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桑达尔班斯的土地利用变化和土壤盐化:基于机器学习的长期转型分析和未来预测

Uttam Kumar Mandal¹, Amit Ghosh¹, Fazlul Karim²

¹ICAR-Central Soil Salinity Research Institute, Regional Research Station, Canning Town, 743 329, India.

Environmental monitoring and assessment

|November 28, 2025

概括

印度桑达尔班的沿海土地利用显示出显著的侵蚀和积累. 定居点和水产养殖业扩大,而单一作物土地面临侵蚀风险,影响未来的土地管理.

科学领域:

环境科学环境科学
遥感遥感遥感遥感
沿海的地形形态学

背景情况:

沿海土地利用和土地覆盖 (LULC) 变化对于资源管理至关重要.
印度的Sundarbans地区对气候变化影响非常敏感.
了解LULC动态对于可持续发展和沿海性至关重要.

研究的目的:

从1973年到2022年,量化Sundarbans的LULC变化,侵蚀和积累.
分析定居点和水产养殖的扩张及其对土地利用的影响.
使用机器学习模型预测未来的LULC变化和土壤盐度.

主要方法:

卫星图像分析 (1973-2022) 用于LULC分类,侵蚀和积累.
使用天花板响应盐度指数 (CRSI) 计算土壤盐度.
应用一个细胞自动机-人工神经网络 (CA-ANN) 模型,将气候和人为因素纳入未来的预测.

主要成果:

经过49年的时间,由于侵蚀而损失了大量的土地 (478平方公里),并通过积累增加了 (408平方公里).
定居点和水产养殖面积分别增加了7倍和2.4倍;双耕面积增长了75.8%.
预计到2049年,定居点 (31.6%) 和水产养殖 (30%) 的增加,植被覆盖率下降12.6%,土壤盐度增加5%.

结论:

单一耕种的土地最容易受到侵蚀的影响,这凸显了适应性战略的必要性.
未来的LULC趋势和土壤盐度的增加对土地退化和沿海社区构成风险.
调查结果支持知情地进行土地管理规划,以提高社区应对气候变化脆弱性的抵御力.

关键词:

在CA-ANN中,它是CA-ANN.气候变化气候变化气候变化侵蚀 - 积累侵蚀 - 积累类动物类动物类动物类动物土壤盐度土壤盐度脆弱性易受伤害脆弱性

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