The extraction of tree species information of forest stands using satellite images

Author

Törmä, Markus

Author_Institution

Inst. of Photogrammetry & Remote Sensing, Helsinki Univ. of Technol., Espoo, Finland

Volume

1

fYear

2000

fDate

2000

Firstpage

438

Abstract

Two different estimation methods to estimate the tree species proportions of forest stands were compared using ERS-1/2 and Landsat TM images as test data. Overall, the estimation method based on the pixelwise classification performed better than neural network method because the differences between the results acquired with training and test sets were smaller. The best results were got using dataset computed from ERS intensity (texture information) and coherence images. The results which were got using TM-image taken during summer 1994 were little bit worse

Keywords

forestry; geophysical techniques; remote sensing; remote sensing by radar; spaceborne radar; synthetic aperture radar; vegetation mapping; ERS; Landsat TM; SAR; coherence image; forest; forestry; geophysical measurement technique; image classification; multispectral remote sensing; pixelwise classification; radar remote sensing; satellite remote sensing; texture; tree species; vegetation mapping; visible; Area measurement; Data mining; Feature extraction; Monitoring; Neural networks; Performance evaluation; Remote sensing; Satellites; Testing; Volume measurement;

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.2000.860557

Filename

860557