </mapProjName> <mapProjCode>17</mapProjCode> <mapProjParam> <param> 6366197.723675813</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> <param> 0.000000000</param> </mapProjParam> <productUnits>"DD"</productUnits> <originX>-158.26477950</originX> <originY>21.59992350</originY> <orientationAngle>0.0</orientationAngle> <colSpacing>0.00</colSpacing> <rowSpacing>0.00</rowSpacing> <productGSD>0.60</productGSD> <edgeMatch>"Off"</edgeMatch> <colorBalance>"On"</colorBalance> <ULX> -158.26477950</ULX> <ULY> 21.59992350</ULY> <ULH> 0.00</ULH> <URX> -158.13533250</URX> <URY> 21.59992350</URY> <URH> 0.00</URH> <LRX>-158.13533250</LRX> <LRY>21.39768450</LRY>


Appendix C: Example Tile Map File

The following is an example tile map format. It is for illustration purposes only. bandId = "RGB"; numTiles = 12; tileSizeX = 8192; tileSizeY = 8192; tileUnits = "Pixels"; tileOverlap = 0; BEGIN_GROUP = TILE_1 filename = "02DEC15023809-S2AS_R1C1-005500420010_01_P001.NTF"; ULColOffset = 0; ULRowOffset = 0; URColOffset = 8191; URRowOffset = 0; LRColOffset = 8191; LRRowOffset = 8191; LLColOffset = 0; LLRowOffset = 8191; ULLon = 121.50000270; ULLat = 25.24998690; URLon = 121.54423410; URLat = 25.24998690; LRLon = 121.54423410; LRLat = 25.20575550; LLLon = 121.50000270; LLLat = 25.20575550; ULX = 121.50000270; ULY = 25.24998690; URX = 121.54423410; URY = 25.24998690; LRX = 121.54423410; LRY = 25.20575550; LLX = 121.50000270; LLY = 25.20575550;


Glossary

AOI

Area of Interest. The area on the Earth that you want to view.

Bilinear Interpolation

Bilinear interpolation uses the value of the four nearest cell centers to determine the value on the output raster. The new value is a weighted average of these four values, adjusted to account for their distance from the center of the output cell. The result is a smoother-looking surface than provided by “nearest neighbor”.

Bicubic Interpolation

Bicubic interpolation combines data points on a two-dimensional grid. This method outputs the smoothest surface of all interpolation methods.

CE

Circular Error.

CE90

Circular Error at 90% confidence. Indicates that the actual location of an object is represented on the image within the stated accuracy for 90% of the points.

CIR

Color Infrared.

COTS

Commercial-Off-The-Shelf.

DEM

See Digital Elevation Model.

Digital Elevation Model (DEM)

A digital model of terrain relief, usually derived from stereo imagery. A DEM is used to remove terrain distortions from Orthorectified Imagery products.

DRA

Dynamic Range Adjustment. An optional post-processing feature that enhances the visual interpretability of the image.

DTED

Digital Terrain Elevation Data.

ECF

Earth Centered Fixed.

FTP

File Transfer Protocol.

GCP

See Ground Control Point.


GE01

GeoEye-1 Satellite.

Geographic Projection

Maps longitudes as straight vertical lines and latitudes as straight horizontal lines all spaced out consistently for constant intervals.

GeoTIFF format

Georeferenced tagged image file format. A GeoTIFF file is a TIFF file that is embedded with geographic data tags.

Ground Control Point (GCP)

A known geographic coordinate location on the ground. A GCP can be collected from ground survey or maps (Primary GCP), or derived via triangulation of primary GCPs (Secondary GCP). GCPs can be planimetric (x, y; latitude, longitude) or vertical (x, y, z; latitude, longitude, elevation).

Ground Sample Distance (GSD)

The size of a single pixel as measured on the ground. This is also referred to as “resolution”.

GSD

See Ground Sample Distance.

Image Support Data (ISD)

A set of files which contain all the necessary data necessary to use and process Imagery Products. These files can be viewed as a collection point for all ancillary data that is expected to be useful to a customer.

ISD

See Image Support Data.

JPEG2000 format

The JPEG2000 format is a JPEG format that was introduced in the year 2000. It has considerable advantages over basic JPEG format including error resilience and progressive transmission.

LE

Linear Error.

LE90

Linear Error at 90 percent confidence. Indicates that the actual elevation of an object is represented within the stated accuracy for at least 90% of elevation posts.

MBR

Minimum-bounding rectangle.

Metadata

Ancillary data that describes and defines the imagery product. DigitalGlobe provides metadata in a set of Image Support Data files.

Mosaic

The process of digitally assembling images to create contiguous large-area coverage.


MrSid format

Multi-Resolution Seamless Image Database. This format compresses large raster images while maintaining the image quality.

MS

See Multispectral.

Multispectral

Imagery with data recorded in multiple discrete spectral bands. Imagery collected in four or eight ranges of wavelengths in the electromagnetic spectrum.

Nadir

The point on the ground vertically beneath the sensor.

National Imagery Transmission Format

See NITF format.

Nearest Neighbor Interpolation

Uses the value of the closest point and disregards all other values, yielding a piecewise-constant interpolant.

