LiDAR and GIS: Classification and Feature Extraction · 2020. 7. 2. · Agenda •LiDAR basics...

LiDAR and GIS:Classification and Feature ExtractionNicholas M. Giner – Esri

Agenda

• LiDAR basics

• Data formats and management

• The LAS dataset

• Classifying LiDAR

• Feature extraction from LiDAR

- Building footprints / 3D buildings

- Trees

- Traffic lights using machine learning

LiDAR basics• LiDAR – Light Detection and Ranging

- Optical remote sensing technique using laser light to densely sample the Earth’s surface, producing a point cloud of highly accurate x,y,zmeasurements

• Types of point clouds- Airborne scanned-based LiDAR

- Mobile / Tripod-based LiDAR

- Photogrammetric / Drone-based LiDAR

• LiDAR point cloud attributes- x,y,z measurements

- Intensity

- Return number

- Class code

- RGB

- Overlaps

Data formats and management• Formats

- LAS / zLAS / LAZ

• Management

LAS Dataset

Mosaic Dataset

Terrain Dataset

Point Cloud Scene Layer

Demo #1Explore a LAS file, Create a LAS Dataset

The LAS Dataset• LAS Dataset

- “Container” for storing reference to many LAS/zLAS files on disk

- Pointer to the original LAS/zLAS files

- Quick to create, small in file size, easy to update with additional LAS/zLAS files

- Can reference surface constraints (breaklines / boundaries)

- Quick display of LAS/zLAS data as point clouds or a dynamic TIN in 2D or 3D

- Excellent for QA/QC of LiDAR coverage (point density/spatial extent)

- Basis for generated products such as DEMs and DSMs or TINs

Working with LiDAR - GeoprocessingData Management (6) 3D Analyst (18) Conversion (2)

Classifying LiDAR• Automated classification (Geoprocessing)

- Change Class Codes

- Classify Buildings

- Classify Ground

- Classify Noise

- Classify Overlap

- Classify by Height

- Classify by 3D Proximity

- Classify by 2D Proximity (using features)

- Classify using raster

• Interactive classification (Manual)

• Editing considerations

Workflow: Classifying LiDAR

Unclassified LAS

Classify LASOverlap

Create LASDataset

Classify LASNoise

Classify LASGround

Create DEMClassify LASBuildings

Classify LASby Height (Vegetation)

Colorize LAS

ClassifiedLAS Dataset

Interactivelyedit class codes

Demo #2Classify LAS data

Other tools for classification• Change LAS Class Codes

- Reassigns classification codes from one class to another

Other tools for classification• Classify by 2D and 3D Proximity (vector)

Set LAS Class Codes using Features (2D) Locate LAS Points by Proximity (3D)

Other tools for classification• Classify using raster

- Requires integer raster with pixel values representing ASPRS LiDAR class codes

Workflow: Extract building footprints

Classified LAS Dataset

Make LAS Dataset LayerClass Code = 6

LAS Point Statistics as RasterMost Frequent Class

Elevation VoidFill (Optional)

Raster to PolygonNo Simplify

SQL(Remove

small polygons)

EliminatePolygon Part(Fill holes)

Raw buildingpolygons

RegularizeBuildingFootprints

Clean up(Optional)

Building Footprints

Workflow: Extract traffic lights

Point CNNClassified LAS Dataset

LAS to Multipoint

Explode multipoints

Reduce datasetsize

DBSCANCluster boundariesAdd fields

Remove noisepoints

Calculatefields

Clean up noise polygons

Final outputpoints

Demo #3Feature extraction: Building footprints, trees, traffic lights

Print Your Certificate of Attendance

Print Stations Located in 150 Concourse Lobby

Tuesday12:30 pm – 6:30 pmExpoHall B

5:15 pm – 6:30 pmExpo SocialHall B

Wednesday10:45 am – 5:15 pmExpoHall B

6:30 pm – 9:30 pmNetworking ReceptionSmithsonian National Museumof Natural History

Download the EsriEvents app and find

your event

Select the session you attended

Scroll down to “Survey”Log in to access the

surveyComplete the survey and select “Submit”

Please Share Your Feedback in the App