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GIS and Remote Sensing based Land Use/Land Cover Change Detection: The Case of Kility Watershed

机译:GIS和基于遥感的土地使用/陆地覆盖变更检测:凯利水域的情况

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The land cover and land use changes are caused by both, natural and anthropogenic factors. This study was conducted in kility Watershed, Amhara Region, North western Ethiopia. The objective of this study was to detect and analyse LULC changes in the watershed. The study has used ArcGIS10.3 and ERDAS IMAGINE 15, Landsat images of 1986 and 2002; Sentinel 2 image for 2019 to analyse land cover and land use changes of Kility watershed. In addition, the survey was conducted to detect the land use class and their drivers of changes. The Maximum Likelihood Algorithm of Supervised Classification has been used to generate land use and land cover maps. For the accuracy of classified Land Use/Land Cover maps, a confusion matrix was used to derive overall accuracy and results were above the minimum and acceptable threshold level. Post classification comparison change detection method was employed to identify gains and losses between Land Use/Land Cover classes. The satellite image results showed that Bush land decreased in the first period but increased in the second and the entire study periods. Grassland increased in the first period and increased in the entire periods. Agricultural land is the most converted cover type during the second study period. In the 33 years, forest lands expanded by over 8.48 % of the original forest cover what was existed at the base year. Settlement area which was not found in the first two study years satellite image result have 1.46 % proportion in 2019 Land Use/Land Cover classification.
机译:土地覆盖和土地利用变化是由天然和人为因素引起的。该研究是在埃塞俄比亚北部举行的艾哈拉地区的凯斯流域进行。本研究的目的是检测和分析流域中的LULC变化。该研究使用了ArcGIS10.3和Erdas Imagine 15,Landsat Images 1986和2002; Sentinel 2 2019年图像分析陆地覆盖和土地利用速度变化。此外,还进行了调查,以检测土地使用课程及其变更驱动因素。监督分类的最大似然算法已被用于生成土地利用和陆地覆盖地图。对于分类土地使用/陆地覆盖图的准确性,使用混淆矩阵来导出总体精度,结果高于最小和可接受的阈值水平。后分类比较变更检测方法旨在识别土地使用/陆地覆盖课程之间的收益和损失。卫星图像结果表明,丛林土地在第一时期下降,但在第二个和整个研究时期增加。草原在第一期增加,整个时期增加。农业用地是第二学习期间最具转换的封面类型。在33年内,林地扩大了8.48%的原始森林覆盖基准年份存在的内容。在前两项研究年份未发现的结算区卫星图像结果在2019年的土地使用/土地覆盖分类中具有1.46%。

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