Salinity and soil moisture retrieval algorithms in western Jilin Province of China using passive microwave remote sensing data

Haoyang Fu; Lingjia Gu; Ruizhi Ren

doi:10.1117/12.2186282

4 September 2015 Salinity and soil moisture retrieval algorithms in western Jilin Province of China using passive microwave remote sensing data

Haoyang Fu, Lingjia Gu, Ruizhi Ren

Author Affiliations +

Proceedings Volume 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII; 96100W (2015) https://doi.org/10.1117/12.2186282
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

Researches on soil moisture and salinity are mainly concerned in the observation of soil salinization. Passive microwave remote sensing data can reflect the dielectric properties of different land surfaces. Meanwhile, soil dielectric properties have high sensitivity to changes of soil moisture and salinity. As a result, passive microwave remote sensing data can be used for retrieval of surface soil moisture and salinity. Western Jilin Province of China was selected as the study area in this paper. By the iteration between the rough surface reflectivity calculated based on satellite data and the rough surface reflectivity calculated based on land surface model, three parameters, including surface roughness parameter, soil moisture and salinity can be retrieved simultaneously. After comparing the retrieval results to the field measurement of salinity and FY satellite soil moisture product, the experimental results show that the surface roughness parameters of the study area were concentrated in the vicinity of 0.31. The error between the average of retrieved salinity and the average of the field measurement of salinity was about 10.52g/kg. The error between the average of retrieved soil moisture and the average of FY satellite soil moisture product was approximately 0.005cm³/cm³.

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Haoyang Fu, Lingjia Gu, and Ruizhi Ren "Salinity and soil moisture retrieval algorithms in western Jilin Province of China using passive microwave remote sensing data", Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100W (4 September 2015); https://doi.org/10.1117/12.2186282

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KEYWORDS

Soil science

Dielectrics

Reflectivity

Satellites

Microwave radiation

Data modeling

Microwave remote sensing

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