Paper Info
Title
A Method For Monitoring Mine Tailings Re-Vegetation Using Hyperspectral Remote Sensing
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 re-vegetation. 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.
Year
Venue
Keywords
2004
IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET
copper,photosynthesis,unsupervised learning,mining,k means
Field
DocType
ISSN
Soil science,Endmember,VNIR,Vegetation,Lime,Computer science,Remote sensing,Revegetation,Hyperspectral imaging,Tailings,Low density
Conference
2153-6996
Citations 
PageRank 
References 
2
0.65
1
Authors
2
Name
Order
Citations
PageRank
Josée Lévesque1155.20
Karl Staenz211523.05