DocumentCode
2131580
Title
A method for monitoring mine tailings revegetation using hyperspectral remote sensing
Author
Lévesque, Josée ; Staenz, Karl
Author_Institution
Defence R&D Canada, Val-Belair, Que., Canada
Volume
1
fYear
2004
fDate
20-24 Sept. 2004
Lastpage
578
Abstract
This paper investigates the use of airborne hyperspectral remote sensing imagery in the 400-nm to 900-nm spectral range for the extraction of information suitable for monitoring mine tailings revegetation. Compact Airborne Spectrographic Imager (CASI) data were acquired over the Copper Cliff mine tailings impoundment area in the VNIR bands during the summers of 1996 and 1998, and Probe 1 data were collected in the VNIR/SWIR bands during the summer of 1999. Endmember fractions of water, lime, fresh and oxidised tailings, low and high photosynthetic vegetation were obtained using constrained linear spectral unmixing. Vegetation fraction, tailings fraction and texture of the vegetation fraction were used in a K-Mean unsupervised classification, which produced the best results using seven classes (78.13% overall accuracy) and captured the vegetation cover from dense homogenous to low density patched cover.
Keywords
mining; photosynthesis; unsupervised learning; vegetation mapping; 400 to 900 nm; AD 1996 to 1999; CASI data; Compact Airborne Spectrographic Imager; Copper Cliff mine tailings; K-Mean unsupervised classification; Ontario; Probe 1 data; USA; VNIR band; VNIR/SWIR bands; airborne hyperspectral remote sensing; constrained linear spectral unmixing; dense homogenous cover; endmember fraction; information extraction; low density patched cover; mine tailings revegetation; photosynthetic vegetation; tailings fraction; vegetation fraction texture; visible/near-infrared band; water/lime fresh-oxidised tailings; Chemical compounds; Copper; Data mining; Hyperspectral imaging; Hyperspectral sensors; Image restoration; Legislation; Probes; Remote monitoring; Vegetation mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Print_ISBN
0-7803-8742-2
Type
conf
DOI
10.1109/IGARSS.2004.1369092
Filename
1369092
Link To Document