NED

National Elevation Dataset DEM. NED DEM is available in the United States. Accuracy in Alaska is not as high as in the contiguous United States.

NIIRS

National Image Interpretability Rating Scale.

NIR1

Near Infrared 1.

NIR2

Near Infrared 2.

NITF format

National Imagery Transmission Format. A United States Department of Defense standard for transmitting and storing digital imagery.

NRG

Near-Infrared, Red, Green.

Off-nadir Angle

The angle between nadir and the point on the ground that the sensor is pointing. Off-nadir angle can be measured in the along-track (forward) direction or across-track (sideways) direction.

Orthorectification

The process of removing image distortions introduced by the collection geometry and variable terrain, and re-sampling the imagery to a specified map projection. Also referred to as ortho-correction or terrain correction.


Pan/Panchromatic

A wide spectral band which is comprised of reflected light in the visible spectrum (blue, green, red and NIR). It is displayed as a black and white image.

Pan-Sharpened

Processed used to colorize imagery by fusing multispectral and panchromatic bands.

Photogrammetry

The art, science, and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring, and interpreting photographic images and patterns of electromagnetic radiant imagery.

Pixel

Picture element. The smallest element comprising a digital image.

PNIIRS

Predicted National Image Interpretability Rating Scale.

Product Framing

The manner in which Imagery Products are delivered. Products are either Scene-based or Area-based.

PVL

Physical Volume Library.

QB02

QuickBird satellite.

Radiometric Correction

The correction of variations in data that are not caused by the object or scene being scanned, such as non-responsive detectors, scanner inconsistencies, and atmospheric interference.

Remote Sensing

The measurement or acquisition of data about an object by an instrument not in contact with the object. Satellite imagery, aerial photography, and radar are all types of remote sensing.

Resolution

The resampled image pixel size derived from GSD.

RGB

Red, Green, Blue.

RMSE

Root Mean Square Error.

RPC

Rational Polynomial Coefficient camera model. RPCs provide the camera geometry obtained at the time of the image collection.


Scale

The ratio of distance on a map as related to the true distance on the ground. Products with a larger scale have higher geometric accuracies than products with a smaller scale.

Seamlines

Seamlines are the lines at which two separate images overlap. These overlapping images can be blended along the seamline to show a more uniform image.

Sensor Azimuth

The azimuth of the sensor measured from the target.

Sensor Correction

The correction of variations in data that are caused by variations in sensor geometry, attitude, and ephemeris.

Spatial Mosaic

The assembly of multiple scenes, each of which shows a portion of the order polygon, into a single image. Usually involves edge matching adjacent scenes.

SRTM

Shuttle Radar Topography Mission digital elevation models.

Stereo

The collection of two or more images of the same Area of Interest (AOI) from different viewing angles.

Sun Azimuth

The azimuth of the sun as seen by an observer sitting on the target measured in a clockwise direction from north.

Sun Elevation

The angle of the sun above the horizon.

Sun-Synchronous

An orbit which rotates around the Earth at the same rate as the Earth rotates on its axis.

Swath Width

The width of an image.

Target Azimuth

The azimuth of the target as seen by an observer sitting on the spacecraft measured in a clockwise direction from north.

TDI

Time Delay Integration.

Terrain Correction

The correction for variations in data caused by terrain displacement due to off-nadir viewing.

TLC

Time-lagged Line Count.

Universal Transverse Mercator Geographic Coordinate System (UTM)

See UTM.


UTM

Universal Transverse Mercator Geographic Coordinate System. UTM utilizes a two-dimensional Cartesian system to specify locations on the Earth’s surface.

WV01

WorldView-1 satellite.

WV02


WV03



Index absAcc, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 absAccUnit, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 absCalFactor, in image metadata, 28 acqDate, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 acquisitio, in STRIP shapefile, 17 area of interest, defined, 61 areaDesc, in delivery index, 14 attFilename, in product component index, 21 attitude file

described, 8 overview, 7

attitudeKnowledgeSrc, in image metadata, 34 avgLineRate, in image metadata, 29 B_Asym, in stereo file, 53 B_BIE, in stereo file, 53 B_Conv, in stereo file, 53 bandId

in image metadata, 25 in RPC00B file, 47 in tile map file, 41

bandInfo, in PRODUCT shapefile, 18 bicubic interpolation, defined, 61 bilinear interpolation, defined, 61 bitsPerPixel, in image metadata, 26 CatId, in image metadata, 29 CE, defined, 61 CE90, defined, 61 childCatalogID, in image metadata, 23 CIR, defined, 61 cloudCover

in delivery index, 15 in image metadata, 33 in MOSAIC_CLOSEDPOLYGONS shapefile, 19

collDate, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 collectAz, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 collectEl, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 collectionStart, in delivery index, 14 collectionStop, in delivery index, 14 colorBalance, in image metadata, 37 colSpacing, in image metadata, 37 colUncertainty, in image metadata, 30 compressionType, in image metadata, 26 conventions

