Advanced LiDAR and airborne hyperspectral remote sensing to support forest management

Funding agency: Belgian Federal Science Policy (BELSPO), within the Research Programme for Earth Observation STEREO II

Research associate: Flore Devriendt

Promoters: Robert De Wulf, Frieke Vancoillie


Duration: 01/2010 – 10/2014


Project objectives

The focus lies on the development of objective indicators quantifying forest diversity and thereby providing usable tools supporting forest management s. l., with particular focus on monitoring aspects.  Forest diversity is defined by three components: (1) tree species composition, (2) stand diversity and (3) forest vitality and will be addressed by the joint useof the HS and LiDAR data for diversity assessment of forest areas with varying degree of complexity.  Questions to answer are:

  1. How can we optimally apply/process HS data sets in order to define objective indicators for forest diversity in terms of (1) tree species composition, (2) stand diversity and (3) forest vitality?
  2. How can we properly exploit the complementary information present in HS and LiDAR data sets in the context of forest diversity assessment?
  3. What is the added value of a RS-based procedure against a ground-based description of forest diversity?
  4. To what extent can the developed methodology be used as a (operational) tool for supporting forest management with particular focus on monitoring aspects?

Project partners

  • Geomatics Engineering Group – KULeuven (Belgium)
  • FORSIT, Research Unit – University of Ghent (UGent, Belgium)
  • Centre for Remote Sensing and Earth Observation (TAP) - Flemish Institute for Technological Research (VITO, Belgium)
  • Department of Environment and Biotechnologies - Centre de Recherche Public Gabriel Lippmann, Luxembourg
  • Remote Sensing Laboratories - University of Zurich
  • Institute for Nature and Forest Research (INBO, Belgium)

Two key publications

Van Coillie, F., Liao, W., Devriendt, F., Gautama, S., De Wulf, R., Vandekerkhove, K., “Effect of Hyperspectral Image Denoising with PCA and Total Variation on Tree Species Mapping Using Apex Data.” South-eastern European Journal of Earth Observation and Geomatics. Ed. Loannis Gitas et al. Vol. 3. 2014. 281–286.

Van Coillie, F., Devriendt, F., Verbeke, L., De Wulf, R. “Directional Local Filtering for Stand Density Estimation in Closed Forest Canopies Using VHR Optical and LiDAR Data.” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 10.4 (2013): 913–917.