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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Radar vegetation indices for estimating the vegetation water content of rice and soybean

Authors
item Kim, Yihyun -
item JACKSON, THOMAS
item Bindlish, R -
item Lee, Hoonyol -
item Hong, Sukyoung -

Submitted to: Geoscience and Remote Sensing Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 10, 2012
Publication Date: June 1, 2012
Citation: Kim, Y., Jackson, T.J., Bindlish, R., Lee, H., Hong, S. 2012. Radar vegetation indices for estimating the vegetation water content of rice and soybean. Geoscience and Remote Sensing Letters. 9:564-568.

Interpretive Summary: A new remote sensing approach for retrieving vegetation water content was demonstrated for use with rice and soybeans. Vegetation water content is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. In this study, a new approach called the Radar Vegetation Index (RVI) was evaluated for estimating vegetation water content. Analysis utilized a data set obtained with a ground-based radar system during an entire growth period of rice and soybean. Prediction equations for the estimation of the biophysical variables from the RVI were developed. Results indicated that it was possible to estimate vegetation water content with an accuracy of 0.21 kg m-2. These results demonstrated that valuable new information can be extracted from current and future radar satellite systems on the vegetation condition of two globally important crop types.

Technical Abstract: Vegetation water content (VWC) is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. In this study, the Radar Vegetation Index (RVI) was evaluated for estimating VWC. Analysis utilized a data set obtained using a ground-based multi-frequency polarimetric scatterometer system during an entire growth period of rice and soybean. Temporal variations of the backscattering coefficients for L-, C-, and X-band, RVI, VWC, Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI) were analyzed. The L-band RVI was found to be correlated to different vegetation indices. Prediction equations for the estimation of the biophysical variables from the RVI were developed. The results indicated that there was a good correlation and accuracy in using RVI for estimating the vegetation biophysical parameters evaluated. It was possible to estimate VWC with an accuracy of 0.21 kg m-2 using L-band RVI observations. These results demonstrate that valuable new information can be extracted from current and future radar satellite systems on the vegetation condition of two globally important crop types.

Last Modified: 9/10/2014
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