中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
SURFACE SOIL MOISTURE RELATIONSHIP MODEL CONSTRUCTION BASED ON RANDOM FOREST METHOD

文献类型:会议论文

作者Zhao Wei2; Li Ainong2; Huang Pan2,4; He Juelin1,2; Ma Xianming2,3
出版日期2017
会议日期JUL 23-28, 2017
会议地点Fort Worth
关键词surface soil moisture random forest AMSR-E MODIS relationship model
页码2019-2022
国家TX
英文摘要Aiming to solve the limitation of coarse spatial resolution of passive microwave soil moisture product, a soil moisture relationship model based on random forest method was constructed with land surface temperature (LST), normalized difference vegetation index (NDVI), and surface albedo (ALB) from MODIS products and surface soil moisture (SSM) from AMSR-E soil moisture product in the study area at the east edge of the Tibetan Plateau. The results show better performance of the proposed compared with the commonly used purely-empirical method, with the R-2 values above 0.88 and the RMSE values lower than 0.05m(3)/m(3), respectively. It suggested that the proposed soil moisture relationship is able to capture the spatio-temporal variation of surface moisture well. There should be great potential to improve the downscaling soil moisture accuracy when the model is used in the passive microwave soil moisture downscaling scheme.
产权排序1
会议录2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
会议录出版者IEEE
会议录出版地NEW YORK
语种英语
ISSN号2153-6996
ISBN号978-1-5090-4951-6
WOS记录号WOS:000426954602034
源URL[http://ir.imde.ac.cn/handle/131551/35218]  
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Li Ainong
作者单位1.Geosciences College, Chengdu University of Technology, Chengdu, China;
2.Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China;
3.Faculty of Geosciences and Environmental Engineering, Chengdu, China
4.University of Chinese Academy of Sciences, Beijing, China;
推荐引用方式
GB/T 7714
Zhao Wei,Li Ainong,Huang Pan,et al. SURFACE SOIL MOISTURE RELATIONSHIP MODEL CONSTRUCTION BASED ON RANDOM FOREST METHOD[C]. 见:. Fort Worth. JUL 23-28, 2017.

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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