Usage Guide¶

Overview¶

The DTCC Python module makes it simple to download, process, and view city data. In essence, you first import the module, then download or load data from files, process the data (e.g. filtering, building meshes, or computing attributes), and finally visualize or export the results. This guide will help novice users get started quickly.

Importing the Module¶

To begin using DTCC, simply import it as follows:

import dtcc

Downloading Data¶

DTCC provides functions to download various types of data such as point clouds, building footprints, and road networks. For example, to download point cloud data and building footprints for a given area, you can define the bounds and call the appropriate functions:

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

# Download point cloud and building footprints
pointcloud = dtcc.download_pointcloud(bounds=bounds)
buildings = dtcc.download_footprints(bounds=bounds)

Loading Data from File¶

In addition to downloading, DTCC allows you to load data from files. For example, to load a CityJSON file and build a city mesh, you might do the following:

from urllib.request import urlretrieve
import dtcc

# Download example CityJSON file
url = "https://3d.bk.tudelft.nl/opendata/cityjson/3dcities/v2.0/DenHaag_01.city.json"
urlretrieve(url=url, filename="city.json")

# Load city model from CityJSON file
city = dtcc.load_city("city.json")

Processing Data¶

Once the data is downloaded or loaded, you can process it. Typical processing steps include cleaning the data, filtering out outliers, and constructing geometries. For example:

# Remove global outliers from the point cloud
pointcloud = pointcloud.remove_global_outliers(3.0)

# Build a terrain raster and mesh from the point cloud
raster = dtcc.builder.build_terrain_raster(pointcloud, cell_size=5,
                                           ground_only=True)
mesh = dtcc.builder.build_terrain_mesh(raster)

# Extract roof points and compute building heights
buildings = dtcc.extract_roof_points(buildings, pointcloud)
buildings = dtcc.compute_building_heights(buildings, raster, overwrite=True)

Viewing and Exporting Data¶

After processing, DTCC makes it easy to visualize the results. Whether you are viewing a complete city model, a terrain mesh, or a point cloud, each object includes a view() method. For example:

# Create a city and add the processed buildings and terrain
city = dtcc.City()
city.add_buildings(buildings)
city.add_terrain(raster)
city.add_terrain(mesh)

# Visualize the city model
city.view()

For more detailed documentation and further examples, please refer to the API Reference and Demos.