file naming, 9 file naming, PVL format, 10

for coordinates, 10 coordinate conventions, 10 copyrightText

in delivery index, 13 in product component index, 21

COTS, defined, 61 countryCode, in delivery index, 14 createDate, in ORDER shapefile, 17 currDate, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 custOrd, in ORDER shapefile, 17 custOrderItemNo, in delivery index, 14 custOrderNo, in delivery index, 14 custOrdItm, in ORDER shapefile, 17 datum, in ORDER shapefile, 17 datumName, in image metadata, 34 datumOffset, in image metadata, 35 delivery index, naming convention, 13 delivery layout file, contents, 16 delivery-level ISD, 7 DEM, defined, 61 DEMCorrection, in image metadata, 39 dgOrderItemNo, in delivery index, 14 dgOrderNo, in delivery index, 14 digital elevation model, defined, 61 DRA, defined, 61 DTED, defined, 61 E_Asym, in stereo file, 53 E_BIE, in stereo file, 53 E_Conv, in stereo file, 53 earliestAcqTime, in image metadata, 34 Earth coordinate system

described, 10 illustrated, 11

ECF, defined, 61 edgeMatch, in image metadata, 37 effectiveBandwidth, in image metadata, 28 end of transfer file


ephemeris file described, 8 overview, 7

ephemFilename, in product component index, 21 errBias, in RPC00B file, 48 errRand, in RPC00B file, 48


exposureDuration, in image metadata, 29 file format, general, 10 file layout, described, 8 file naming convention, 9 fileList, in delivery index, 14 filename, in tile map file, 42 fileName, in TILE shapefile, 18 firstId, in stereo file, 52 firstLineTime, in image metadata, 29 FTP, defined, 61 GCP, defined, 61 GE01, defined, 62 generationTime, in image metadata, 23 geoCalFilename, in product component index, 22 geographic location map files

described, 8 included in delivery, 16 overview, 7, 16

geographic projection, defined, 62 geometric calibration file


GeoTIFF, defined, 62 Ground Control Point, defined, 6 Ground Sample Distance, defined, 62 GSD, defined, 62 gsd, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 HAE, defined, 39 heightOffset, in RPC00B file, 48 heights above ellipsoide. See HAE heightScale, in RPC00B file, 48 horError, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 horizontalAccuracy, in image metadata, 39 image coordinate system

described, 11 illustrated, 11

image metadata file contents, 23 described, 8 naming conventions, 23 overview, 7

image support data. See ISD imageDescriptor, in image metadata, 23 imageIdStr, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 IMFFilename, in product component index, 21 intro, in product component index, 21 inverseFlattening, in image metadata, 35 ISD

defined, 62

delivery-level, 7 file described, 8 files delivered, 7 overview, 6 product component level, 7

JPEG2000, defined, 62 jpegProfileName, in image metadata, 26 latestAcqTime, in image metadata, 34 latOffset, in RPC00B file, 48 latScale, in RPC00B file, 48 layout file


LE, defined, 62 LE90, defined, 62 license file


licenseTxtFilename, in product component index, 21 lineDenCoef, in RPC00B file, 48 lineNumCoef, in RPC00B file, 48 lineOffset, in RPC00B file, 48 lineScale, in RPC00B file, 48 LLColOffset, in tile map file, 43 LLH, in image metadata, 39 LLHAE, in image metadata, 27 LLLat

in image metadata, 27 in tile map file, 44

LLLon in image metadata, 27 in tile map file, 44

LLRowOffset, in tile map file, 44 LLX


LLY in image metadata, 38 in tile map file, 45

longOffset, in RPC00B file, 48 longScale, in RPC00B file, 48 LRColOffset, in tile map file, 43 LRH, in image metadata, 38 LRHAE, in image metadata, 27 LRLat

in image metadata, 27 in stereo file, 53 in tile map file, 44

LRLon in image metadata, 27


in stereo file, 53 in tile map file, 44

LRRowOffset, in tile map file, 43 LRX


LRY in image metadata, 38 in tile map file, 45

manifest file defined, 50 described, 8 example, 50 overview, 7

mapHemi, in image metadata, 36 mapProjCode, in image metadata, 35 mapProjName, in image metadata, 35 mapProjParam, in image metadata, 36 mapZone, in image metadata, 36 maxCollectedColGSD, in image metadata, 30 maxCollectedRowGSD, in image metadata, 30 maxCrossTrackViewAngle, in image metadata, 32 maxInTrackViewAngle, in image metadata, 32 maxOffNadirViewAngle, in image metadata, 33 maxSatAz, in image metadata, 31 maxSatEl, in image metadata, 31 maxSunAz, in image metadata, 30 maxSunEl, in image metadata, 31 MBR, defined, 62 meanCollectedColGSD, in image metadata, 30 meanCollectedGSD, in image metadata, 30 meanCollectedRowGSD, in image metadata, 30 meanCrossTrackViewAngle, in image metadata, 33 meanInTrackViewAngle, in image metadata, 32 meanOffNadirViewAngle, in image metadata, 33 meanProductColGSD, in image metadata, 30 meanProductGSD, in image metadata, 30 meanProductRowGSD, in image metadata, 30 meanSatAz, in image metadata, 31 meanSatEl, in image metadata, 31 meanSunAz, in image metadata, 31 meanSunEl, in image metadata, 31 mediaCreationDate, in delivery index, 13 metadata, defined, 62 minCollectedColGSD, in image metadata, 30 minCollectedRowGSD, in image metadata, 30 minCrossTrackViewAngle, in image metadata, 32 minInTrackViewAngle, in image metadata, 32 minOffNadirViewAngle, in image metadata, 33

