CCGISUG Best Practices for Working With LiDAR Data in ArcGIS
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Transcript of CCGISUG Best Practices for Working With LiDAR Data in ArcGIS
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LiDAR Solutions in ArcGIS
John Sharrard
GIS Solutions Engineer
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Outline
• Esri‟s “Big Picture” concerning LiDAR
• Data structures, tools, and workflows
• Terrains
• Some processing examples
• What‟s coming at 10.1 – Direct LiDAR read
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Big Picture
• Solutions for GIS end users
- Not about LiDAR data production
• Operate on clean/classified LiDAR points
• Produce useful derivatives
• Perform analysis
• Handle large datasets
• Database oriented
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Supporting Data structures and Tools
• Vector features
- points
- multipoints
- lines
- polygons
• Raster
• TIN
• Terrain Dataset
FunctionInput Output
Workflow
• Point File Information
• LAS To Multipoint
• ASCII 3D To Feature Class
• Point To Raster
• Terrain To Raster
• Terrain To TIN
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What are Terrains ?
• A Terrain is a multi-resolution surface created from measurements stored in geodatabase feature classes
• New dataset at ArcGIS 9.2
• Terrains live inside Feature Datasets
• Typical applications:
- Topographic mapping
- Bathymetric mapping
• Typical data sources:
- Photogrammetric data
- LIDAR
- SONAR
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What are Terrains?
• Characteristics of Terrains:
- Feature classes participate
- Rules specify how features are used to define a surface
- TIN based
- Multi-resolution
Feature Classes Participate in Terrain
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Multi-resolution terrain dataset (TIN structure)
Multi-Resolution Surface Model
Points and Breaklines
Terrain Pyramids
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Implementation
• TIN surface generated on-the-fly for given area of interest and
level of detail
• Supports point, multipoint, polyline, and polygon based
features
• Seamless
• Fast
• Scalable
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Terrain Pyramids
• Similar to raster pyramids in concept, but built from source measurements
• Reduced point sets thinned based on vertical tolerance
• Scale threshold associated with each level
Levels
of
Detail
Z-Tolerance Scale
0 0 1:1
1 1 2500
2 5 10,000
3 10 50,000
4 20 100,000
Points
The distance between the lower
resolution surfaces and the full
resolution surface will not exceed a
given Z-tolerance.
z-tolerance
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Contours
Terrain Dataset WorkflowData Conversion Product Generation
Pro
prie
tary
or d
e-fa
cto
stan
da
rd fo
rma
ts
Surface Integration
ArcGIS
Terrain
Dataset
Pyramid
TIN surfaces
Points Breaklines DEM TIN
LIDAR post-
processed data
(points)
SONAR post-
processed data
(points)
Photogrammetric
data
(points & lines)
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Lidar point coverage and sample density
• Basic QA/QC before loading data into geodatabase
• Verify xy and z extent
• Examine point spacing
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Point File Information Tool
• Inputs files (LAS and ASCII) and folders of files and
outputs a polygon feature class.
• Each output record includes
- Polygon of file‟s data extent
- Source filename
- Point count
- Point spacing estimate
- Z min
- Z max
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Point File Information Tool
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Loading Data: LAS To Multipoint Tool
• LAS = industry standard file format for LiDAR
• Multipoints used for efficiency
• Filter options
- By class
- By return
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Point to Raster Tool
• Used after points are loaded into geodatabase
• More detailed assessment than Point File
Information
• Based on actual points loaded
(i.e., filtered by class code or
return) rather summary of
entire file.
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Point To Raster: Sample Density
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Creating Raster DEMs and DSMs
Bare earth surface made using only
ground hits.
Includes ground, trees, and buildings
made using first returns.
Digital Elevation Model Digital Surface Model
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Point to Raster Tool
• Fast
• Rasterize based on multipoint vertex z
• Not true interpolation
• Doesn‟t support breaklines
• Data gaps
• Arguably works best with 1st return data because
there are fewer and smaller data voids to deal with.
