Recent Advances in Soil Moisture Estimation from Remote Sensing

作     者：Peng, Jian Loew, Alexander 

作者机构：Ludwig Maximilians Univ Munchen Dept Geog D-80333 Munich Germany Max Planck Inst Meteorol D-20146 Hamburg Germany 

出 版 物：《WATER》 (水)

年 卷 期：2017年第9卷第7期

页      面：530-530页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 

主　　题：soil moisture remote sensing retrieval algorithms uncertainties validations applications 

摘      要：Monitoring soil moisture dynamics from local to global scales is essential for a wide range of applications. The field of remote sensing of soil moisture has expanded greatly and the first dedicated soil moisture satellite missions (SMOS, SMAP) were launched, and new missions, such as SENTINEL-1 provide long-term perspectives for land surface monitoring. This special issue aims to summarize the recent advances in soil moisture estimation from remote sensing, including recent advances in retrieval algorithms, validation, and applications of satellite-based soil moisture products. Contributions in this special issue exploit the estimation of soil moisture from both microwave remote sensing data and thermal infrared information. The validation of satellite soil moisture products can be very challenging, due to the different spatial scales of in situ measurements and satellite data. Some papers present validation studies to quantify soil moisture uncertainties. On the other hand, soil moisture downscaling schemes and new methods for soil moisture retrieval from GPS are also addressed by some contributions. Soil moisture data are used in fields like agriculture, hydrology, and climate sciences. Several studies explore the use of soil moisture data for hydrological application such as runoff prediction.