Forest mapping from space: Enhanced satellite data processing by spectral mixture analysis and topographic corrections
The spectral reflectance of ground objects in mountainous areas is largely contaminated by second order effects which are due to topographic slope and aspect. Such topographic effects present severe problems for the consistent analysis of optical remote sensing images, in particular for satellite-based forest cover mapping. The presented study integrated a topographic correction module into a modified 5S atmospheric correction model, where targets are assumed to have lambertian reflectance characteristics. The method was successfully applied to four Landsat-TM images with large seasonal differences in solar elevation. Classification methods of increasing complexity (euclidian minimum distance, maximum likelihood and a back-propagation neural network) have then been used to produce forest maps from images which were either corrected for atmospheric effects only or for radiometric distortions due to both atmosphere and topography.
Bibliographic Reference: EUR 17702 EN (1997) 90pp., FS, free of charge
Availability: Available from the Public Relations and Publications Unit, JRC Ispra, I-21020 Ispra (IT), Fax: +39-332-785818
Record Number: 199810173 / Last updated on: 1998-02-12
Original language: en
Available languages: en