Thesis subject

MSc thesis topic: Urban Green Volume Index based on the AHN dataset

In an urbanizing society the importance for green in the city becomes more and more important. This thesis topic is on creating a new index or indicator of how much green there is in urban area. This proposed index is based on the (crown) volume of green and will be calculated based on the AHN pointcloud directly. Deriving a CHM first and an index based on this are possible approaches that need to be investigated and explored. The final aim is to develop the Urban Green Volume Index and compare these against other existing indices of urban greenness.

ALS | Airborne Lidar Scanning data (ALS) provides height information in XYZ points. ALS is commonly used to derive digital elevation models for larger areas as well as to extract other derivates from height information about objects. Well-known examples are digital terrain and surface modelling, hydrological derivatives or modelling and adding the third dimension (z) to geo-visualizations. ALS is also useful for modelling vegetation, for example in forest management, crop monitoring or 3D representations of urban green.

AHN | The Algemeen Hoogtebestand Nederland (AHN) is an ALS dataset that covers the whole of the Netherlands and was mainly of value for national water management. In 2014 the AHN became publicly available, free of charge, and is currently widely used in 3D modelling of buildings and other physical objects in the Netherlands. The benefit of the AHN dataset is the large spatial coverage of the ALS. On the other hand, one of the major drawbacks and challenges of the AHN ALS data is the relatively limited point density (10-20 pts/m2). This raises the question what the potential is of the AHN in the Netherlands and to what extent this dataset can be used for representing and modelling the world around us.

Exact research questions and objective will be formulated after brainstorm with the supervisor

  • Review literature on Urban Greenness measures and estimations
  • Inspect the quality and suitability of the AHN pointcloud data to represent urban green
  • Develop model to calculate Urban Green Volume Index (UGVI)
  • Apply the developed model to different Dutch cities and inspect & validate results by field visits and comparisons with other Greenness measures

Literature

Requirements

  • Scripting skills for reproducibility and scaling up of your work (Geoscripting)
  • High interest for Urban Green and its value for citizens

Theme(s): Sensing & measuring; Integrated Land Monitoring