模拟气候变化影响,并利用遥感和机器学习预测肯尼亚山森林生态系统未来的脆弱性
Terry Amolo Otieno1, Loventa Anyango Otieno1, Brian Rotich2
1Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Agriculture and Technology (JKUAT), P.O. Box, Nairobi, 62000 00200, Kenya.
Environmental monitoring and assessment
|May 6, 2025
概括
气候变化威胁肯尼亚山.
科学领域:
- 生态生态学 生态生态学
- 气候科学 气候科学
- 遥感 遥感 遥感 遥感
背景情况:
- 肯尼亚山森林生态系统 (MKFE) 是一个重要的生物多样性热点和水塔.
- 气候变化,以气温上升和不稳定的降雨为特征,对MKFE的生态完整性和服务构成重大威胁.
- 变化的植被模式,减少的弹性,以及对生物多样性和水资源安全的威胁,迫切需要保护规划.
研究的目的:
- 用遥感数据评估MKFE的历史植被变化.
- 预测未来的植被动态,并在气候变化情景下确定风险地区.
- 了解气候极端和森林健康之间的关系.
主要方法:
- 使用Landsat图像 (2000-2020年) 来得出植被指数 (NDVI,EVI,SAVI,BSI).使用Landsat图像 (2000-2020年) 来得出植被指数 (NDVI,EVI,SAVI,BSI).
- 从CHIRPS和ERA5数据集中提取了气候变量 (极端降水,温度).
- 采用机器学习模型 (随机森林,XGBoost,SVM) 来分析气候植物关系,并使用SSP245.5下的CMIP6数据预测未来的变化.
主要成果:
- 随机森林模型在预测植被动态方面表现出高准确度 (R2=0.82,RMSE=0.15).
- 预测显示,到2040年,森林地区的增强植被指数 (EVI) 将下降49-55%.
- 较低的山区被确定为最容易受到气候引起的植被压力的地区,降水是森林健康的关键因素.
结论:
- 迫切需要适应性管理策略,包括植树和可持续的土地利用规划.
- 政策驱动的保护工作对于减轻气候变化对MKFE的影响至关重要.
- 该研究为全球森林生态系统影响建模提供了一个可扩展的框架,并为决策者提供了可操作的见解.
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