Four decades of microwave satellite soil moisture observations: Part 1. A review of retrieval algorithms. (November 2017)

• Record Type: Journal Article
• Authors: Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.
• Is Part Of: Advances in water resources. Volume 109(2017)
• Page Start: 106
• Page End: 120
• Publication Date: 2017-11
• Subjects: Soil moisture -- Retrieval algorithm -- Passive microwave -- Active microwave -- Radiative transfer model -- Change detection model; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2017.09.006
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: Review of developments of microwave soil moisture retrieval algorithms. Passive and active microwave soil moisture retrieval algorithms are presented. Emphasis on physics based models used in the soil moisture retrieval process. Discussed current research efforts to improve individual aspects of the algorithms. Alternate retrieval methodologies have also been presented. Abstract: The satellite based passive (radiometer) and active (radar) microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Microwave retrievals require an algorithm to estimate soil moisture from satellite measurements. In this Part 1 of a two-part review series, we provide a synthesis of four decades of research and development on the passive and active microwave soil moisture retrieval algorithms. The algorithms associated with passive sensors use the radiometer brightness temperatures, while active sensors use the radar backscatter measurements to retrieve soil moisture. The physics of both algorithm classes are based on the fact that the microwave measurements at lower frequencies are influenced by the soil dielectric property, which acts as a proxy for the surface soil moisture content. In this review effort, the emphasis is laid on the physical models of the passive and the active retrieval algorithms. These algorithms facilitate to obtain the individual radiative contributions from soil, vegetation, and atmosphere that reach satellite sensors after mixing (roughness), scattering, and attenuation. In the process, we looked into the current research efforts to improve individual aspects of the algorithms, followed by a description of different retrieval procedures. In Part 2 of this review series, performance evaluation and inter-sensor comparisons of soil moisture of eight passive and two active sensors are carried out using 1058 stations along with model soil moisture data in the Contiguous United States (CONUS) region.