Demo: Build Terrain Mesh With Footprints¶

This demo illustrates how to build a terrain mesh that conforms to building footprints.

To run the demo, type:

$ python build_terrain_mesh_with_footprints.py

Purpose¶

This demo demonstrates how to download point cloud data and building footprints from the OSM provider, process and simplify the footprints, and then build a terrain mesh with the footprints serving as subdomains. This approach allows the mesh to better conform to the building boundaries.

Step-by-step¶

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)
```
Download Data: Retrieve the point cloud and building footprints using the appropriate functions. The footprints are downloaded from the OSM provider.
```
pointcloud = dtcc.download_pointcloud(bounds=bounds)
buildings = dtcc.download_footprints(bounds=bounds, provider="OSM")
```
Process the Point Cloud: Remove global outliers from the point cloud to reduce noise.
```
pointcloud = pointcloud.remove_global_outliers(3.0)
```

Process and Simplify Footprints: Merge, simplify, and adjust the building footprints. These steps ensure that the footprints are clean and suitable for defining subdomains in the mesh.

buildings = dtcc.merge_building_footprints(buildings, max_distance=0.5,
                                           min_area=10)
buildings = dtcc.simplify_building_footprints(buildings, tolerance=0.25)
buildings = dtcc.fix_building_footprint_clearance(buildings, 0.5)

Extract Footprints: Extract the simplified footprints (using the LOD0 representation) from the processed building objects.
```
footprints = [building.lod0 for building in buildings]
```

Define Subdomain Resolutions: Set subdomain resolutions, assigning different resolutions for alternate buildings.

subdomain_resolution = [2.0] * len(footprints)
subdomain_resolution[1::2] = [0.5] * len(subdomain_resolution[1::2])

Build the Terrain Mesh: Build the terrain mesh by supplying the point cloud, the extracted footprints as subdomains, and the corresponding resolution settings. Additional parameters such as maximum mesh size, minimum mesh angle, and smoothing factor are also specified.
```
mesh = dtcc.build_terrain_mesh(
    pointcloud,
    subdomains=footprints,
    subdomain_resolution=subdomain_resolution,
    max_mesh_size=10,
    min_mesh_angle=25,
    smoothing=3,
)
```
Visualize the Mesh: Display the resulting terrain mesh using the view() method.
```
mesh.view()
```

Complete Code¶

Below is the complete code for this demo:

# This demo illustrates how to build a terrain mesh that conforms to building footprints.

import dtcc

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

# Download point cloud and footprints
pointcloud = dtcc.download_pointcloud(bounds=bounds)
buildings = dtcc.download_footprints(bounds=bounds, provider="OSM")

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

# Simplify building footprints
buildings = dtcc.merge_building_footprints(buildings, max_distance=0.5, min_area=10)
buildings = dtcc.simplify_building_footprints(buildings, tolerance=0.25)
buildings = dtcc.fix_building_footprint_clearance(buildings, 0.5)

# Extract footprints
footprints = [building.lod0 for building in buildings]

# Set subdomain resolutions to 2.0 for half of the buildings and 0.5 for the other half
subdomain_resolution = [2.0] * len(footprints)
subdomain_resolution[1::2] = [0.5] * len(subdomain_resolution[1::2])

# Build terrain mesh with footprints as subdomains
mesh = dtcc.build_terrain_mesh(
    pointcloud,
    subdomains=footprints,
    subdomain_resolution=subdomain_resolution,
    max_mesh_size=10,
    min_mesh_angle=25,
    smoothing=3,
)

# View terrain mesh
mesh.view()