用地图绘制和监测土地使用土地覆盖的动态使用谷歌地球引擎和机器学习算法在Chattogram,孟加拉国
Jayanta Biswas1, Md Abu Jobaer1, Salman F Haque1
1Urban and Rural Planning Discipline, Khulna University, Khulna, 9208, Bangladesh.
Heliyon
|November 13, 2023
概括
查托格拉姆大都市区的土地使用土地覆盖面的变化显示出快速的城市化,建筑面积不断扩大,耕地减少. 密集的植被增加,为城市可持续性提供了积极的信号.
科学领域:
- 环境科学 环境科学
- 城市规划 城市规划
- 遥感 遥感 遥感 遥感
背景情况:
- 查托格拉姆大都市区 (CMA) 的快速城市化推动了土地使用和土地覆盖面 (LULC) 的重大变化.
- 城市扩张和计划外发展影响可持续性,气候和生物多样性.
研究的目的:
- 从2003年到2023年,监测LULC在CMA中的转化.
- 用卫星图像绘制城市扩张和自然资源枯竭的地图.
主要方法:
- 在谷歌地球引擎 (GEE) 上利用了Landsat卫星图像 (2003-2023年).
- 将LULC分为五个类别:水体,积累,赤裸的土地,密集的植被和耕地.
- 采用并比较了四种机器学习算法:随机森林,梯度树提升,分类和回归树 (CART) 和支持矢量机.
主要成果:
- 在CMA中,CART模型在LULC分类方面表现出卓越的准确性和效率.
- 分析显示,建筑面积大幅扩大,耕地减少.
- 在20年的研究期间,人们观察到密集的植被显著增加.
结论:
- 该研究强调了由于城市化而导致CMA的关键LULC转移.
- 调查结果强调了战略城市规划的必要性,以管理扩张和保护自然资源.
- 密集植被的增加表明,城市景观中的生态恢复有可能发生.
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