Spatial Soil Moisture Prediction Model Over an Agricultural Land

Part of the Studies in Big Data book series (SBD, volume 72)


Satellite remote sensing observations have the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from active/passive microwave remote sensing data are typically complex due to inherent difficulty in characterizing interactions among land surface parameters that contribute to the retrieval process. Therefore, adequate physical mathematical descriptions of microwave backscatter interaction with parameters such as land cover, vegetation density, and soil characteristics are not readily available. In such condition, non-parametric models could be used as a possible alternative for better understanding the impact of variables in the retrieval process and relating it in the absence of exact formulation. The following chapter will provide a conceptual framework for SMPM: A non-parametric approach over an agriculture land.


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© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Geomatics Section, Civil Engineering DepartmentIndian Institute of Technology RoorkeeRoorkeeIndia
  2. 2.Surveying and Geomatics Section, Civil Engineering DepartmentMaharishi Markandeshwar UniversityAmbalaIndia
  3. 3.Indian Institute of Remote Sensing (IIRS)DehradunIndia

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