{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:07:08Z","timestamp":1760144828747,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T00:00:00Z","timestamp":1716163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NRL base research program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The use of bistatic polarimetric SAR for rough surface observation has attracted increasing interest in recent years, with its acquisition of additional polarimetric information. In this paper, we investigate the sensitivity of polarimetric variables to soil moisture and surface roughness, with the intention of locating favorable bistatic geometries for soil moisture retrieval. However, in the bistatic setting, the expanded imaging geometry is convolved with the polarimetric scattering response along with the in-scene variations in the soil moisture and surface roughness. The probing polarization states continuously evolve with the bistatic geometry, incurring varying polarization orientation angles. In this investigation, we propose to first compensate the bistatic polarimetric observations for the geometry-induced polarization rotation. Simulations based on a two-scale rough surface scattering model are then used to evaluate the optimal imaging geometry for the best sensitivity to the soil moisture content. We show the different sensing geometries associated with a full list of common polarimetric variables, as we seek favorable bistatic geometries in non-specular directions. The influences of both surface roughness scales are evaluated, with the small-scale roughness parameter imposing the greatest limitation on our results.<\/jats:p>","DOI":"10.3390\/rs16101807","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T06:31:58Z","timestamp":1716186718000},"page":"1807","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Geometry-Compensated Sensitivity Study of Polarimetric Bistatic Scattering for Rough Surface Observation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-4906-730X","authenticated-orcid":false,"given":"Yanting","family":"Wang","sequence":"first","affiliation":[{"name":"Remote Sensing Division, U.S. Naval Research Laboratory, Washington, DC 20375, USA"}]},{"given":"Thomas L.","family":"Ainsworth","sequence":"additional","affiliation":[{"name":"Department of Physics, Kent State University, Kent, OH 44242, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3252","DOI":"10.1109\/TGRS.2008.921495","article-title":"Radar bistatic configurations for soil moisture retrieval: A simulation study","volume":"46","author":"Pierdicca","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4227","DOI":"10.1080\/01431160903232808","article-title":"Sensitivity of bistatic scattering to soil moisture and surface roughness of bare soils","volume":"31","author":"Brigioni","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, T., Hajnsek, I., and Chen, K.-S. (2021). Sensitivity analysis of bistatic scattering for soil moisture retrieval. Remote Sens., 13.","DOI":"10.3390\/rs13020188"},{"key":"ref_4","unstructured":"Masters, D., Katzberg, S., and Axelrad, P. (2003, January 21\u201325). Airborne GPS bistatic radar soil moisture measurements during SMEX 02. 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