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
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5652580