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Point to Raster Post-process: Void Filling
Point To RasterRaster
Calculator
Con(IsNull("pt2ras"), FocalStatistics(“pt2ras", NbrRectangle(3, 3, "CELL"), "MEAN", "DATA"), "pt2ras")
Con(IsNull([pt2ras]), FocalMean([pt2ras], Rectangle, 3, 3, DATA), [pt2ras]) 9.3
10.0
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Don‟t Abuse Con
• Introduces anomalies if used repeatedly
Hilltop
Valley bottom
Nodata cells
Steeper slope
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Terrain to Raster
• Quality
• Supports ancillary data (breaklines, water bodies,
etc.)
• True interpolation
• Can handle large datasets
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Void Filling - Comparison
Terrain to Raster - interpolation Point to Raster followed by several
iterations of Con to reduce voids
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Data Area Delineation
Dense collection of source
measurement points (green).
Triangulation of those
points without a boundary constraint.
Constraint applied.
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Workflow to Calculate a Data Area Polygon
Point to
Raster
Input multipoint
feature class
Con Expand Shrink
Raster to
Polygon
Eliminate
Polygon Part
Output polygon
feature class
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Estimating Forest Canopy Density and Height
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Canopy Density and Height
• Density is the ratio of vegetation hits to total hits
within a unit area (i.e., raster cell).
- LAS to Multipoint to make two feature classes: ground
and non-ground.
- Point to Raster to make „count‟ grids.
- Add ground and non-ground to make a „total‟ grid.
- Use Divide to get the ratio between non-ground and
total.
• Height is the difference between DSM and DEM
- Use Point to Raster or Terrain to Raster followed by
Minus.
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Creating Intensity Images
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BLOB Based Storage of Intensity
BLOBs are used, in the context of LiDAR, to store multiple numeric values together in
one thing. Each BLOB contains as many values as there are vertices in the corresponding multipoint.
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Intensity Image Workflow
LAS To Multipoint
GP Tool
Output
multipoint feature class
Intensity Image
Input LAS files
Point To Raster
GP Tool
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Reducing Noise for Contouring and Slope
Analysis
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Lidar Is Noisy
• Lidar has measurement error
• Typically 12-15cm vertical accuracy
• Horizontal sample density is often 1m or less
• This results in high frequency noise
- Extremely messy contours
- Average slope skewed to be very high
• Goal is to reduce noise without degrading the
accuracy
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Point Thinning, Interpolation, and Rasterization
• Use only those points necessary
• Some applications refer to points selected for use in
making contours as „model key‟ points
• Terrain pyramids
- Original points filtered into different levels of detail
- Can specify which pyramid level to use when
interpolating to raster or extracting TIN
• Natural neighbors
- Conservatively smooth
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Point Thinning, Interpolation, and Rasterization
Input LiDAR
Create
Terrain GP Tool
Terrain To
Raster GP Tool
Contour
GP Tool
Slope
GP Tool
Workflow
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Floodplain Delineation
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Surface Difference Tool
• Subtract LiDAR based ground surface
from modeled (e.g., HEC-RAS) water
surface
• Output polygons used to
delineate floodplain
• Optional output of depth
surface(s)
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LAS Dataset – New Datatype in 3D Analyst 10.1
• Current support for LIDAR data in 10.0
• Motivation for LAS Dataset
• Other user workflows
• Import LAS files to Geo-database using “LAS To Multipoint” tool
• Point To Raster
• Terrain
• Quality review before importing and building surface models
• Emergency response applications (eg. Military)
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LAS Dataset – New Datatype in 3D Analyst 10.1
• LAS Dataset
• File based data structure (i.e., doesn‟t live in a geo-
database)
• Stores references to LAS files on disk
• Treats a collection of LAS files as one logical dataset
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LAS Dataset – New Datatype in 3D Analyst 10.1
• LAS Dataset – Native consumption of LAS files (Airborne)
• Quick Preview of point data in LAS format
• Display and query both as surface and as points
• Symbolize by LAS Attributes (Class code, Return, RGB
etc.)
• Editing (for fixing data anomalies, misclassifications)
• Support for break-lines (Surface constraints)
• Surface Analysis (Interpolate Shape etc.)
• Complimentary To Terrain
• LAS & Terrain as source to Mosaic Dataset
• Catalog very large collections
• Fast Access and Serving
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LAS Dataset – New Datatype in 3D Analyst 10.1
• Suitability
• Classified LAS files organized as „tiles‟
• All participating LAS files with the same Spatial Reference
(Projected Coordinate System)
• Project-based / Localized in scope
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Questions?
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