DocumentCode
2942338
Title
Senescent vegetation and crop residue mapping in agricultural lands using artificial neutral networks and hyperspectral remote sensing
Author
Bannari, A. ; Chevrier, M. ; Staenz, K. ; McNairn, H.
Author_Institution
Dept. of Geogr., Ottawa Univ., Ont., Canada
Volume
7
fYear
2003
fDate
21-25 July 2003
Firstpage
4292
Abstract
This paper focuses on a comparative study between a semi empirical model, the Modified Soil Adjusted Crop Residue Index (MSACRI), and artificial neutral networks (ANN) for estimating crop residue cover on agricultural fields using hyperspectral imagery. The results indicate the ANN method is more accurate and more representative of the ground reference information than the MSACRI.
Keywords
agriculture; crops; neural nets; vegetation mapping; MSACRI; Modified Soil Adjusted Crop Residue Index; agricultural fields; agricultural lands; artificial neutral networks; crop residue mapping; hyperspectral imagery; hyperspectral remote sensing; semiempirical model; senescent vegetation; Crops; Geoscience and remote sensing; Hyperspectral imaging; Hyperspectral sensors; Intelligent networks; Protection; Remote sensing; Soil measurements; Vegetation mapping; Water conservation;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
Print_ISBN
0-7803-7929-2
Type
conf
DOI
10.1109/IGARSS.2003.1295493
Filename
1295493
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