minSatAz, in image metadata, 31 minSatEl, in image metadata, 31 minSunAz, in image metadata, 30 minSunEl, in image metadata, 31 mode, in image metadata, 28 mosaic seamlines file, described, 16 Mosaic, defined, 62 MOSAIC_CLOSEDPOLYGONS shapefile, fields described,

19 MrSid format, defined, 63 MS, defined, 63 Multispectral, defined, 63 Nadir, defined, 63 National Imagery Transmission Format, defined, 63 nearest neighbor, defined, 63 NED, defined, 63 NIIRS, defined, 63 NIR1, defined, 63 NIR2, defined, 63 NITF format, defined, 63 normalized values, defined, 46 NRG, defined, 63 numberOfLooks

in delivery index, 15 in image metadata, 26

numColumns, in image metadata, 25 numGCP, in image metadata, 39 numPair, in stereo file, 52 numRows, in image metadata, 25 numTiles, in tile map file, 42 numTLC, in image metadata, 29 nwLat, in delivery index, 15 nwLong, in delivery index, 15 offNadir

in MOSAIC_CLOSEDPOLYGONS shapefile, 19 in STRIP shapefile, 17

off-nadir angle, defined, 63 ORDER shapefile, fields described, 17 orderDesc, in ORDER shapefile, 17 orderNumber, in delivery index, 13 orientationAngle, in image metadata, 36 originX, in image metadata, 36 originY, in image metadata, 36 orthorectification, defined, 63 outputFormat, in image metadata, 28 overlap, in stereo file, 52 pan/panchromatic, defined, 64 panSharpenAlgorithm, in image metadata, 25 pan-sharpened, defined, 64


photogrammetry, defined, 64 PIXEL shapefile, fields described, 19 pixel, defined, 64 PNIIRS

defined, 64 in image metadata, 33

positionKnowledgeSrc, in image metadata, 34 postSpacing, in image metadata, 37 prodDate, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 prodDesc

in PIXEL shapefile, 19 in PRODUCT shapefile, 18 in TILE shapefile, 18

product area file, described, 16 product browse file

defined, 40 described, 8 example, 41 overview, 7

product component areas file, described, 16 product component index contents, 21 product component index file

contents, 21 described, 8 overview, 7

product component level ISD, 7 product component XML file

described, 49 example, 49

product framing, defined, 64 product level to product type relationships, 40 product pixel area file, described, 16 PRODUCT shapefile, fields described, 18 product subcomponent areas file, described, 16 product types covered, 6 productAccuracy, in image metadata, 24 productCatalogID, in image metadata, 23 productGSD, in image metadata, 37 productLevel, in image metadata, 25 productOrderId, in image metadata, 23 productScale

in delivery index, 14 in image metadata, 24

productType, in image metadata, 26 productUnits, in image metadata, 36 projection, in ORDER shapefile, 17 PVL

defined, 64 described, 10 example of format, 54

QB02, defined, 64 radiometric correction, defined, 64 radiometricEnhancement, in image metadata, 26 radiometricLevel, in image metadata, 26 rational functions, illustrated, 46 rational polynomial coefficients, defined, 45 RCP terms, 46 readme

contents, 13 relAcc, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 relAccUnit, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 remote sensing, defined, 64 resamplingKernel, in image metadata, 34 resolution, defined, 64 restrictedAreaIntersect, in image metadata, 26 revNumber, in image metadata, 34 RGB, defined, 64 RMSE, defined, 64 RMSE2D, in image metadata, 24 rowSpacing, in image metadata, 37 rowUncertainty, in image metadata, 30 RPC, defined, 64 RPC00B file

described, contents, 47

overview, 7 RPC00Bfilename, in product component index, 22 sampDenCoef, in RPC00B file, 48 sampNumCoef, in RPC00B file, 48 sampOffset, in RPC00B file, 48 sampScale, in RPC00B file, 48 satellite, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 satId

in image metadata, 28 in RPC00B file, 47

scale, defined, 65 scanAz, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 scanDir, in MOSAIC_CLOSEDPOLYGONS shapefile, 19 scanDirection, in image metadata, 29 seamlines, defined, 65 secondId, in stereo file, 52 seLat, in delivery index, 15 seLong, in delivery index, 15 semiMajorAxis, in image metadata, 35 sensor azimuth, defined, 65 sensor correction, defined, 65 spatial mosaic, defined, 65 SpecId, in RPC00B file, 47 SRTM, defined, 65


