侯赛男,党国锋

• 1:西北师范大学地理与环境科学学院

摘要(Abstract)：

针对城市热岛研究中MODIS地表温度数据云覆盖像元值问题，该文构建SVR、RF和XGBoost 3种机器学习模型以实现对MODIS地表温度产品缺失像元值的最优模拟，以最优模型获得郑州市2009—2018年无缝地表温度数据；基于距离加权不透水面聚集密度，提取出郑州市逐年主要建成区范围；结合地表温度数据、建成区范围及郊区范围动态分析郑州市热岛面积及热岛强度变化。结果表明：XGBoost模型回归拟合系数为0.95,均方根误差为0.06,填补MODIS地表温度数据像元值空缺效果优于SVR和RF模型；研究期间内，郑州市每年主要建成区面积增长速率均超过8%;郑州市这10 a间地表温度的标准差呈平稳下降的趋势，中温区面积呈上升趋势，热岛强度呈下降趋势，表明了郑州市“高温化”的缓解。

关键词(KeyWords)： MODIS;城市热环境;支持向量机;随机森林;XGBoost;主要建成区;城市热岛

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41971268)

作者(Author): 侯赛男,党国锋

DOI: 10.16251/j.cnki.1009-2307.2022.09.024

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