Comparison of the information content in optical and high resolution SAR images of the Amazon rain forest

Author

Lombardo, Pierfrancesco ; Rossi, Alessandro

Author_Institution

INFOCOM Dept., Rome Univ., Italy

Volume

1

fYear

2000

fDate

2000

Firstpage

411

Abstract

A new algorithm for jointly exploiting mean and texture in the segmentation of high resolution SAR images is proposed. The coincidence with the classification of the rain forest from Thematic Mapper (TM) images is demonstrated, for three classes: forest, clearings and regrowth areas. Also the ability to extract information not available in TM data is shown

Keywords

forestry; geophysical signal processing; geophysical techniques; image classification; image segmentation; image texture; radar imaging; remote sensing; remote sensing by radar; sensor fusion; synthetic aperture radar; vegetation mapping; Amazon; SAR; Thematic Mapper; algorithm; clearing; geophysical measurement technique; high resolution; image classification; image segmentation; image texture; information content; multispectral remote sensing; optical image; radar remote sensing; rain forest; regrowth area; synthetic aperture radar; tropical forest; vegetation mapping; Data mining; Fluctuations; Image resolution; Image segmentation; Layout; Pixel; Rain; Remote sensing; Satellites; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.860548

Filename

860548