使用机器学习算法解决土地使用土地覆盖面变化对土地表面温度的影响
Sajid Ullah1,2, Xiuchen Qiao3, Mohsin Abbas4
1School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai, 200237, People's Republic of China. Sajidjalwan@gmail.com.
Scientific reports
|August 13, 2024
概括
喀布尔的快速城市化显著改变了土地覆盖面,增加了建筑面积和土地表面温度 (LST). 预计这一趋势将持续下去,这突显了城市增长与气温上升之间的直接联系.
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:
- 25年来,喀布尔省的快速城市化推动了土地利用和土地覆盖 (LULC) 的重大变化.
- 了解这些LULC动态对于评估它们对城市环境的影响至关重要,特别是土地表面温度 (LST).
研究的目的:
- 评估LULC变化对1998年至2022年喀布尔省LST的影响.
- 为了预测未来的LULC和LST模式,使用细胞自动物流回归 (CA-LR) 模型对2034年和2046年进行预测.
主要方法:
- 支持矢量机 (SVM) 算法应用于Landsat卫星图像 (1998-2022) 以将LULC分为四类.
- 使用Landsat热带数据进行LST评估.
- 蜂自动物流回归 (CA-LR) 模型用于未来的LULC和LST预测.
主要成果:
- 建筑面积增加了9.37%,而裸露的土壤和植被覆盖面分别减少了7.20%和2.35% (1998-2022年).
- 建筑区的LST平均值最高,其次是裸露的土壤和植被.
- 未来的预测表明,建筑区的持续增长以及LST≥32°C的地区的显著增加.
结论:
- 在喀布尔的建筑面积增加,植被覆盖面减少和土地表面温度上升之间存在直接的相关性.
- 城市化是LST增长的主要驱动因素,需要城市规划策略来缓解热效应.
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