Demo: Build Terrain Raster¶

This demo illustrates how to build a terrain raster from a point cloud.

To run the demo, type:

$ python build_terrain_raster.py

Purpose¶

This demo demonstrates how to download a point cloud for a specified area, process the point cloud by removing global outliers, build a terrain raster from the processed data, and finally visualize the resulting raster.

Step-by-step¶

1. Define Bounds: Specify the spatial bounds for a residential area in Helsingborg by setting a height/width value (here, 2000.0 units).

   h = 2000.0
   bounds = dtcc.Bounds(319891, 6399790, 319891 + h, 6399790 + h)
   

2. Download Point Cloud: Retrieve the point cloud data (lidar) for the defined bounds using the download_pointcloud function.

   pointcloud = dtcc.download_pointcloud(bounds=bounds)
   

3. Process Data: Remove global outliers from the point cloud to filter out noise.

   pointcloud = pointcloud.remove_global_outliers(3.0)
   

4. Build Terrain Raster: Construct a terrain raster from the processed point cloud. The build_terrain_raster function uses a specified cell size to create a grid representation of the terrain.

   raster = dtcc.build_terrain_raster(pointcloud, cell_size=10)
   

5. Visualize the Raster: View the generated terrain raster using the view() method.

   raster.view()
   

Complete Code¶

Below is the complete code for this demo:

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# This demo illustrates how to build a terrain raster from a point cloud.

import dtcc

# Define bounds (a residential area in Helsingborg)
h = 2000.0
bounds = dtcc.Bounds(319891, 6399790, 319891 + h, 6399790 + h)

# Download point cloud
pointcloud = dtcc.download_pointcloud(bounds=bounds)

# Remove global outliers
pointcloud = pointcloud.remove_global_outliers(3.0)

# Build terrain raster
raster = dtcc.build_terrain_raster(pointcloud, cell_size=10)

# View terrain raster
raster.view()