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利用开源 GIS 预测印度特伦甘纳邦 Saroor Nagar 流域的未来土地利用和土地覆被变化。

Predicting the future land use and land cover changes for Saroor Nagar Watershed, Telangana, India, using open-source GIS.

机构信息

Department of Civil Engineering, National Institute of Technology, Tadepalligudem, Andhra Pradesh, India.

Department of Civil Engineering, Maturi Venkata Subba Rao Engineering College, Hyderabad, Telangana, India.

出版信息

Environ Monit Assess. 2023 Nov 20;195(12):1499. doi: 10.1007/s10661-023-12128-2.

Abstract

The dynamics of land use and land cover are profoundly affected by the growth, mobility, and demand of people. Thematic maps of land use and land cover (LULC) help planners account for conservation, concurrent uses, and land-use compressions by providing a reference for analysis, resource management, and prediction. The purpose of this research is to identify the transition of land-use changes in the Saroor Nagar Watershed between 2008 and 2014 using the Modules for Land Use Change Evaluation (MOLUSCE) plugin (MLP-ANN) model and to forecast and establish potential land-use changes for the years 2020 and 2026. To predict how these factors affected LULC from 2008 to 2014, MLP-ANN was trained with maps of DEM, slope, distance from the road, and distance to a waterbody. The projected and accurate LULC maps for 2020 have a Kappa value of 0.70 and a correctness percentage of 81.8%, indicating a high degree of accuracy. Changes in LULC are then predicted for the year 2026 using MLP-ANN, which shows a 17.4% increase in built-up area at the expense of vegetation and barren land. The results contribute to the development of sustainable plans for land use and resource management.

摘要

土地利用和土地覆盖的动态变化受到人口的增长、流动和需求的深刻影响。土地利用和土地覆盖(LULC)专题地图通过为分析、资源管理和预测提供参考,帮助规划者考虑保护、并发用途和土地利用压缩。本研究的目的是使用土地利用变化评估模块(MOLUSCE)插件(MLP-ANN)模型识别 2008 年至 2014 年萨拉尔纳加尔流域的土地利用变化,并预测和建立 2020 年和 2026 年的潜在土地利用变化。为了预测这些因素如何影响 2008 年至 2014 年的土地利用变化,MLP-ANN 接受了 DEM、坡度、道路距离和水体距离地图的训练。2020 年的预测和准确的 LULC 地图的 Kappa 值为 0.70,正确性百分比为 81.8%,表明具有很高的准确性。然后使用 MLP-ANN 预测 2026 年的土地利用变化,结果显示建成区将增加 17.4%,而植被和荒地将减少。这些结果有助于制定可持续的土地利用和资源管理计划。

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