Comparison of the potential of IRS-1C, SPOT and Landsat-TM multispectral and panchromatic data for forest area classification in Northeastern Switzerland

Author

Kellenberger, Tobias W.

Author_Institution

Remote Sensing Labs., Zurich Univ., Switzerland

Volume

2

fYear

1998

fDate

6-10 Jul 1998

Firstpage

870

Abstract

Forest area classification is a main topic in remote sensing based environmental monitoring in Switzerland. The classification methodologies previously developed use mainly operational multispectral sensor systems like SPOT or Landsat-TM. The failure of some systems in 1997 (Landsat-6 or SPOT-3) and the aging sensors have forced remote sensing users to look for alternative operational systems like IRS-1C. In this study the potential of SPOT, Landsat-TM and IRS-1C to classify a forested area at 20 to 25 m resolution in Switzerland was evaluated. Additionally some investigation about the usefulness of including the high resolution panchromatic channels in the classification process were tested

Keywords

geophysical signal processing; image classification; remote sensing; IRS-1C; Landsat-TM; Northeastern Switzerland; SPOT; forest area classification; multispectral data; panchromatic data; remote sensing based environmental monitoring; Clouds; Condition monitoring; Digital elevation models; Layout; Radiometry; Remote monitoring; Remote sensing; Satellite broadcasting; Sensor systems; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International

Conference_Location

Seattle, WA

Print_ISBN

0-7803-4403-0

Type

conf

DOI

10.1109/IGARSS.1998.699610

Filename

699610