Predicting Forest Stand Height and Canopy Cover
from LANDSAT and LIDAR Data Using Data Mining Techniques
Saso Dzeroski
Department of Knowledge Technologies
Jozef Stefan Institute
Ljubljana, Slovenia
http://www-ai.ijs.si/SasoDzeroski/SasoDzeroski.html
The motivation for this study was to use data-mining techniques to improve the
consistency, accuracy, and spatial resolution of supporting
information for the forest monitoring system in Slovenia. Specifically, we aim
to generate raster maps with 25m horizontal resolution of forest stand height
and canopy cover for the Kras region of Slovenia. To this end, we learn
predictive models based on multi-temporal
Landsat ETM+ data, calibrated by data on forest stand height and canopy cover
extracted from high-resolution airborne laser scanning
data. Visual inspection of the resulting maps by a forestry expert showed that
they corresponded to the actual forest cover in the Kras
region, both in terms of forest stand height and canopy cover.
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Date: Thurs, May 25 |
Time: 4:15-5:30PM |
Place: Cordura Hall, Rm 100 |
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