A new vegetation index for cooperative inversion of winter wheat covered surface soil moisture based on sentinel-1/2 remote sensing data

Author(s): B. Zhang^{1, 2, 3} ; J. Zhao^{1, 2, 3} ; N. Li^{1, 2, 3} ; Z. Guo^{1, 2, 3}
DOI: 10.1049/icp.2021.0636

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Author(s): B. Zhang^{1, 2, 3} ; J. Zhao^{1, 2, 3} ; N. Li^{1, 2, 3} ; Z. Guo^{1, 2, 3}
- Affiliations: 1: College of Computer and Information Engineering , Henan University , Kaifeng 475004 , PR China ;
  2: Henan Key Laboratory of Big Data Analysis and Processing , Henan University , Kaifeng, 475004 , PR China ;
  3: Henan Engineering Research Center of Intelligent Technology and Application , Henan University , Kaifeng, 475004 , PR China

Source:

IET International Radar Conference (IET IRC 2020),

2021

445 – 449

Conference: IET International Radar Conference (IET IRC 2020)

DOI: 10.1049/icp.2021.0636

ISBN: 978-1-83953-540-6

Location: Online Conference

Conference date: 04-06 November 2020

Format: PDF

Aiming at the problem of the interfere of winter wheat on radar backscattering coefficient in surface soil moisture inversion, a new vegetation index called Fusion Vegetation Index (FVI) is defined in this study. Based on the Multi-Spectral Imager (MSI) data of Sentinel-2, and the Synthetic Aperture Radar (SAR) data of Sentinel-1, using FVI to retrieve water content of winter wheat, combined with Water Cloud model, the interference of winter wheat in soil moisture inversion was reduced. The results show that good soil moisture retrieval results can be obtained by combining with FVI.

Inspec keywords: geophysical image processing; remote sensing by radar; soil; moisture; vegetation mapping; backscatter; synthetic aperture radar; vegetation

Subjects: Geophysical aspects of vegetation; Radar equipment, systems and applications; Other topics in Earth sciences; Optical, image and video signal processing; Geophysical techniques and equipment; Other topics in solid Earth physics; Data and information; acquisition, processing, storage and dissemination in geophysics; Soil moisture; Computer vision and image processing techniques; Geophysics computing; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research

A new vegetation index for cooperative inversion of winter wheat covered surface soil moisture based on sentinel-1/2 remote sensing data

A new vegetation index for cooperative inversion of winter wheat covered surface soil moisture based on sentinel-1/2 remote sensing data

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