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A monitoring framework for land use around kaolinmining areas through Landsat TM images

机译:通过Landsat TM影像对高岭土矿区周围的土地利用进行监测的框架

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摘要

Sustainable management of land requires regular acquisition of qualitative information regarding the status of its use. It is especially important to track the changes relating to the land's competitive development needs such as mining. The field-based monitoring of a mine with a wide footprint is expensive and time-consuming. Remote sensing techniques have been developed and demonstrated as cost-effective alternatives for the conventional methods of land use/land cover (LULC) monitoring. In this study, the land cover changes that occurred between the year of 2000 and 2009 in a kaolin mining and processing area in the Kutch region of India are mapped using two Landsat-5 Thematic Mapper (TM) images. For this purpose, the spectral signature of the land covers including vegetation cover and kaolin were determined and matched filtering (MF) method was applied to classify the images. The overall accuracy of the classified 2009 image was estimated for the kaolin and the vegetation cover to 89.5 and 86.0 % respectively. The change in the land use which occurred from 2000 to 2009 were quantified and analysed for both classes. This study provided a practical framework for rapid mapping of the land cover changes around open-cut kaolin mining area using freely available Landsat data.
机译:土地的可持续管理要求定期获取有关其使用状况的定性信息。跟踪与采矿等土地的竞争性发展需求相关的变化尤其重要。对具有广泛足迹的矿场进行基于现场的监视既昂贵又费时。已经开发了遥感技术,并证明了遥感技术可作为常规的土地利用/土地覆被(LULC)监测方法的经济有效替代方案。在这项研究中,使用两幅Landsat-5 Thematic Mapper(TM)图像绘制了2000年至2009年之间印度库奇地区高岭土开采和加工区发生的土地覆盖变化。为此,确定了包括植被覆盖层和高岭土在内的土地覆盖层的光谱特征,并应用了匹配滤波(MF)方法对图像进行分类。高岭土和植被覆盖度估计的2009年分类图像的整体准确度分别达到89.5%和86.0%。对这两个类别的2000年至2009年发生的土地利用变化进行了量化和分析。这项研究提供了一个实用的框架,可利用免费的Landsat数据快速绘制明挖高岭土矿区周围的土地覆盖变化。

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