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使用随机森林回归模型和地理信息系统预测突然洪水易感性绘制
Mohamed Wahba1, Radwa Essam2, Mustafa El-Rawy3,4
1Civil Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
Heliyon
|July 29, 2024
概括
这项研究使用随机森林模型和11个环境因素预测了日本的洪水易感性. 由此产生的地图突出显示了洪水风险低至高的地区,有助于防灾准备和空间规划.
科学领域:
- 环境科学 环境科学
- 地理信息系统 (GIS) 是指地理信息系统.
- 气候变化研究 气候变化研究
背景情况:
- 由于气候变化,突然洪水正在增加,影响社区和环境管理.
- 准确地绘制洪水易受性的地图对于有效的灾害减缓和城市规划至关重要.
研究的目的:
- 为日本伊巴拉基县制定洪水易感性地图 (FSM).
- 通过先进的建模技术,调查和预测易受洪水影响的地区.
主要方法:
- 使用与GIS集成的随机森林 (RF) 回归模型.
- 包含了11个环境变量 (例如,海拔,坡度,土地覆盖面,水体和道路的距离).
- 使用接收器操作特征 (ROC) 曲线分析验证了该模型,其中有224个洪水/非洪水实例.
主要成果:
- FSM显示,伊巴拉基县大约三分之二的洪水易感度低至非常低.
- 大约五分之一的地区被确定为高至非常高的洪水易感性.
- 射频模型表现出高精度,ROC曲线下的面积 (AUC) 为99.56%.
结论:
- 开发的FSM是伊巴拉基县政策制定者的重要工具.
- 该地图支持知情地进行空间规划,并实施有针对性的洪水减缓战略.
- 这项研究有助于气候变化适应和可持续土地管理实践.
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