In this workshop we are going to walk you through the details of the 3D BAG data set, which is a collection of 3D building models at multiple levels of detail for the Netherlands. See https://3dbag.nl. We will introduce the data set, discussing the data model, available formats, data quality and some of the peculiarities. In the hands-on part of the session, we will show how you can make the most out of the data by using Python, whether you integrate with other services or use it directly for analysis. In this part we will focus on CityJSON (http://www.cityjson.org) and cjio (https://github.com/cityjson/cjio), but we will also show other tools that can be helpful for working with the data.
Python version: 3.6 or above. We used Python 3.8 for developing these materials.
Probably the easiest if you install the dependencies with conda
. See how to install conda
Create a new conda environment and set install the dependencies from the environment.yml
file.
conda env create --name foss4gnl_3dbag --file environment.yml
You can also set up everything if you cannot or don't want to use conda. In this case, install the dependencies manually with pip
. The dependencies are listed in the environment.yml
file.