期刊
REMOTE SENSING OF ENVIRONMENT
卷 233, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2019.111346
关键词
Microwaves remote sensing; Satellite soil moisture; High-resolution retrievals; Constrained inverse problems; Tikhonov regularization
资金
- NASA's Science Utilization of the Soil Moisture Active-Passive (SUSMAP) Mission and Terrestrial Hydrology Program (THP) [NNX16AM12G, 80NSSC18K1528]
Remote sensing of soil moisture and vegetation water content from space often requires inversion of a zeroth-order approximation of the forward radiative transfer equation in L-band, known as the t-? model. This paper shows that the least-squares inversion of the model is not strictly convex and the widely used unconstrained damped least-squares (DLS) can lead to biased retrievals, due to preferential descending paths. In particular, the numerical experiments show that for sparse (dense) vegetation with a low (high) opacity, the DLS tends to overestimate (underestimate) the soil moisture and vegetation water content when the soil is dry (wet). A new Constrained Multi-Channel Algorithm (CMCA) is proposed that confines the retrievals with a priori information about the soil type and vegetation density and accounts for slow temporal changes of the vegetation water content through a smoothing-norm regularization. It is demonstrated that depending on the resolution of the constraints, the algorithm can lead to high-resolution soil moisture retrievals beyond the radiometric spatial resolution. Controlled numerical experiments are conducted and the results are validated against ground-based gauge observations using the passive microwave observations by the Soil Moisture Active Passive (SMAP) Satellite.
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