Decadal Land Use Land Cover Change Analysis using Remote Sensing and GIS in Nagpur city of Maharashtra, India

Arti Kumari, A. Upadhyaya, S. Nagarkar, NagireddyMasthan Reddy, Rajkishor Kumar, A. K. Singh
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引用次数: 1

Abstract

An attempt has been made to analyze the LULC change pattern of Nagpur over the past decade (2010-2020) using remote sensing and GIS. In this study, the LULC map for selected years was prepared by supervised classification using a maximum likelihood algorithm from Landsat data, and accuracy assessment by confusion matrix. The results showed that there were major changes in built-up areas (17.37% expansion) and barren land (19.32% deduction). However, water bodies and forest cover decreased slightly by 0.17% and 0.76%, respectively. Overall, the acreage used for agriculture increased by 2.88% and seems to have been replaced by barren / forest areas. Overall, the LULC change detection algorithms used for classification was very effective with an overall accuracy of 78.88 and 73.30% and a kappa coefficient of 0.74 and 0.67, respectively for 2010 and 2020, considered substantial. Overall, Nagpur's land cover changes constantly due to overcrowding; water and forest bodies are adversely affected by rapid urbanization. The study concludes that previous 10 years of Nagpur LULC trend analysis will help to understand land use change pattern by line departments and take necessary actions to reduce the negative impact of land use and land cover change, as well as proper land use planning and management of the Nagpur city.
基于遥感和GIS的印度马哈拉施特拉邦那格浦尔市土地利用和土地覆盖变化年代际分析
利用遥感和GIS技术,对那格浦尔近10年(2010-2020年)土地利用价值变化规律进行了分析。本研究使用最大似然算法对Landsat数据进行监督分类,并通过混淆矩阵对准确度进行评估。结果表明:建成区(扩张17.37%)和荒地(减少19.32%)变化较大;水体和森林覆盖分别减少0.17%和0.76%。总的来说,用于农业的面积增加了2.88%,似乎已经被贫瘠/森林地区所取代。总体而言,用于分类的LULC变化检测算法非常有效,2010年和2020年的总体准确率分别为78.88和73.30%,kappa系数分别为0.74和0.67,被认为是实质性的。总体而言,由于过度拥挤,那格浦尔的土地覆盖不断变化;水和森林体受到快速城市化的不利影响。研究认为,过去10年那格浦尔土地利用变化趋势分析有助于各部门了解土地利用变化格局,采取必要措施减少土地利用和土地覆被变化的负面影响,并对那格浦尔城市进行合理的土地利用规划和管理。
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