Derivation of land-cover change data and their assimilation in ecosystem models IIB

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Context and objectives

In order to be able to characterise subtle changes in land-cover from space, the change detection procedures have to be tested and optimised towards the change phenomena and scale of interest. Second, adequate measurement techniques have to be developed to assess accurate scale-integrated ground reference data needed for the calibration of remotely sensed data.

The specific objectives are:
- Optimisation of change indicator extraction procedure from medium resolution satellite imagery for the detection of subtle land-cover changes.
- The quantification and modeling of the natural variability of LAI for three important forest communities in Flanders based on yearly-repeated monthly measurements.
- Development of a general data acquisition technique for field measurements.
- Development of a specific data-aggregation method to move from in-situ point measurements to spatial measurements. This includes also the up-scaling from community level quantitative data to complex spatial data units to be assimilated into ecosystem models.

Project outcome

Expected scientific results

Selection of optimal sampling scheme for indirect LAI measurements
- Geometrical Canopy Model and optimisation of indirect LAI measurements
- Optimisation of change detection procedures for the detection of subtle forest cover changes
- Development of a network of controlled field experiments
- Coppin P., Nackaerts K., Queen L., Carpenter W. 1999. Operational monitoring of green biomass change for forest management. Photogrammetric Enineering and Remote Sensing, 67(5): 603-612.
- Vaesen K., Nackaerts K., Muys B., Coppin P. 2000. Performance of a modified change vector analysis approach in forest change detection. Remote Sensing of Environment. In Press.
- Vaesen K., Nackaerts K., Lizarraga I., Muys B., Coppin P. 2000. Use of a Metatruth Image concept to assess forest change detection accuracy at pixel level. International Journal of Remote Sensing, In Review.
- Nackaerts K., Coppin P., Muys B., Hermy M. 1999. Sampling methodology for Leaf Area Index measurements with LAI-2000 in small forest stands. Agricultural and Forest Meteorology, 101:247-250.
- Nackaerts K., Sterckx S., Muys B., Coppin P. submitted. Fractal dimension based optimization of indirect Leaf Area Index measurements for digital change detection. Remote Sensing of Environment.
- Presentations at international congresses and symposia.
Project leader(s): KULeuven - Geomatics and Forest Engineering
Location: Region:
  • Vlaanderen

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