A MACHINE LEARNING METHOD TO CORRECT THE TERRAIN EFFECT ON LAND SURFACE TEMPERATURE IN MOUNTAINOUS AREAS
文献类型：会议论文
| 作者 | Wei Zhao1 ; Fengping Wen1,2; Ainong Li1
|
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 会议地点 | Valencia, SPAIN |
| 关键词 | Land surface temperature terrain effect random forest MODIS |
| 页码 | 2539-2542 |
| 国家 | SPAIN |
| 英文摘要 | 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. |
| 源文献作者 | IEEE |
| 产权排序 | 1 |
| 会议录 | IEEE International Symposium on Geoscience and Remote Sensing IGARSS
 |
| 语种 | 英语 |
| ISSN号 | 2153-6996 |
| ISBN号 | 978-1-5386-7150-4 |
| WOS记录号 | WOS:000451039802163 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/24498]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 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 |
| 推荐引用方式 GB/T 7714 | Wei Zhao,Fengping Wen,Ainong Li. A MACHINE LEARNING METHOD TO CORRECT THE TERRAIN EFFECT ON LAND SURFACE TEMPERATURE IN MOUNTAINOUS AREAS[C]. 见:. Valencia, SPAIN. 2018. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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