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Remote Sensing-Based Land Use and Land Cover Change in Shalamulun Catchment

机译:莎拉木伦流域基于遥感的土地利用与土地覆盖变化

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In this study, the decision tree (DT) classification technique was used to detect the land use changes based on the spectral characteristics of the samples and the spatial patterns of the six land use classes for two landsat images for the Shalamulun river catchment of China acquired in 1987 and 2001. And post-classification change detection technique was applied to map land cover changes. For validating the classification results, detailed field data of the land cover as well as land use was recorded with the help of a mobile mapping system equipped with GPS. Changes among different land cover classes were assessed based on the information extraction technique, spatial analysis technique and mathematical statistics method, supported by GIS software. During the study period, the land cover changes were distinctly on grassland and forest. In this study, we analyzed the quantity change, spatial-temporal change and the extent of land use change in the catchment by spatial analysis and revealed the driving forces of land use and land cover change.
机译:在这项研究中,决策树(DT)分类技术用于基于样本的光谱特征和获得的中国沙拉穆伦河流域的两个陆地卫星图像的六个土地利用类别的空间格局,来检测土地利用的变化分别于1987年和2001年使用。后分类变化检测技术被应用于地图土地覆被变化。为了验证分类结果,借助配备GPS的移动制图系统,记录了土地覆盖以及土地利用的详细现场数据。在GIS软件的支持下,基于信息提取技术,空间分析技术和数理统计方法,对不同土地覆被类别之间的变化进行了评估。在研究期间,草地和森林的土地覆盖变化明显。在这项研究中,我们通过空间分析来分析流域内的数量变化,时空变化和土地利用变化的程度,并揭示了土地利用和土地覆被变化的驱动力。

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