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A METHOD FOR MONITORING MINE TAILINGS RE-VEGETATION USING HYPERSPECTRAL REMOTE SENSING

机译:一种使用高光谱遥感监测矿山尾矿重新植被的方法

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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.
机译:本文调查了在400nmn至900nm的光谱范围内使用空中高光谱遥感图像,以提取适用于监测矿山尾矿重新植被的信息。 在1996年和1998年夏季的VNIR乐队中的铜悬崖矿尾矿污染物上获得了紧凑的空气光谱成像仪(CASI)数据,并在1999年夏季在VNIR / SWIR乐队中收集了探针1数据。Endmember分数 使用受约束的线性光谱解密获得水,石灰,新鲜和氧化尾矿,低和高光合植被。 植被级分,尾矿分数和植被级别的质地均用于k均无知的分类,其使用七级(78.13%的总体精度)产生了最佳结果,并将植被覆盖从致密的均匀覆盖覆盖覆盖。

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