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Lidar and GIS: Applications and Examples

Learn how to analyze Lidar data in GIS with this comprehensive guide. Explore topics like Lidar point coverage, canopy density estimation, floodplain delineation, and 3D city modeling. Discover tools and workflows for creating raster DEMs and DSMs, feature extraction, and more.

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Lidar and GIS: Applications and Examples

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  1. Lidar and GIS:Applications and Examples Dan Hedges Clayton Crawford

  2. Outline • Data structures, tools, and workflows • Assessing lidar point coverage and sample density • Creating raster DEMs and DSMs • Data area delineation • Estimating forest canopy density and height • Floodplain delineation • Feature Extraction for 3D City Modeling

  3. 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 • Both file and database oriented solutions

  4. Supporting Data structures and Tools • Point File Information • LAS To Multipoint • ASCII 3D To Feature Class • Point To Raster • Terrain To Raster • Terrain To TIN • Vector features • points • multipoints • lines • polygons • Raster • TIN • Terrain Dataset Function Output Input Workflow

  5. Supporting Data structures and Tools • LAS dataset… • Change LAS Class Codes • Classify LAS By Height • Classify LAS Ground • Extract LAS • Locate LAS Points By Proximity • Mosaic dataset • Extensive collection of raster tools • LAS dataset • LAS Dataset Statistics • LAS Dataset To Raster • LAS Point Statistics As Raster • LAS Point Statistics By Area • LAS Dataset To TIN • Set LAS Class Codes Using Features Function Output Input Workflow

  6. Lidar Point Coverage and Sample Density • Basic QA/QC before loading data into geodatabase • Verify xy and z extent • Examine point spacing = ?

  7. LAS Dataset Layer

  8. LAS Dataset Properties

  9. 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

  10. Point File Information Tool

  11. LAS Point Statistics As Raster Tool Pulse/sample density

  12. Demo

  13. Creating Raster DEMs and DSMs Digital Elevation Model Digital Surface Model Bare earth surface made using only ground hits. Includes ground, trees, and buildings made using first returns.

  14. LAS Dataset To Raster • Binning • Fast • Reasonable for DSMs • Void filling options • Honors replace andclip constraint types • Triangulation • True interpolation • Always fills voids • Appropriate for DEMs • Honors all constraint types

  15. Data Area Delineation Constraint applied Dense collection of source measurement points (green) Triangulation of those points without a boundary constraint

  16. Workflow to Calculate a Data Area Polygon Input LAS dataset LAS Point Statistics As Raster Con Expand Shrink Raster to Polygon Output polygonfeature class Eliminate Polygon Part

  17. Demo

  18. Estimating Forest Canopy Density and Height

  19. Canopy Density and Height • Density is the ratio of vegetation hits to total hits within a unit area (i.e., raster cell). • LAS Point Statistics As 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 • Sometimes referred to as normalized DEM (nDSM) or Canopy Height Model (CHM) • LAS Dataset to Raster or Terrain to Raster followed by Minus.

  20. Floodplain Delineation

  21. 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)

  22. Demo

  23. Roof-Form Extraction for Procedural Building Modeling • Extract information about roof shape and height from lidar-derived surfaces • Symbolize buildings in 3D using procedural rules • Review output against LAS dataset

  24. Automated Roof-Form Attribute Extraction • Classify areas of like slope & aspect in DSM • Create roof-plane polygons • Extract attributes

  25. Procedural Modeling Ridge Direction • Ridge Height = Highest point • Eave Height = Lowest point • Ridge Direction = Perpendicular to roof slope • Roof form = Dependent on plane types found in footprint Ridge Height Eave Height Roof Form: Gable

  26. Procedural Modeling • Roof types automatically classified Gable Flat Hip • Other types supported: • Shed • Dome • Vault • Mansard

  27. Reviewing Output • Compare procedural symbols directly against lidar • Manual changes update on-the-fly

  28. Demo

  29. Do It Yourself! • ‘Schematic City’ workflow in ArcGIS for Local Government Solutions • Task-based workflow for ArcGIS Pro • Includes other workflows for 3D tree creation, and 3D city analysis • ArcGIS for 3D Cities: An Introduction • Wednesday and Thursday 1:30 - 2:45 • http://solutions.arcgis.com/local-government/help/local-government-scenes/

  30. Questions?

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