Determination of tree species using ranging scatterometer data

Author

Törmä, Markus

Author_Institution

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

Volume

3

fYear

34881

fDate

10-14 Jul1995

Firstpage

2038

Abstract

This study represents a method to determine tree species using helicopter-borne ranging scatterometer called HUTSCAT. The determination is based on the form of measured forest canopy profiles. Different methods of normalizing profiles and feature extraction are presented. Classification is performed using the Bayes decision rule for minimum error. Experiments show that tree species can be detected quite reliably using the presented method

Keywords

Bayes methods; airborne radar; feature extraction; forestry; geophysical signal processing; geophysical techniques; image classification; radar imaging; remote sensing by radar; Bayes decision rule; Bayesian method; HUTSCAT; airborne radar; feature extraction; forest canopy profile; forestry; geophysical measurement technique; helicopter-borne radar; image classification; method; minimum error; normalization; radar remote sensing; ranging scatterometer; tree species identification; vegetation mapping; Backscatter; Feature extraction; Filtering; Filters; Power measurement; Radar measurements; Remote sensing; Sea measurements; Space technology; Spaceborne radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International

Conference_Location

Firenze

Print_ISBN

0-7803-2567-2

Type

conf

DOI

10.1109/IGARSS.1995.524102

Filename

524102