Geospatial Applications in Land Use/Land Cover Change Detection for Sustainable Regional Development: The Case of Central Haryana, India

Surender Kumar, Ripudaman Singh
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引用次数: 4

Abstract

Timely and accurate detection of land use/land cover (LULC) change is im‐ portant for the macro and micro level sustainable development of any region. For this purpose, geospatial techniques are the best tool for change analysis as they supply timely, cheaper, precise and up to date information. This paper examines the spatial temporal change trend in LULC in the case of Central Haryana. Landsat 2, 3, 5, 7 and 8 images for the years 1975–2020 for pre‐ and post‐monsoon periods were analyzed for the study. Radiometric correction was performed to derive better information. ArcGIS 10.2 and ENVI 5.3 are used for thematic layout and thematic change preparation. An unsupervised clas‐ sification using ERDAS IMAGINE 2015 has also been done to classify study area in eight classes. The year 1975 is considered as the base year for change detection analysis. Results showed an increasing trend for the land use classes of built‐up, water body, and agricultural land without waterlogging in the pre‐ and post‐monsoon periods between 1975 and 2020. Remaining land use classes of agriculture with waterlogging, open waterlogged area, vegetation and fal‐ low land/sand dunes decreased during the same period. Increased human ac‐ tivities have changed the LULC in the region and have had a great impact on its sustainable regional development.
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地理空间应用于可持续区域发展的土地利用/土地覆盖变化检测:以印度哈里亚纳邦中部为例
及时准确地检测土地利用/土地覆盖变化对任何地区的宏观和微观可持续发展都至关重要。为此,地理空间技术是进行变化分析的最佳工具,因为它们提供了及时、廉价、准确和最新的信息。本文研究了哈里亚纳邦中部LULC的时空变化趋势。分析了1975-2020年季风前后的陆地卫星2、3、5、7和8的图像。为了获得更好的信息,进行了辐射校正。ArcGIS 10.2和ENVI 5.3用于专题布局和专题变更准备。还使用ERDAS IMAGINE 2015进行了无监督分类,将研究区域分为八类。1975年被认为是变化检测分析的基准年。结果显示,在1975年至2020年的季风前后,建筑用地、水体用地和无内涝农业用地的土地利用类别呈上升趋势。同期,有内涝、开阔积水区、植被和洼地/沙丘的农业剩余土地利用类别减少。人类活动的增加改变了该地区的LULC,并对其可持续区域发展产生了巨大影响。
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来源期刊
Geomatics and Environmental Engineering
Geomatics and Environmental Engineering Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
2.30
自引率
0.00%
发文量
27
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