Mobile Bay Plume Remote Sensing NASA MRC RPC 14 April 2008 Skylab Image courtesy of NASA.
An Introduction to Remote Sensing A RSET Applied Remote SEnsing Training A project of NASA Applied...
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![Page 1: An Introduction to Remote Sensing A RSET Applied Remote SEnsing Training A project of NASA Applied Sciences NASA Remote Sensing Training Norman, OK June.](https://reader036.fdocuments.us/reader036/viewer/2022062518/56649f485503460f94c69daf/html5/thumbnails/1.jpg)
An Introduction to RemoteSensing
ARSET
Applied Remote SEnsing Training
A project of NASA Applied Sciences
NASA Remote Sensing TrainingNorman, OK
June 19-20, 2012
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What is Remote Sensing?
Remote sensing is a method of obtaining information about the properties of an object without coming into physical contact with it.
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Why use Remote Sensing to Study the Earth ?
• Provides visual Global information
• Complements ground-monitoring networks or provides information where there are no ground-based measurements
• Provides advance warning of impending environmental events and disasters.
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How Do Satellites Make Measurements?
• Passive satellite sensors measure radiation reflected or emitted by the earth-atmosphere system
- Radiance
• Radiance is converted to a geophysical parameter.
Examples:
Accumulated Rainfall
Snow Cover
Accumulated Rainfall Guatemala
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Example of Remote Sensing Product Precipitation Radar from TRMM
(Guatemala)
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Types of satellite orbits
Geostationary orbit
Fixed’ above earth at ~36,000 km
Frequent Measurements
Limited Spatial Coverage
Low Earth Orbit (LEO)
- Polar (Aqua, Terra)) - Nonpolar (TRMM)
Circular orbit constantly moving relative to the Earth at 160-2000 km
Less Frequent measurements (< 2 times per day)
Large (global) spatial Coverage
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Low Earth Orbit (LEO):Orbiting at an altitude of 160-2,000 km.
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Path of Satellite
Low-Earth Orbits (LEO)
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Ascending Orbit:Moving South to North when that portion of the orbit track crosses the equator.
Low Earth Orbit:Orbiting at an altitude of 160-2,000 km.
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Path of Satellite
Low-Earth Orbits (LEO)
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Descending Orbit:Moving North to South when that portion of the orbit track crosses the equator.
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Low-Earth Orbits (LEO)
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Aqua (“ascending” orbit) day time
Terra (“descending”) Day time
LEO Polar Orbiting
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• Near-polar, sun-synchronous, orbiting the Earth every 98.8 minutes, crossing the equator going north (daytime ascending) at 1:30 p.m. and going south (night time descending) at 1:30 a.m.
• The orbit track changes every day but will repeat on a 16 day cycle. This is true for Aqua, Terra, and TRMM.
AquaAqua’’s Orbits Orbit
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Terra - Descending Aqua - Ascending
When looking at an image of a piece of the orbit the two sensors will have opposite ‘tilts’.
Daytime OrbitsDaytime Orbits
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TRMM (“ascending” orbit)
LEO nonpolar Orbiting
TRMM’s Low orbit allows its instruments to concentrate on the tropics. This image shows half the observations TRMM makes in a single day
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Earth-Observing Satellites
Sun-Synchronous:The satellite is always in the same relative position between the Earth and Sun.
Equator-Crossing Time:The local apparent solar time when the satellite crosses the equator.
Example: Terra has an equatorial crossing timeof 10:30 am, and is calledan “AM” or morningsatellite.
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The orbit is defined as having a cross-track and an along-track direction.
Direction of Satellite Motion
Along-Track Direction
Cross-Track Direction
LEO Field-of-View (FOV)
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Direction of Satellite Motion
Cross-Track Scanning
“Cross-Track Scanning,” Scan mirror swings back and forth.
Sensor observes pixels in sequence across track and along the direction of the satellite’s motion.
Earth-Observing Satellites
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Direction of Satellite Motion
Satellites in Low Earth Orbit have only an instantaneous Field-of-View (IFOV)
LEO Field-of-View (FOV)
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MODIS Orbit in 3D
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Remote Sensing Resolutions
• Spatial resolution
• Temporal resolution
• Spectral resolution
• Radiometric resolution
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Spatial Resolution
Spatial Resolution : A simple definition is the pixel size that satellite images cover.
Satellite images are organized in rows and column called raster imagery and each pixel has a certain spatial resolution.
Nadirpixel sizeOff-nadir
pixel size
FOVFOV IFOVIFOV
SatelliteSatelliteheightheight
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cylindrical isotropic projection
Native satellite view vs. map projection
increasing pixel size
bow-tie effect
Flight directionFlight direction
Sca
n d
irect
ion
Sca
n d
irect
ion
““BowTieBowTie”” effect effect
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Spatial Resolution of NASA Satellite Data Products
High Spatial resolution 250x250m; 500x500 m; 1x1 km; 0.05x0.05 degrees Example: MODIS True Color Imagery (RGBs) Moderate Spatial Resolution 0.25x0.25 degrees Example: TRMM precipitation products.
