利用遥感和地理信息系统分析印度马哈拉施特拉邦次上克里希纳盆地的十年土地利用和土地覆盖动态

Omkar Sunil Karale, B. K. Gavit, Adarsha Gopalakrishna Bhat, Vinayak Paradkar, Sweety Mukherjee, Anand Gupta
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引用次数: 0

摘要

研究目的:本研究利用遥感技术和地理信息系统 (GIS),对 2009 年至 2019 年马哈拉施特拉邦克里希纳上游流域的土地利用和土地覆盖 (LULC) 动态进行了研究,重点关注水体、植被、土壤、居民点及其变化。研究设计:该研究利用遥感和地理信息系统绘制了土地利用、土地利用的变化(2009-2019 年)图,在监督分类中使用了最大似然分类法,确定了六种土地利用类别:水体、灌木丛、森林、农田、居民点和休耕地。研究地点和时间:研究在马哈拉施特拉邦的克里希纳上游流域进行,历时十年(2009-2019 年)。研究方法:研究利用卫星遥感和地理信息系统工具绘制 LULC 地图。采用最大似然分类器对土地进行监督分类。使用地理信息系统方法分析了水体、灌木、森林、农田、定居点和休耕地的变化。结果显示结果显示,十年间,休耕地减少了 3.03%,而农田和定居点分别增长了 7.32% 和 4.3%。林木覆盖率增加了 9.85%,水体增加了 0.93%,开阔灌丛地减少了 1.77%。制度因素、更容易获得水资源以及技术和经济因素推动了这些变化。结论该研究提倡有效利用卫星遥感技术监测土地利用、土地利用变化和土地利用变化的变化,识别包括制度和技术因素在内的关键驱动因素,有助于可持续发展规划。研究结果有助于预测未来土地利用的变化,支持该地区有效的土地管理和保护战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing Decadal Land Use Land Cover Dynamics in the Sub-Upper Krishna Basin of Maharashtra, India Using Remote Sensing and GIS
Aims: This study was conducted to examine Land Use Land Cover (LULC) dynamics in Maharashtra’s sub-upper Krishna basin from 2009 to 2019 using remote sensing and geographical information system (GIS), focusing on water bodies, vegetation, soil, settlements, and their changes. Study Design: Employing remote sensing and GIS for LULC mapping (2009-2019) the study used a maximum likelihood classifier in supervised classification, identifying six land use categories: water bodies, open shrubs, forests, agricultural land, settlements, and fallow land. Place and Duration of Study: It was conducted in the sub-upper Krishna basin, Maharashtra, over ten years’ data (2009-2019). Methodology: The study utilised satellite remote sensing and GIS tools for LULC mapping. A supervised classification was applied with a maximum likelihood classifier to categorize land. The changes in water bodies, open shrubs, forests, agricultural land, settlements, and fallow land were analysed using GIS approach. Results: It was seen that, over the decade, fallow land decreased by 3.03%, while agricultural land and settlements grew by 7.32% and 4.3%, respectively. Tree cover increased by 9.85%, water bodies by 0.93%, and open scrubland decreased by 1.77%. Institutional factors, easier water access, and technological and economic factors drove these changes. Conclusion: The study advocates the effective use of satellite remote sensing to monitor LULC changes, identifying key drivers, including institutional and technological factors, contributes to sustainable development planning. The findings aid predictions for future land use changes, supporting effective land management and conservation strategies in the region.
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