Best Practices for Managing and Serving

Lidar and Elevation Data

Cody Benkelman

Expectations…

• This demo theater presumes an advanced audience…

• Data structures

- LAS & zLAS formats

- LAS Dataset

- Mosaic Dataset

• Longer presentations with further detail:

- Managing Lidar and photogrammetric point clouds

- Wednesday, Room 16 B 3:15 to 4:30 (1845 / 2107)

- Thursday, Room 15 A 1:30 to 2:45 (1845 / 1347)

Outline

• Workflow

- QA/QC of lidar data

- Creation of elevation surfaces (DTM & DSM)

- Management & sharing of elevation surfaces

- Sharing of lidar point files

• Automated workflows

Lidar – 3D points and derived 2.5D surfaces

Lidar QC

Quality Control Checks

• Class codes

• # of Return values

• Z (height) values

• Is coverage of project area complete?

• Pulse density

• Point density

Quality Control Checks

• Class codes

- Are they as requested? Accurate?

• # of Return values

- Are First, Second, Third, Fourth returns present?

• Z (height) values

- Is the range reasonable? (“Bird strikes”, points below ground)

• Is coverage of project area complete?

• Pulse density

• Point density

POINT STATISTICS

Quality Control Checks

• Class codes

- Are they as requested? Accurate?

• # of Return values

- Are First, Second, Third, Fourth returns present?

• Z (height) values

- Is the range reasonable? (“Bird strikes”, points below ground)

• Is coverage of project area complete?

• Pulse density

- # laser pulses sent out, per square meter

• Point density

- “echos” or “returns” received by the sensor

SPATIAL PROCESSING

Quality Control Part 1 – Data Statistics

• LAS Dataset Properties

Statistical Reports

• LAS Dataset Properties

Statistical Reports

• LAS Dataset Properties

Statistical Reports

• LAS Dataset Properties

Quality Control Part 2 – Spatial Processing

• Pulse Density

• Summarized per square unit area (meter)

• Output product is a raster (image / pixels)

Example:

4 outgoing pulses per

square meter

Quality Control Part 2 – Spatial Processing

• Point Density

• Summarized per square unit area (meter)

• Output product is a raster (image / pixels)

Example:

10 return pulses per square

meter

Quality Control Part 2 – Spatial Processing

• Pulse Density – Loss due to water absorption

• Summarized per square unit area (meter)

• Output product is a raster (image / pixels)

Example:

Fewer return pulses over

water

Best Practices

• Tiled LAS, v1.1 or higher

• Projected, rearranged, indexed

- zLAS

• File size: 1 – 2 GB or less (<500 MB if not rearranged)

• Keep file I/O local, avoid network

- Study area boundary included as constraint

• Airborne lidar

- Classified (bare earth, non-ground)

- Breaklines for hydro enforcement

• Terrestrial lidar

- RGB & intensity values, classified

* Also applies to photogrammetric point clouds

DTM & DSM

Creation of Raster Surfaces

Export raster surfaces from LAS Dataset“Workflow A”

• Most scalable method

• Ensures consistent surfaces for all users

• 5x – 10x data reduction, LAS files do not need to remain on line

• Recommended method for best scalability

• Test before export to define best parameters

• Ensure tiles overlap

• Lidar data may be moved to offline storage

Tool: LAS Dataset to Tiled Rasters

Download from http://links.esri.com/3dSamples

Addition of feature constraints“Workflow A”

• Constraints for Hydrology, Breaklines, Model Key points

• DTM only

Alternative – Rasters generated on-the-fly from lidar points “Workflow B”

• Fastest method to share data

• Can support alternative surfaces (e.g. buildings on DTM, minus trees)

• LAS files should remain on line*

Managed/Versioned DTM using Terrain Dataset“Workflow C”

• For versioned digital terrain model

• Model points within a geodatabase

Elevation Data Management

Source Imagery

SourceMosaic

Datasets

SRTM

LiDAR Project #N

Source Mosaic Datasets – Elevation & Lidar example

LiDAR Project #1

Additional notes:

1) Create overviews on Source Mosaics, then use SRTM (instead of overviews) to fill in “background” elevation values

2) Don’t calculate statistics – it takes too long and statistics for elevation datasets aren’t really meaningful – instead,

use Set Raster Properties to manually insert approximate statistics.

Source Imagery

SourceMosaic

Datasets

DerivedMosaic Dataset

Combine into Derived Mosaic Dataset

Use TABLE

Raster Type

Advantage: All data available in a

single location

Multi-source, multi-resolution collection of elevation data

Source Imagery

SourceMosaic

Datasets

DerivedMosaic Dataset

Orthometric Height

f

Single image service with multiple server functions

Example – ArcGIS World Elevation – Server Raster Functions

…many other

functions

Aspect

Ellipsoidal

Height

Slope

Contour

Hillshade

Source Imagery

SourceMosaic

Datasets

DerivedMosaic Dataset

Orthometric Height

f

Single image service with multiple server functions

Example – ArcGIS World Elevation – Update with new data

…many other

functions

Aspect

Ellipsoidal

Height

Slope

Contour

New data collections added to the central Derived Mosaic appear

immediately in all services

Hillshade

Lidar-derived surfaces in ArcGIS Online World Elevation Service

Demos

Support for 3D analysis

LAS / zLAS files exposed for download – ArcGIS for Server

• Server must have local storage for LAS/zLAS files

• Client = ArcGIS Desktop or custom web client

LAS / zLAS files exposed for download – Simple download (S3 / FTP)

• Simple cloud storage for LAS/zLAS files, linked to AGOL Feature Service

• Client = browser

Sharing Geoprocessing Services – Data and Tools in the CloudMove the Processing to the Data, not the Data to the Processing…

• Take advantage of storage and

computing power in the cloud or on a

private server

• Expose Geoprocessing Tools as

services

• Viewshed, Line of sight, Volume

calculations, etc.

• Accessible to Desktop, Web, and

Mobile clients

Geoprocessing

Service

Geoprocessing Services: Volume calculation

Lidar point download: Sonoma County GIS

Demos

Automated Workflows – for Repeatability & Scalability

• Simplicity

• Improve Productivity

- Repeatability, Maintainability, Scalability

- Documentation Facilitate QA & QC, Design Review

• Training/Examples

- Encapsulate best practices

- Reusable templates

Image Management Workflows – Landing pagehttp://resources.arcgis.com

• Overview of Workflows

• Guidebook

- Part of Online Doc

• ArcGIS Online Group

- Gallery of downloadable items

Resources

• Imagery Resource Center : http://esriurl.com/6005

• Image Management Workflows: http://esriurl.com/6550

• Guidebook in ArcGIS Help: http://esriurl.com/6007

• ArcGIS Online Group: http://esriurl.com/6539

• Recorded Webinar on lidar data management: http://esriurl.com/LTSLidarMgmt

• Optimized LAS tool: http://esriurl.com/zlas

• Tools from 3D Team: http://links.esri.com/3dSamples

• Contact information:

- Cody Benkelman cbenkelman@esri.com

- Lindsay Weitz lweitz@esri.com

Managing Lidar

Managing Lidar