Using vegetation indices for soil-moisture retrievals from passive microwave radiometry

Author:

Burke E.J.,Shuttleworth W.J.,French A.N.

Abstract

Abstract. Surface soil moisture and the nature of the overlying vegetation both influence microwave emission from land surfaces significantly. One widely discussed but underused method for allowing for the effect of vegetation on soil-moisture retrievals from microwave observations is to use remotely sensed vegetation indices. This paper explores the potential for using the Normalised Difference Vegetation Index (NDVI) in soil-moisture retrievals from L-band (1.4 GHz) aircraft data gathered during the Southern Great Plains '97 (SGP97) experiment. A simplified version of MICRO-SWEAT, a soil vegetation atmosphere transfer (SVAT) scheme coupled with a microwave emission model, was used as the retrieval algorithm. Estimates of the optical depth of the vegetation, the parameter that describes the effect of the vegetation on microwave emission, were obtained by calibrating this retrieval algorithm against measurements of soil moisture at 15 field sites. A significant relationship was found between the optical depth so obtained and the observed NDVI at these sites, although this relationship changed with the resolution of the microwave brightness temperature observations used. Soil-moisture estimates made with the retrieval algorithm using the empirical relationship between optical depth and NDVI applied at two additional sites not used in the calibration show good agreement with field measurements. Keywords: NDVI, soil moisture, passive microwave, SGP97

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences,General Engineering,General Environmental Science

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Time-variant error characterization of SMAP and ASCAT soil moisture using Triple Collocation Analysis;Remote Sensing of Environment;2021-04

2. A Coupling Model for Soil Moisture Retrieval in Sparse Vegetation Covered Areas Based on Microwave and Optical Remote Sensing Data;IEEE Transactions on Geoscience and Remote Sensing;2018-12

3. Sensitivity of GNSS-R Spaceborne Observations to Soil Moisture and Vegetation;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2016-10

4. Can we measure vegetation water content and vegetation opacity at L-band with a single GPS receiver?;2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS);2016-07

5. Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data;ISPRS Journal of Photogrammetry and Remote Sensing;2014-05

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