Kamaraj Manikandan, Rangarajan Sathyanathan
Department of Civil Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Kanchipuram, 603 203, Chennai, TN, India.
Environ Sci Pollut Res Int. 2022 Dec;29(57):86337-86348. doi: 10.1007/s11356-021-17904-6. Epub 2022 Feb 3.
Human population growth, movement, and demand have a substantial impact on land use and land cover dynamics. Thematic maps of land use and land cover (LULC) serve as a reference for scrutinizing, source administration, and forecasting, making it easier to establish plans that balance preservation, competing uses, and growth compressions. This study aims to identify the changeover of land-use changes in the Bhavani basin for the two periods 2005 and 2015 and to forecast and establish potential land-use changes in the years 2025 and 2030 by using QGIS 2.18.24 version MOLUSCE plugin (MLP-ANN) model. The five criteria, such as DEM, slope, aspect, distance from the road, and distance from builtup, are used as spatial variable maps in the processes of learning in MLP-ANN to predict their influences on LULC between 2005 and 2010. It was found that DEM, distance from the road, and distance from the builtup have significant effects. The projected and accurate LULC maps for 2015 indicate a good level of accuracy, with an overall Kappa value of 0.69 and a percentage of the correctness of 76.28%. MLP-ANN is then used to forecast changes in LULC for the years 2025 and 2030, which shows a significant rise in cropland and builtup areas, by 20 km and 10 km, respectively. The findings assist farmers and policymakers in developing optimal land use plans and better management techniques for the long-term development of natural resources.
人口增长、迁移和需求对土地利用和土地覆盖动态有着重大影响。土地利用和土地覆盖（LULC）专题地图是审查、资源管理和预测的参考依据，有助于制定平衡保护、竞争性用途和增长压力的规划。本研究旨在确定巴瓦尼河流域2005年至2015年两个时期土地利用变化的转变情况，并通过使用QGIS 2.18.24版本的MOLUSCE插件（MLP-ANN）模型预测和确定2025年和2030年潜在的土地利用变化。数字高程模型（DEM）、坡度、坡向、距道路距离和距建成区距离这五个标准被用作MLP-ANN学习过程中的空间变量地图，以预测它们在2005年至2010年期间对LULC的影响。研究发现，DEM、距道路距离和距建成区距离有显著影响。2015年的预测LULC地图和精确LULC地图显示出较高的准确性，总体卡帕值为0.69，正确率为76.28%。然后使用MLP-ANN预测2025年和2030年LULC的变化，结果显示农田和建成区面积将分别显著增加20平方公里和10平方公里。这些研究结果有助于农民和政策制定者制定优化的土地利用规划和更好的管理技术，以促进自然资源的长期发展。
