Abstract
This article compares the performance of four different interferometric synthetic aperture radar (SAR) techniques for the estimation of rice crop height by means of bistatic TanDEM-X data. Methods based on the interferometric phase alone, on the coherence amplitude alone, on the complex coherence value, and on polarimetric SAR interferometry (PolInSAR) are analyzed. Validation is conducted with reference data acquired over rice fields in Spain during the Science Phase of the TanDEM-X mission. Single- and dual-polarized data are exploited to also provide further insights into the polarization influence on these approaches. Vegetation height estimates from methodologies based on the interferometric phase show a general underestimation for the HH channel (with a bias that reaches around 25 cm in mid-July for some fields), whereas the VV channel is strongly influenced by noisy phases, especially at large incidences [root-mean-square error (RMSE) = 31 cm]. Results show that these approaches perform better at shallower incidences than the methodologies based on coherence amplitude and on PolInSAR, which obtain the most suitable results at steep incidences, with RMSE values of 17 and 23 cm. On the contrary, at shallower incidences, they are highly affected by very low input coherence levels. Hence, they tend to overestimate vegetation height.
Highlights
V EGETATION height is a key feature in crop and forest monitoring, from which other important variables, such as yield and biomass, can be retrieved
The inversion with methodologies based on the interferometric phase is only possible, thanks to the proportional variation of the phase center with time
This article presents a comparison of all known interferometric SAR (InSAR) techniques for the retrieval of rice crop height using TanDEMX datasets
Summary
V EGETATION height is a key feature in crop and forest monitoring, from which other important variables, such as yield and biomass, can be retrieved. A systematic acquisition of quantitative information about vegetation height from remote sensing data is of major relevance to support agricultural and forest management services. The exploitation of vegetation height information in the agricultural domain presents diverse objectives. Manuscript received September 30, 2020; revised April 5, 2021; accepted July 19, 2021. Date of publication July 30, 2021; date of current version August 18, 2021.
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More From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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