期刊
REMOTE SENSING
卷 6, 期 8, 页码 7683-7707出版社
MDPI
DOI: 10.3390/rs6087683
关键词
soil moisture; SAR; Envisat ASAR; change detection; Africa
类别
资金
- ESA Data User Element (DUE) Tiger Innovator Project SHARE (European Space Research Institute (ESRIN)) [19420/05/I-EC]
- ESA Data User Element (DUE) Tiger Innovator Project TIGER-NET (ESRIN) [4000105732/12/I-NB]
A surface soil moisture (SSM) product at a 1-km spatial resolution derived from the Envisat Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) mode data was evaluated over the entire African continent using coarse spatial resolution SSM acquisitions from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Noah land surface model from the Global Land Data Assimilation System (GLDAS-NOAH). The evaluation was performed in terms of relative soil moisture values (%), as well as anomalies from the seasonal cycle. Considering the high radiometric noise of the ASAR GM data, the SSM product exhibits a good ability (Pearson correlation coefficient (R) = similar to 0.6 for relative soil moisture values and root mean square difference (RMSD) = 11% when averaged to 5-km resolution) to monitor temporal soil moisture variability in regions with low to medium density vegetation and yearly rainfall >250 mm. The findings agree with previous evaluation studies performed over Australia and further strengthen the understanding of the quality of the ASAR GM SSM product and its potential for data assimilation. Problems identified in the ASAR GM algorithm over arid regions were explained by azimuthal effects. Diverse backscatter behavior over different soil types was identified. The insights gained about the quality of the data were used to establish a reliable masking of the existing ASAR GM SSM product and the identification of areas where further research is needed for the future Sentinel-1-derived SSM products.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据