stereo file contents, 52 defined, 51 described, 8 overview, 8

stereo geometry, illustrated, 52 stereo, defined, 65 stereoFilename, in product component index, 22 strip or substrip area file, described, 16 STRIP shapefile, fields described, 16 stripDesc, in STRIP shapefile, 16 sun azimuth, defined, 65 sun elevation, defined, 65 sunAz, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 sunAzimuth, in STRIP shapefile, 17 sunEl, in MOSAIC_CLOSEDPOLYGONS shapefile, 20 sun-synchronous, defined, 65 swath-width, defined, 65 target azimuth, defined, 65 TDI, defined, 65 TDILevel, in image metadata, 28 terrain correction, defined, 65 terrainHAE, in image metadata, 39 tile map file

contents, 41 described, 8 example, 60 overview, 7

TILE shapefile, fields described, 18 tileName, in TILE shapefile, 18 tileOverlap, in tile map file, 42 tileSizeX, in tile map file, 42 tileSizeY, in tile map file, 42 tileUnits, in tile map file, 42 tilFilename, in product component index, 22 tiling, explained, 41 time, defined, 12 TLC, defined, 65 TLCList, in image metadata, 29 TLCTime, in image metadata, 29 top-level delivery index

contents, 13 top-level index (readme) file

overview, 7 described, 8

top-level index (XML) file overview, 7 described, 8

ULColOffset, in tile map file, 42

ULH, in image metadata, 38 ULHAE, in image metadata, 27 ULLat

in image metadata, 27 in stereo file, 53 in tile map file, 44

ULLon in image metadata, 27 in stereo file, 53 in tile map file, 44

ULRowOffset, in tile map file, 42 ULX


ULY in image metadata, 38 in tile map file, 44

universal transverse mercator coordiante system, defined, 65

URColOffset, in tile map file, 43 URH, in image metadata, 38 URHAE, in image metadata, 27 URLat


URLon in image metadata, 27 in tile map file, 44

URRowOffset, in tile map file, 43 URX


URY, in tile map file, 45 UTM, defined, 66 version

in delivery index, 13 in image metadata, 23 in product component index, 21

verticalAccuracy, in image metadata, 39 volNum

in PIXEL shapefile, 19 in PRODUCT shapefile, 18 in TILE shapefile, 18

WV01, defined, 66 WV02, defined, 66 WV03, defined, 66 XML file

described, 8, 10 example, 57

overview, 7 XMLFilename, in product component index, 21

High Resolution Stereo Satellite Elevation Mapping ServiceConfirmed Proof of Accuracy

Case History, WorldView-1 Stereo Photos, Asmara, Eritrea

A one-metre square grid of elevations was produced by geophysical processing of WorldView-1 stereo satellite photos over an area of 374 square kilometres.

The elevation accuracy is better than 35cm RMSE for areas up to 10km by 10km as determined by over 15,000 conventionally established elevation checkpoints.

Gerry Mitchell, P. Geo, Geophysicist, President PhotoSat Information Ltd;Kevin MacNabb, Geophysicist, President MWH Geo-Surveys Inc.

A 1m square grid of elevation values, covering an area of 374 square kilometres, was produced for the Asmara Project of Sunridge Gold in Eritrea (TSX.V:SGC). The elevation grid was constructed using geophysical processing of 50cm ground resolution stereo satellite photos taken by the Digital Globe WorldView-1 satellite. The stereo satellite elevations were referenced to the same benchmark as over 15,000 previously established accurately surveyed gravity survey stations.

Figure 1. Stereo satellite elevation map with 5m contours showing some of the 15,020 checkpoints used to determine the elevation mapping accuracy of better than 35cm Root Mean Square Error (RMSE) for areas up to 10km by 10km for the WorldView-1 stereo photos on the Sunridge Gold Asmara Project. For more information about the Sunridge Gold Asmara Project, please consult the Sunridge Gold website: www.Sunridgegold.com/s/Asmara.asp

1

http://www.Sunridgegold.com/s/Asmara.asp

Figure 2. Asmara Project, Eritrea. MWH Geo-Surveys differential GPS survey crew and equipment. Over 45,000 gravity stations were surveyed from 2004 through 2008 using differential GPS instruments from Magellan. All of the GPS positions were surveyed in Real Time Kinematic (RTK) mode with accuracies of 2cm or better. 15,020 of these gravity survey stations were used as elevation checkpoints for the WorldView-1 stereo satellite elevation mapping accuracy assessment. The Magellan RTK base with a ProMarkTM 500 GPS rover are shown in this photo.

Figure 3. The entire 374 square kilometre Asmara, Eritrea WorldView-1 stereo satellite elevation mapping project was tied to the single ground control point shown in this photo. The accuracy of the stereo satellite elevation mapping of better than 35cm RMSE for areas up to 10km by 10km was determined using 15,020 independent elevation checkpoints.

2

GPS

Figure 4. WorldView-1 50cm stereo photo. Asmara, Eritrea.

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Figure 5. Stereo WorldView-1 elevation image created from a 1m posted DEM. Asmara, Eritrea.

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Figure 6. 50cm contours from the stereo WorldView-1 elevation mapping showing the elevations of some of the 15,020 elevation checkpoints used to determine the stereo satellite elevation mapping accuracy of better than 35cm RMSE for areas up to 10km by 10km.

