Abstract
This article presents an analysis of the scattering measurements for an entire wheat growth cycle by ground-based scatterometers at a frequency of 5.3 GHz. Since wheat ears are related to wheat growth and yield, the radar backscatter of wheat was analyzed at two different periods, i.e., with and without wheat ears. Simultaneously, parameters such as wheat and soil characteristics as well as volume scattering and soil scattering were analyzed for the two periods during the entire growth cycle. Wheat ears have been demonstrated to have a great influence on radar backscatter; therefore, a modified version of water-cloud model used for retrieving biomass should consider the effect of wheat ears. This work presents two retrieval models based on the water-cloud model and adopts the advanced integral equation model to simulate the soil backscatter before the heading stage and the backscatter from the layer under wheat ears after the heading stage. The research results showed that the biomass retrieved from the advanced synthetic aperture radar (ASAR) images to agree well with the data measured <italic<in situ</italic< after setting the modified water-cloud model for the growth stages with ears. Furthermore, it was concluded that wheat ears should form an essential component of theoretical modeling as they influence the final yield.
Highlights
Microwave remote sensing has been a popular tool because of the distinct benefits such as retrieval of vegetation information, penetrability, and availability in all weathers
advanced integral equation model25 (AIEM) can be used to simulate the backscatter of the “water layer,” and the total backscatter could be obtained
When the modified water-cloud models were applied to retrieve biomass, the backscattering coefficients extracted from the advanced synthetic aperture radar (ASAR) images could output the biomass maps at the two acquisition times
Summary
Microwave remote sensing has been a popular tool because of the distinct benefits such as retrieval of vegetation information, penetrability, and availability in all weathers. Analyzing the radar backscatter characteristics of wheat has become an active research field in recent years.[1,2] Further, backscatter modeling of wheat and biomass retrieval from SAR images has been attributed great attention by the researchers.[3,4,5,6]. Scatterometers have been used to measure and analyze vegetation scattering characteristic because of their associated ease of use.[7,8] Yihyun et al.[9] analyzed the capacity of radar vegetation indices for monitoring wheat growth cycles at P-, L-, and C-bands. Stiles et al.[12] studied the wheat measurements and modeled backscatter of wheat He et al.[13] modeled wheat radar backscatter by adapting Michigan microwave canopy scattering model (MIMICS). A greater number of satellites launched in recent years have resulted in increased availability of valuable synthetic aperture radar (SAR) images that can Journal of Applied Remote Sensing
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