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United States Department of Agriculture

Agricultural Research Service

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Retrieval of wheat growth parameters with radar vegetation indices

item Kim, Yihyun
item Jackson, Thomas
item Bindlish, R.
item Hong, Sukyoung
item Jung, G.
item Lee, Hoonyol

Submitted to: Geoscience and Remote Sensing Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/1/2014
Publication Date: 11/1/2014
Publication URL:
Citation: Kim, Y., Jackson, T.J., Bindlish, R., Hong, S., Jung, G., Lee, H. 2014. Retrieval of wheat growth parameters with radar vegetation indices. Geoscience and Remote Sensing Letters. 11:808-812.

Interpretive Summary: A relationship was established between crop growth data and an index derived from polarimetric radar observations for wheat. A time series of backscattering coefficient data and crop growth data collected using a ground based multi-frequency (L-, C-, and X-band) polarimetric radar system and field sampling during a wheat growth cycle were analyzed. The Radar Vegetation Index (RVI) for all bands increased in accordance with growth data and decreased with a reduction of vegetation water content (VWC) and fresh weight. Retrieval equations were developed for estimating VWC and fresh weight using the RVI for wheat. The results of this investigation clearly show that accurate information on VWC of wheat can be retrieved using RVI. Although the error increases, a single linear function applied to three crop types also performed well. Information on VWC and biomass is valuable in global crop assessment and yield estimation. In addition, VWC is used in retrieving soil moisture from microwave remote sensing observations. NASA's Soil Moisture Active and Passive (SMAP) mission (launch October 2014) will include an L-band radar and a radiometer.

Technical Abstract: The Radar Vegetation Index (RVI) has a low sensitivity to changes in environmental conditions and has the potential as a tool to monitor the vegetation growth. In this study, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations made with a ground-based multi-frequency polarimetric scatterometer system over an entire wheat growth cycle. We analyzed the temporal variations of backscattering coefficients for L-, C-, and X-band, RVI, vegetation water content (VWC), and fresh weight. We found that the L-band RVI was highly correlated with both VWC (r=0.98) and fresh weight (r=0.98). Based upon these analyses, linear equations were developed for estimation of VWC (RMSE=0.126 kg m-2) and fresh weight (RMSE=0.12 kg m-2). In addition, the results of the wheat study were combined with previous investigations with other crops (rice and soybean). We found that a single linear relationship between L-RVI and VWC can be used for all crop types (RMSE=0.47 kg m-2). These results clearly demonstrate the potential of RVI as a robust method for characterizing vegetation canopies. VWC is a key input requirement for retrieving soil moisture from microwave remote sensing observations. The results of this investigation will be useful for the Soil Moisture Active and Passive (SMAP) mission (2014) which is designed to measure global soil moisture.

Last Modified: 09/24/2017
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