DocumentCode :
3352124
Title :
Detection of leafy spurge using hyper-spectral-spatial-temporal imagery
Author :
Jay, Steven C. ; Lawrence, Rick L. ; Repasky, Kevin S. ; Rew, Lisa J.
Author_Institution :
Montana State Univ., Bozeman, MT, USA
fYear :
2010
fDate :
25-30 July 2010
Firstpage :
4374
Lastpage :
4376
Abstract :
We examined the ability of hyper spectral (80 bands), spatial (0.3 m), and temporal (10 dates during the growing season) imagery to detect leafy spurge infestations and classify plant densities. Random forest classification was used for all analyses. Single date classifications were similar to the best classifications in other studies (73% to 90% overall accuracies), although with greater distinction of densities. Mulitdate classification achieved 97% accuracy over four density classes.
Keywords :
geophysical image processing; photogrammetry; vegetation mapping; hyperspectral imagery; image spectroscopy; invasive species; leafy spurge infestations; plant densities; random forest; random forest classification; spatial imagery; temporal imagery; Accuracy; Classification algorithms; Hyperspectral imaging; Sensors; Vegetation mapping; Invasive species; image spectroscopy; random forest;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
ISSN :
2153-6996
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2010.5652580
Filename :
5652580
Link To Document :
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