Student information

MSc thesis topic: Counting the trees of the Netherlands with AHN

The Algemeen Hoogtebestand Nederland (AHN) is an open airborne lidar (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. Studies on urban vegetation and individual trees is done to a limited extent. The structure of Dutch forests and detection of individual trees in forest using the AHN is yet not fully explored.

ALS data is commonly used for forest management. In the Scandinavian countries, ALS is the standard tool to retrieve forest information on large scales. In the Netherlands, ALS has not yet been adopted on this scale. Several methods and algorithms for individual tree detection have been presented and could be tested on the AHN data. One of the major drawbacks of the AHN ALS data is the limited point density (10-20 pts/m2), which raises the question whether, and to what extent, forest monitoring is impossible.

WUR GRS has a UAV lidar system, Riegl RiCopter with VUX1, available since 2016 and several campaigns have been flown within the Netherlands. This detailed data, with in general higher point densities can be used to validate tree detection performed with the AHN.

Objectives

The overall objective of this thesis topic is to investigate the potential of AHN(3) data for detection of individual trees in Dutch forest stands.

  • Review literature on individual tree detection algorithms
  • Check quality and suitability of available UAV lidar data for tree identification
  • Perform tree detection on AHN data & validate results using the UAV lidar data

Literature

Requirements

  • Basic scripting skills (e.g. R, Python, MatLab) (more will be learned during the thesis)

Theme(s): Sensing & measuring