Forest assessment from satellite data by use of genetic algorithms


Coskun H., Oztopal A., Sen Z.

20th Annual Symposium of the European-Association-of-Remote-Sensing-Laboratories (EARSeL), Dresden, Germany, 14 - 16 June 2000, pp.33-38 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Dresden
  • Country: Germany
  • Page Numbers: pp.33-38

Abstract

In this study genetic algorithm model investigated for the forest parameters using satellite data which are used for Landsat-TM classified images for forest stand type map. Aim of the main project was stand type mapping of a selected forest area near Istanbul with remote sensing techniques.. Forest stands parameters (tree species, mean diameter, stand density, stand volume) and the multispectral digital data were obtained in the same year with the TM data. Genetic algorithm model is used to examine the relationship between the two data sets that mean reflectance and forest parameters are analysed. A genetic algorithm model has been developed from classified final imagery for stand parameter measurement and the reflectance values of each band, for which genetic algorithm were applied, are in good agreement.