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Figure 7. Area of the 22km by 17km Eritrea Stereo WorldView-1 1m posted DEM showing the single ground control point and the 15,020 gravity survey stations used as elevation checkpoints to determine the accuracy of the stereo satellite elevation mapping. As recommended in the Guidelines for Digital Elevation Data of the US National Digital Elevation Program (NDEP), the elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Figure 8. Area of the 22km by 17km Eritrea Stereo WorldView-1 1m posted DEM showing the 2,538 regional gravity survey stations, in a grid of approximately 250m by 350m, used as elevation checkpoints to determine the accuracy of the stereo satellite elevation mapping. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Figure 9. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and the 2,538 regional elevation checkpoints. The Root Mean Square Error (RMSE) is 42cm, and the Linear Error (LE90) is 65cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Figure 10. Plot of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and the 2,538 regional elevation checkpoints as a function of Northing. The least squares regression line has a slope of -4.3cm/km.

Figure 11. Plot of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and the 2,538 regional elevation checkpoints as a function of Easting. The least squares regression line has a slope of -1.2cm/km.

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Figure 12. Plot of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area, adjusted by 4.3cm/km North-South, and the 2,538 regional elevation checkpoints as a function of Northing. This simulates the adjustment of the DEM to fit at least two perfect ground control points.

Figure 13. Plot of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and the 2,538 regional elevation checkpoints as a function of Easting, after the North-South adjustment by 4.3cm/km. The least squares regression line has a slope of 0.5cm/km.

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Figure 14. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and the 2,538 regional elevation checkpoints, after the North-South adjustment by 4.3cm/km. RMSE 34cm, LE90 50cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

Figure 15. The semivariogram of the elevation differences between the WorldView-1 stereo satellite elevations and the 2,538 regional checkpoints in a 250m by 350m grid shows a very close correlation of the elevation differences out to a distance of 10km between elevation points.

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Figure 16. Areas with 20m by 100m grids of gravity survey stations used as elevation checkpoints to determine the accuracy of the stereo satellite elevation mapping. Area A has 6,479 checkpoints over an area of 5.1km by 4.6km, area B has 1,827 checkpoints over an area of 2.2km by 1.7km, area C has 1,958 checkpoints over an area of 4.3km by 1.6km, area D has 2,218 checkpoints over an area of 2.7km by 2.0km. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Figure 17. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for area A (5.1km by 4.6km) and the 6,479 elevation checkpoints, after the North-South adjustment by 4.3cm/km. RMSE 32cm, LE90 50cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

Figure 18. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for area B (2.2km by 1.7km) and the 1,827 elevation checkpoints, after the North-South adjustment by 4.3cm/km. RMSE 26cm, LE90 35cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Area A5.1km by 4.6km

Area B2.2km by 1.7km

Figure 19. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for area C (4.3km by 1.6km) and the 1,958 elevation checkpoints, after the North-South adjustment by 4.3cm/km. RMSE 29cm, LE90 45cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

Figure 20. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for area D (2.7km by 2.0km) and the 2,218 elevation checkpoints, after the North-South adjustment by 4.3cm/km. RMSE 29cm, LE90 45cm. The elevation checkpoints are not in areas with slopes greater than 20% grade, beside buildings, nor on narrow topographic ridges.

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Area C4.3km by 1.6km

Area D2.7km by 2.0km

Figure 21. Histogram of the elevation differences between the WorldView-1 stereo satellite elevations for the 22km by 17km area and 638 regional elevation checkpoints in areas with slopes greater than 20% grade, after the North-South adjustment by 4.3cm/km. RMSE 60cm, LE90 100cm.

Cautionary Statement: This is an accuracy assessment for elevation mapping from a single stereo pair of WorldView-1 satellite photos. While we expect that these results will be typical for most WorldView-1 stereo photos, we cannot yet confirm that these results apply to more than this pair of stereo photos.

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For stereo satellite elevation mapping, contact:

For gravity surveying and ground control points, contact:

Tel: (250) 542-9897 (775) 722-0616

Tel: (604) 681-9770

www.mwhgeo.com

Slopes 20% to 100% grade

Slopes 20% to 100% grade

WORLDVIEW-2 Imagery Basics and ERDAS IMAGINE

Import DigitalGlobe tiled data (.TIL) with ERDAS IMAGINE ERDAS has added support in IMAGINE 2011 for the DigitalGlobe .TIL format. DigitalGlobe often delivers images cut into smaller tiles that do not overlap. Often times image files can be extremely large in file size. To better handle these large files in 3rd party software, DigitalGlobe’s customers have the option to tile the imagery. An ancillary .TIL text file provides a list of these tiles and their relationships. To use these files in georeferencing workflows, they must be assembled back into a single original image. The ERDAS IMAGINE importer now allows you to select a .TIL file and import all the tiles into a single file. The georeferencing information (RPC) is still preserved (see “DigitalGlobe RPC in ERDAS IMAGINE” documentation for RPC explanation). Additionally, this support can be used for direct-read scenarios, so the assembled tiles can be used directly in workflows without first processing them into a new file. Users can type *.TIL in the file chooser to expose this option. Note: This feature works for both NITF and TIFF tiled files, and the .RPB file must reside in the same folder as the imagery tiles for proper georeferencing.

