Soil moisture retrieval under wheat crop using RISAT-1 hybrid polarimetric SAR data

Authors

  • P.K. SHARMA Indian Institute of Remote Sensing, ISRO, Dehradun, Uttarakhand–248001
  • D. KUMAR Indian Institute of Technology (ISM), Dhanbad, Jharkhand–826004
  • H. S. SRIVASTAVA Indian Institute of Remote Sensing, ISRO, Dehradun, Uttarakhand–248001
  • P. PATEL Space Applications Centre, Ahmedabad , Gujarat–380015
  • T. SIVASANKAR Indian Institute of Remote Sensing, ISRO, Dehradun, Uttarakhand–248001

DOI:

https://doi.org/10.54386/jam.v21i1.206

Keywords:

Hybrid polarimetry, m-delta decomposition, RISAT-1 SAR, soil moisture, wheat crop

Abstract

The study aims to retrieve soil moisture from RISAT-1 hybrid polarimetric SAR data. Although the use of linear polarimetric SAR data has been well understood and documented, but hybrid polarimetric SAR data is grossly under explored and under reported for this purpose. Regression analysis has been carried to develop soil moisture retrieval models and validated the same. The retrieval models have been developed from back scattering coefficients (RH & RV) and m- space decomposition parameters (even bounce, odd bounce, and volume component) generated from RISAT-1 hybrid polarimetric SAR data. A total of three models are analyzed in this work, (i) using both RH &RV, (ii) volume component, and (iii) using even bounce, odd bounce and volume component. The study results showed that the model using m- decomposition derived parameters can provide better accuracy with R2 and RMSE of 0.92 and 2.45 per cent respectively in comparison to other two models.

 

Downloads

Published

01-03-2019

How to Cite

P.K. SHARMA, D. KUMAR, H. S. SRIVASTAVA, P. PATEL, & T. SIVASANKAR. (2019). Soil moisture retrieval under wheat crop using RISAT-1 hybrid polarimetric SAR data. Journal of Agrometeorology, 21(1), 58–62. https://doi.org/10.54386/jam.v21i1.206

Issue

Vol. 21 No. 1 (2019): March

Section

Research Paper

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This is a human-readable summary of (and not a substitute for) the license. Disclaimer.

You are free to:

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material

The licensor cannot revoke these freedoms as long as you follow the license terms.

    Under the following terms:

    Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

    NonCommercial — You may not use the material for commercial purposes.

    ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

    No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

    Notices:

    You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

    No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.