气候变化领域集成服务门户(CCPortal): Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques

CCPortal

DOI	10.1016/j.rse.2021.112485
	Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques
	Shi H.; Zhao L.; Yang J.; Lopez-Sanchez J.M.; Zhao J.; Sun W.; Shi L.; Li P.
发表日期	2021
ISSN	00344257
卷号	261
英文摘要	Surface soil moisture (SM) retrieval over agricultural areas from polarimetric synthetic aperture radar (PolSAR) has long been restricted by vegetation attenuation, simplified polarimetric scattering modelling, and limited SAR measurements. This study proposes a modified polarimetric decomposition framework to retrieve SM from multi-incidence and multitemporal PolSAR observations. The framework is constructed by combining the X-Bragg model, the extended double Fresnel scattering model and the generalised volume scattering model (GVSM). Compared with traditional decomposition models, the proposed framework considers the depolarisation of dihedral scattering and the diverse vegetation contribution. Under the assumption that SM is invariant for the PolSAR observations at two different incidence angles and that vegetation scattering does not change between two consecutive measurements, analytical parameter solutions, including the dielectric constant of soil and crop stem, can be obtained by solving multivariable nonlinear equations. The proposed framework is applied to the time series of L-band uninhabited aerial vehicle synthetic aperture radar data acquired during the Soil Moisture Active Passive Validation Experiment in 2012. In this study, we assess retrieval performance by comparing the inversion results with in-situ measurements over bean, canola, corn, soybean, wheat and winter wheat areas and comparing the different performance of SM retrieval between the GVSM and Yamaguchi volume scattering models. Given that SM estimation is inherently influenced by crop phenology and empirical parameters which are introduced in the scattering models, we also investigate the influence of surface depolarisation angle and co-pol phase difference on SM estimation. Results show that the proposed retrieval framework provides an inversion accuracy of RMSE<6.0% and a correlation of R≥0.6 with an inversion rate larger than 90%. Over wheat and winter wheat fields, a correlation of 0.8 between SM estimates and measurements is observed when the surface scattering is dominant. Specifically, stem permittivity, which is retrieved synchronously with SM also shows a linear relationship with crop biomass and plant water content over bean, corn, soybean and wheat fields. We also find that a priori knowledge of surface depolarisation angle, co-pol phase difference and adaptive volume scattering could help to improve the performance of the proposed SM retrieval framework. However, the GVSM model is still not fully adaptive because the co-pol power ratio of volume scattering is potentially influenced by ground scattering. © 2021 Elsevier Inc.
英文关键词	Multi-incidence; Multitemporal; Polarimetric decomposition; Soil moisture; Synthetic aperture radar
语种	英语
scopus关键词	Antennas; Crops; Nonlinear equations; Parameter estimation; Polarimeters; Soil surveys; Surface scattering; Synthetic aperture radar; Vegetation; %moisture; Multi-incidence; Multi-temporal; Performance; Polarimetric decomposition; Polarimetric synthetic aperture radars; Radar observations; Scattering model; Soil moisture retrievals; Volume scattering; Soil moisture; Brassica napus var. napus; Glycine max
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178815
作者单位	State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, 430079, China; School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China; Institute of Computing Research, University of Alicante, P.O. Box 99, Alicante, E-03080, Spain
推荐引用方式 GB/T 7714	Shi H.,Zhao L.,Yang J.,et al. Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques[J],2021,261.
APA	Shi H..,Zhao L..,Yang J..,Lopez-Sanchez J.M..,Zhao J..,...&Li P..(2021).Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques.Remote Sensing of Environment,261.
MLA	Shi H.,et al."Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques".Remote Sensing of Environment 261(2021).