Semantic segmentation of the AHN dataset with the Random Forest Classifier

Three-dimensional (3D) city models are of great significance and are high in demand. They can be used for various useful applications such as urban planning, visibility analysis and estimating the solar irradiation and energy demand of buildings throughout the day. Nowadays, Light Detection And Ranging (LiDAR) sensors are one of the most...

Simplification of Massive TINs with the Streaming Geometries Paradigm

The volume and density of geospatial data is constantly increasing as newer acquisition techniques are developed to create higher-resolution datasets and more countries are creating country-wide datasets such as point clouds. However, methods to deal with this increase in the amount of data are lagging behind and the developments in computer...

Inferring roof semantics for more accurate solar potential assessment

In guiding the energy transition efforts towards renewable energy sources, 3D city models were shown to be useful tools when assessing the annual solar energy generation potential of urban landscapes. However, the simplified roof geometry included in these 3D city models and the lack of additional semantic information about the buildings'...

Automatic identification of water courses from AHN3 in flat and engineered landscapes

The Netherlands is characterised by mostly low lying, flat, and engineered agricultural lands, which are sensitive to flooding. To protect against floods, a correct network characterisation is of the utmost importance. A Dutch water resources management company, the HDSR, wishes to have a highly automated method to characterise the water course...