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Remote Sens. 2018, 10(11), 1776; https://doi.org/10.3390/rs10111776 (registering DOI)

Analysis of the Radar Vegetation Index and Potential Improvements

1
German Aerospace Center, Microwaves and Radar Institute, P.O. Box 1116, 82234 Wessling, Germany
2
Bayreuth Center for Ecology and Environmental Research, University of Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany
3
German Aerospace Center, Institute of Data Science, Mälzerstraße 3, 07745 Jena, Germany
4
Cesbio, 18 avenue Edouard Belin, 31401 Toulouse, France
5
E.I Purpan, 75 voie du TOEC, BP57611, 31076 Toulouse CEDEX 3, France
6
INRA, Centre de Bordeaux Aquitaine, 71 avenue E. Bourlaux, 33882 Villenave d’Ornon CEDEX, France
7
Image Processing Lab, Parc Cientific, University of Valencia, 46980 Paterna Valencia, Spain
8
Department of Civil and Environmental Engineering, MIT, Vassar Street 15, Cambridge, MA 02139, USA
*
Author to whom correspondence should be addressed.
Received: 7 October 2018 / Revised: 1 November 2018 / Accepted: 7 November 2018 / Published: 9 November 2018
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Abstract

The Radar Vegetation Index (RVI) is a well-established microwave metric of vegetation cover. The index utilizes measured linear scattering intensities from co- and cross-polarization and is normalized to ideally range from 0 to 1, increasing with vegetation cover. At long wavelengths (L-band) microwave scattering does not only contain information coming from vegetation scattering, but also from soil scattering (moisture & roughness) and therefore the standard formulation of RVI needs to be revised. Using global level SMAP L-band radar data, we illustrate that RVI runs up to 1.2, due to the pre-factor in the standard formulation not being adjusted to the scattering mechanisms at these low frequencies. Improvements on the RVI are subsequently proposed to obtain a normalized value range, to remove soil scattering influences as well as to mask out regions with dominant soil scattering at L-band (sparse or no vegetation cover). Two purely vegetation-based RVIs (called RVII and RVIII), are obtained by subtracting a forward modeled, attenuated soil scattering contribution from the measured backscattering intensities. Active and passive microwave information is used jointly to obtain the scattering contribution of the soil, using a physics-based multi-sensor approach; simulations from a particle model for polarimetric vegetation backscattering are utilized to calculate vegetation-based RVI-values without any soil scattering contribution. Results show that, due to the pre-factor in the standard formulation of RVI the index runs up to 1.2, atypical for an index normally ranging between zero and one. Correlation analysis between the improved radar vegetation indices (standard RVI and the indices with potential improvements RVII and RVIII) are used to evaluate the degree of independence of the indices from surface roughness and soil moisture contributions. The improved indices RVII and RVIII show reduced dependence on soil roughness and soil moisture. All RVI-indices examined indicate a coupled correlation to vegetation water content (plant moisture) as well as leaf area index (plant structure) and no single dependency, as often assumed. These results might improve the use of polarimetric radar signatures for mapping global vegetation. View Full-Text
Keywords: microwaves; radiometer; radar; vegetation index; soil scattering; roughness; soil moisture; SMAP; SMOS microwaves; radiometer; radar; vegetation index; soil scattering; roughness; soil moisture; SMAP; SMOS
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Szigarski, C.; Jagdhuber, T.; Baur, M.; Thiel, C.; Parrens, M.; Wigneron, J.-P.; Piles, M.; Entekhabi, D. Analysis of the Radar Vegetation Index and Potential Improvements. Remote Sens. 2018, 10, 1776.

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