Fig.1. Importing Tiled Imagery

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To import a DigitalGlobe .TIL file in ERDAS IMAGINE, follow the steps below.

1. Open ERDAS IMAGINE and click on the Manage Data tab

Fig.2. Import Data

2. Click Import Data

3. In the Import Dialog, change the Type to DigitalGlobe TIL 4. For the Input File, navigate to the directory where your DigitalGlobe imagery is stored

and select the .TIL file (see fig.3)

5. Change the Output File name and directory as desired and click OK.

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Fig.3. Import DigitalGlobe TIL

Note: By default, the import process will create an .img file, but you have the option of writing the .TIL file directly to any of the formats shown in the figure 4.

Fig.4. Ouput .img file

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Create an Ortho from existing RPC model

1. When the import process is finished, open the new file in the Viewer. File > Open > Raster Layer

2. Click on the Multispectral tab and click the Transform and Ortho drop down menu

and select Ortho Using Existing Model. (see below)

Fig.5. Select Ortho Using Existing Model

In the Resample dialog, note that the Current Geo Model is RFunctions, meaning the import process preserved the RPC information and we can now create an ortho. Note the Elevation Source is set to Elevation Library by default. The Elevation Library Manager provides a method to collect and manage your elevation source files, including Digital Elevation Model data (DEM), as well as Digital Terrain Elevation Data (DTED) use by the U.S. National Geospatial-Intelligence Agency.

3. Name the Output file and click OK

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Fig.6. Resample

4. Once the orthorectification process is complete, dismiss the process window by clicking

Dismiss and open the new Ortho Image in the viewer.

5. On the main menu select File > Open > Raster Layer and navigate to the folder with your new Orthorectified Image

Switching Band Combinations with WorldView-2 WorldView-2 is the first sensor of its kind to offer 8 multispectral imaging bands. Up until the launch of WorldView-2 most high resolution satellites imaged with four (4) multispectral bands (Blue, Green, Red and Near-Infrared) or less. WorldView-2 not only images with those bands mentioned but also employs the Coastal Blue Band, Yellow Band, Red-Edge Band and Near-Infrared 2 Band. This allows for more of the visible spectrum to be absorbed by the sensor ultimately providing more information within the pixels of the image. In IMAGINE 2011, ERDAS has added additional band combinations designed specifically for WorldView-2. For an in-depth look at the benefits of the Eight Spectral Bands of WorldView-2 please visit http://www.digitalglobe.com/sites/default/files/DG-8SPECTRAL-WP-WEB.pdf

http://www.digitalglobe.com/sites/default/files/DG-8SPECTRAL-WP-WEB.pdf

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1. From the ERDAS IMAGINE 2011 main menu bar click on File > Open > Raster Layers and navigate to the folder that contains your WorldView-2 image.

Note: Multispectral Imagery from DigitalGlobe resides in a subdirectory with a _MUL in the folder name (e.g. 05225877010_01_P001_MUL)

Fig.7. Band Groups (WorldView-2)

2. From the ERDAS IMAGINE 2011 main menu bar click on the Multispectral tab and change the sensor to WorldView-2 in the Bands group. From the drop down list you can easily switch between pre-defined band combinations for WorldView-2 (See Fig.7).The document http://www.digitalglobe.com/downloads/white-papers/DG-8SPECTRAL-WP.pdf provides great insight into what each band may be suitable for in different multispectral analysis applications

Hyperspherical Color Space (HCS) Pan Sharpening Pan-sharpening is a technique that merges high-resolution panchromatic data with medium-resolution multispectral data to create a multispectral image with higher-resolution features. Hyperspherical Color Space Pan Sharpening was designed specifically with WorldView-2 in mind and is a new feature in IMAGINE 2011. However, HCS works with any multispectral data containing 3 bands or more. For more information on HCS please visit http://www.digitalglobe.com/downloads/WorldView-2_Pan-Sharpening.pdf

http://www.digitalglobe.com/downloads/white-papers/DG-8SPECTRAL-WP.pdf

http://www.digitalglobe.com/downloads/WorldView-2_Pan-Sharpening.pdf

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1. To Pan-Sharpen using the HCS technique click on the Raster Tab, and select the Pan Sharpen pull down and select HCS Resolution Merge

Fig.8.HCS Resolution Merge

To pan sharpen DigitalGlobe imagery you will need both the multispectral image files as well as the panchromatic image files. WorldView-2 bundle products contain both of these file sets. The input multispectral and panchromatic images can be found in a sub directory with multispectral (_MUL in folder name) and panchromatic (_Pan in folder name) images living in their respective folders.

