Retrieval of Wheat Growth Parameters With Radar Vegetation Indices

Retrieval of Wheat Growth Parameters With Radar Vegetation Indices

The radar vegetation index (RVI) has low sensitivity to changes in environmental conditions and has the potential as a tool to monitor vegetation growth. In this letter, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations made w...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters Vol. 11; no. 4; pp. 808 - 812
Main Authors: Kim, Yihyun, Jackson, Thomas, Bindlish, Rajat, Hong, Sukyoung, Jung, Gunho, Lee, Kyuongdo
Format: Journal Article
Language:English
Published: Piscataway IEEE 01-04-2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Agriculture
Backscatter
Backscattering coefficients
canopy
correlation
crops
environmental factors
equations
fresh weight
L-band
linear models
Meteorology
polarimetric scatterometer
radar
Radar measurements
radar vegetation index (RVI)
Remote sensing
rice
soil water
soybeans
temporal variation
Vegetation
Vegetation mapping
vegetation types
vegetation water content (VWC)
water content
wheat
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Summary:The radar vegetation index (RVI) has low sensitivity to changes in environmental conditions and has the potential as a tool to monitor vegetation growth. In this letter, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations made with a ground-based multifrequency polarimetric scatterometer system over an entire wheat growth cycle. We analyzed the temporal variations of backscattering coefficients for L-, C-, and X-bands; 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 (root-mean-square error (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 (e.g., rice and soybean). We found that a single linear relationship between L-band 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 mission (2014), which is designed to measure global soil moisture.
Bibliography:http://handle.nal.usda.gov/10113/59881
http://dx.doi.org/10.1109/LGRS.2013.2279255
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2013.2279255