Lidar 2018Tree Canopy Density and Height Analysis

Qian Song

HARC

Data: 2014 TCEQ

LAS Point Classification

1 Processed, but unclassified

2 Bare-earth Ground

3 Low Vegetation (0.01m to 1.00m)

4 Medium Vegetation (1.01m to 3.00m)

6 Building

7 Low Point (noise)

9 Water

10 Ignored Ground

14 Culverts

17 Bridge Decks

5 High Vegetation (greater than 3.01m)

Image: https://environment.arlingtonva.us

Tree CanopyDensity

Tree Density - Methodology

1. Divide the study area into many small equal-sized units (Raster Dataset)

2. In each raster cell,

Density =The Number of Above Ground Points

The Total Number of Points

Tree Canopy Density =The Number of High Vegetation Points

The Number of High Vegetation Points + The Ground Points

Tree Density - Workflow

Las DatasetTree Canopy

Density Raster

Total Points Raster

Above Ground Points Raster

Las Point Statistics As Raster (Point Count)

Divide

Tips

• Convert any resulting NoData cells to 0

• Make sure one raster to be floating point to get floating-point output

Las Dataset Layer(Total)

Las Dataset Layer(Above Ground)

Tree Density - Results

Tree Density - Results

Tree CanopyHeight

Tree Height - Methodology

Digital Surface Model(DSM): the first return surface

First return of the High Vegetation Class

Digital Elevation Model(DEM): the bare earth surface

Canopy Height = DSM - DEM

Tree Height - Workflow

Las Dataset

Las Dataset to Raster DSM

DEM

Minus Tree Height

Las Dataset Layer(Above Ground &

First Return)

Tree Height - Results

Tree Height - Results

Houston Advanced Research Center (HARC)

Wrap Up

• Tree Canopy Density and Height Processes and Results

• Other applications

– Flood Inundation Depth and Area

HARCresearch.org

HARC (härk), n.

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Qian Songqsong@harcresearch.org

281-364-6085