Low Spatial Resolution (Level 3) Primarily at 1 x 1 degree - derived from each data set’s native resolution product Example: AIRS surface air temperature
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Example: NASA High Spatial Resolution Product
2x2 km resolution MODIS TERRA
True Color Image over Southern California
January 4th, 2009
Source: NASA GSFC Rapidfire AERONET Subset for Fresno, CA
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Example: NASA Moderate Spatial Resolution Product
0.25x0.25 degree TRMM
Accumulated Rainfall over Guatemala
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Example: NASA Low Spatial Resolution Product
MERRA Monthly Precipitable Water 1.25 x 1.25 Degrees
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Temporal Resolution of Remote Sensing Data
The frequency at which data are obtained is determined by:
- Type and height of orbit
- Size of measurement swath
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Temporal resolution of Polar Orbiting Satellites
Example: Terra, Aqua
• Observations available only at the time of the satellite overpass.
• IR based observations available 2X a day (AIRS)
• Visible observations available 1X a day• Polar regions may have several observations
per day.
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Temporal resolution of nonpolar satellites
Example: TRMM
• Observations available only at the time of the satellite overpass.
• Observations available less than once a day
Note: derived products available at 3-hourly
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Remote Sensing – Resolutions
Spectral resolution – The number and range of spectral bands.
More bands = More information
Radiometric resolution – The bandwidth of the individual spectral bands. Important for avoiding or taking advantage of “atmospheric windows”
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Satellite data levels of processing and formats
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Levels of Data ProcessingLevels of Data Processing
Level 1 Source Data: L1a are raw radiance counts and L1b are calibrated radiances (after applying calibration to L1a)
Level 2 Derived geophysical variables at the same resolution and location as Level 1 source data (after applying atmospheric correction, etc.)
Level 2G Level 2 binned data mapped on a uniform space-time grid (Example: OMI Tropospheric NO2 at 0.25x0.25 degree resolution)
Level 3 Geophysical variables mapped on a uniform space-time grid in derived spatial and/or temporal resolutions (Example: MODIS Temperature at1x1 degree resolution)
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Levels of Data Processing and Spatial Resolution
• Level 1 and Level 2 data products have the highest spatial and temporal resolution
• Level 3 products are derived products with equal or lower spatial and temporal resolution than Level 2 products. Available hourly, daily and for some products also monthly
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Level 1 Products
Level 2 Products
Less Processing
More Processing
Orbital data
Level 3 Products
Global compositesof level 2 products
Used to produce
Used to produce
Levels of Data Processing
Orbital data
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Level 1 Products
Level 2 Products
Orbital data
Level 3 Products
Global compositesof level 2 products
Used to produce
Used to produce
More User Control
Less User Control
Harder to Use
Easier to Use
Levels of Data Processing
Orbital data
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Level 2 Example: Guatemala Precipitation Radar from TRMM
(4x4 km)
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Level 3 Example: TRMM Accumulated Rainfall
0.25x0.25 degree TRMM
Accumulated Rainfall over Guatemala
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Reprocessing: Applying a new algorithm to and entire data set.
Forward Processing: Applying the current algorithm to newly acquired data.
Important Terms for Level 2 and Level 3 Products
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Data Versions• For some NASA data products more than one
version may be available• Note: Giovanni products are the most recent data
version publicly available• For each level of processing versions of data are
periodically released as retrieval algorithms or other sources of information improve, e.g. V001, V002, V003
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Data Formats• Text/ASCII
pros: easy to read and examine the data right away (can
read with used tools such as excel and GIS software)
cons: large data files• Binary – HDF, NetCDF
pros: takes less space, more information (metadata,SDS)
cons: need specific tools or code to read the data• KML or KMZ (zipped KML)
pros - easy 2D and 3D visualization of the data
through free tools such as Google Earth. Data are very low
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HDF Data Formats
HDF is the standard format for most NASA data HDF files contain both data and metadata
SDS - Each parameter within an HDF file is referred to as an SDS (Scientific Data Set)
An SDS must be referenced precisely according to name when analyzing the data with your own computer code.
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Accessing different data formats
(Example: Giovanni Download Page)
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GIF KMZ HDF NetCDF ASCII
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Putting it all together: data file names
Data product: 3- Hourly Rain Rate (mm/hr) Version 6
Date (June 30, 2011)
Data format is HDF5Level of Processing is L3Version 6
Time (GMT hour: 21)
Data Format (HDF5)
3B42.110630.21.6A.HDF.Z Level 3
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Conclusions• NASA satellite data formats are varied and the most appropriate depends on specific user needs
• Available data formats include, ASCII, HDF, NetCDF, and KMZ
• Satellite data vary in spatial resolution depending on instrument characteristics and the level of processing (L2, L2G, L3)