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

被引:1
|
作者
Vaddiraju, Shiva Chandra [1 ,2 ]
Talari, Reshma [1 ]
Bhavana, K. [2 ]
Apsana, S. [2 ]
机构
[1] Natl Inst Technol, Dept Civil Engn, Tadepalligudem, Andhra Pradesh, India
[2] Maturi Venkata Subba Rao Engn Coll, Dept Civil Engn, Hyderabad, Telangana, India
关键词
Land use land cover; QGIS; Modules for land use change evaluation; Cellular automata; Artificial neural network; Multilayer perceptron; DYNAMICS; MODELS; IMPACT;
D O I
10.1007/s10661-023-12128-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:18
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