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A MACHINE LEARNING METHOD TO CORRECT THE TERRAIN EFFECT ON LAND SURFACE TEMPERATURE IN MOUNTAINOUS AREAS
语种英语
Wei Zhao1; Fengping Wen1,2; Ainong Li1
2018
会议录名IEEE International Symposium on Geoscience and Remote Sensing IGARSS
会议录编者/会议主办者IEEE
页码2539-2542
会议名称38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议日期2018
会议地点Valencia, SPAIN
会议举办国SPAIN
产权排序1
摘要In mountainous areas, land surface temperature (LST) shows significant terrain effect, which can be directly reflected by the spatial distribution associated with the change of topographic factors (elevation, slope, and aspect). By the way, the terrain effect diminishes the impacts from the differences in surface water and heat fluxes, and influences their comparison or estimation over complex terrain. In this study, a practical way to reduce the terrain effect is proposed based on the random forest method with datasets from MODIS products, which is used to build a LST prediction model instead of the previous model developed based on some numerical model or empirical method. The results indicates that the constructed LST model shows a good performance in predicting LST with the R-2 of 0.93 and the RMSE lower than 2.0 K for four selected days. Corrected LST maps are compared with the original LST map, which presents a preliminary correction results with an obvious correction on pixels with significant terrain effect.
关键词Land surface temperature terrain effect random forest MODIS
ISBN号978-1-5386-7150-4
ISSN号2153-6996
收录类别CPCI
WOS记录号WOS:000451039802163
引用统计
文献类型会议论文
条目标识符http://ir.imde.ac.cn/handle/131551/24498
专题中国科学院水利部成都山地灾害与环境研究所
通讯作者Wei Zhao
作者单位1.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China;
2.University of Chinese Academy of Sciences, Beijing, 10049, China
第一作者单位中国科学院水利部成都山地灾害与环境研究所
通讯作者单位中国科学院水利部成都山地灾害与环境研究所
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Wei Zhao,Fengping Wen,Ainong Li. A MACHINE LEARNING METHOD TO CORRECT THE TERRAIN EFFECT ON LAND SURFACE TEMPERATURE IN MOUNTAINOUS AREAS[C]//IEEE,2018:2539-2542.
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