DocumentCode
2121988
Title
Cover type classification and biomass estimation by spectral analysis
Author
Lambert, M.-C. ; Raulier, F. ; Ung, C.H.
Author_Institution
Laurentian Forestry Centre, Natural Resources Canada, Sainte-Foy, Que., Canada
Volume
4
fYear
2002
fDate
24-28 June 2002
Firstpage
2069
Abstract
This paper was written within the context of scaling up forest attributes, especially cover type and biomass, from ground plot inventory data to near infrared aerial photos. The material used is represented by ground plots georeferenced on aerial photos. Areas of 150 by 150 m are decomposed into proportions of spectrally distinct land cover elements: shadow and sunlit. Pielou´s non-randomness index is used as a surrogate of tree spatial distribution. Cover type is predicted with 71% of accuracy by blue, red, and green bands and by Pielou´s index. Meanwhile, only the blue and green bands are significant explanatory variables of biomass with a poor accuracy. More intensive use of photo texture information should improve the biomass prediction.
Keywords
forestry; geophysical techniques; vegetation mapping; Canada; IR; Peilou index; Pielou´s non-randomness index; Quebec; biomass; forest; forestry; geophysical measurement technique; image classification; land cover type; near infrared; remote sensing; scaling; spectral analysis; vegetation mapping; visible; Biological materials; Biomass; Breast; Cities and towns; Databases; Equations; Forestry; Predictive models; Reflectivity; Spectral analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN
0-7803-7536-X
Type
conf
DOI
10.1109/IGARSS.2002.1026447
Filename
1026447
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