2. Navigate to the folder with the Pan file and select it for the High Resolution Input (Pan) File (This can be GeoTiff, NITF, or IMG)

3. Navigate to the folder with the Multispectral file and select it for the Multispectral Input File (This can be GeoTiff, NITF, or IMG)

4. For the Output File navigate to a folder where you would like the pansharpen file to reside. Name this file. It will be given a .img extension

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Fig.9. Hyperspherical Color Space Resolution Merge

5. Under the output dropdown you’ll see a check box with “Stretch to Unsigned 8bit” This

function will apply a minimum maximum stretch range from 0-255 to the image. Min-max function makes the range of the lookup table vary linearly from the minimum statistics value to the maximum statistics value in the input (X) direction and from 0 to the maximum brightness value in the output (Y) direction. For this example we’ll leave this unchecked.

6. For Process Area we’ll leave intersection as the input since it will automatically use the

intersection of the Pan and Multi image

7. For Resampling we’ll select Bilinear Interpolation.

Which technique is best will largely depend on the relative spatial resolutions of the data being merged. Any use of the Nearest Neighbor option will likely result in edge effects still being visible in the merged data at the interval of the original multispectral pixel sampling; however, it is the fastest technique to use. If the ratio of high resolution to low resolution is 2:1 (for example, Landsat 15 m Pan to Landsat 30 m multispectral), then Bilinear Interpolation is a reasonable compromise of image quality and speed of processing. For pixel ratios of 4:1 or higher (for

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example, QuickBird 60 cm Pan to QuickBird 2.4 m multispectral), the 4x4 sampling window used by cubic convolution may provide the better results. However, in some cases, Cubic Convolution has proved to generate worse results than Bilinear Interpolation. We recommend that Bilinear Interpolation be used whenever the merge is performed on large files that will take a considerable amount of time. For smaller merges that can be performed quickly, you may wish to try both Cubic Convolution and Bilinear Interpolation, and choose the result based on visual inspection of the output of each resampling technique.

8. The default for smoothing filter is 7. We’ll use this value for this process. Smoothing Filter defines the size in pixels of the filter used to smooth the output image. This option uses a square window filter surrounding the pixel of interest, therefore enter an odd number. The default setting is 7x7. Smoothing softens the transition between the images.

9. When the process has finished, go to the Home tab, select the Add Views menu and select Display Three Views.

10. Go back to the Add Views menu and select Vertical Layout.

Fig.10. Add Views menu

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11. Open your Multispectral.img in View #1

12. Open your panchromatic.img in View # 2

13. Open your HCS.img in View # 3

Use some of the tools shown below to link all of the views and roam around the images to see the new .5 meter 8 band image.

14. You can also use the tools at the top right of each viewer to link / unlink and sync the different viewers.

Fig.11. Example of Multispectral, Panchromatic, and HCS Pansharpened Image

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Discriminant Function Change Detection DigitalGlobe’s vast archive of satellite imagery (well over a billion square kilometers) is perfectly suited as a historical account of change on the earth. For a trained imagery analyst the process of detecting change from one image date to another may be an easy task. However this is not always economically feasible. ERDAS IMAGINE software employs algorithms to extract information from satellite imagery in an automated fashion. For the IMAGINE 2011 release, ERDAS, Inc. has developed a new algorithm for change detection between two co-registered images acquired at different dates. This algorithm, named Discriminant Function Change (DFC), characterizes the natural distribution of spectral clusters in one image’s data space and then uses a discriminant function to measure probability of change of the pixels in the other image. WorldView-2 is well suited for this application because of its ability to collect more of the visible spectrum with its 8 band technology.

For more technical information on DFC please visit https://sgisupport.intergraph.com/infocenter/index?page=home And search for “Discriminant Function Change in ERDAS IMAGINE”

1. To begin the Discriminant Function Change Detection application click on the Raster tab and select Discriminant Function Change

Fig.12. Discriminant Function Change Menu

Note: You will need at least two images from different dates over the same location in order to run the DFC algorithm. For this example we use two images; one from the QuickBird Satellite taken on the 6th of January and one from the WorldView-2 Satellite taken on the 10th of June.

2. Select 06jan_qbsubset2.img as the Input Before Image and 10jun_wv2_subset.img as the Input After Image as seen below.

https://sgisupport.intergraph.com/infocenter/index?page=home

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Fig.13. Discriminant Function Change Detection

3. Check the boxes for Positive Change, Negative Change and Combined Change and name

the output file accordingly as seen in the figure above.

4. Click OK to run the process.

5. When the process is completed, open the before, after and combined.img files in the same viewer. Make sure the combined.img is the top layer and is active, then select Panchromatic tab.

6. Select the General Contrast drop down menu and click Load Breakpoints

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Fig.14.Load Breakpoints

7. Select the combined_break.mbp file and click OK

Fig.15. Select BreakPoints File

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This filters the points in the viewer, so that only points with > 90% probability of change appear.

8. Fit the image to frame using the on the Home tab. Take note of some of the areas of significant change (white areas) and zoom to those areas to investigate further. You can use the Swipe / Blend / Fade Tools or you can use the check boxes in the table of contents to turn layers on or off.

Fig.16. Discriminant Function Change Detection Image

For more information on ERDAS IMAGINE go to https://sgisupport.intergraph.com/infocenter/index?page=home For more technical information on DigitalGlobe Products and Services please visit the Resources tab at http://www.digitalglobe.com/

https://sgisupport.intergraph.com/infocenter/index?page=home


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