{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T18:53:39Z","timestamp":1767984819260,"version":"3.49.0"},"reference-count":71,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T00:00:00Z","timestamp":1541548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The physical properties of a medium such as density, grain size and surface roughness all influence the angular dependence of spectral signatures. Radiative transfer models, such as the one developed by Hapke, can relate the angular dependence of the reflectance to these geophysical variables. This paper focuses on extracting geophysical parameters, fill factor (decreasing porosity) and the single scattering albedo (SSA), through the inversion of a modified version of the Hapke model of airborne and space-borne imagery. The inversion methodology was validated through controlled experiments within a laboratory setting, where a good correlation (R     2     = 0.72) between the retrieved fill factor and the measured density was obtained. Using the same approach, we also retrieved the sediment fill factor and SSA from airborne data collected by the NASA G-LiHT system, and space-borne data observed by the NOAA GOES imager. The results from these studies provide a mechanism to understand geophysical characteristics of the terrain and may potentially be used for long-term monitoring of the dynamic dunes system.<\/jats:p>","DOI":"10.3390\/rs10111758","type":"journal-article","created":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T10:32:07Z","timestamp":1541586727000},"page":"1758","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Retrieval of Sediment Fill Factor by Inversion of a Modified Hapke Model Applied to Sampled HCRF from Airborne and Satellite Imagery"],"prefix":"10.3390","volume":"10","author":[{"given":"Rehman S.","family":"Eon","sequence":"first","affiliation":[{"name":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623-5603, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3466-0483","authenticated-orcid":false,"given":"Charles M.","family":"Bachmann","sequence":"additional","affiliation":[{"name":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623-5603, USA"}]},{"given":"Aaron D.","family":"Gerace","sequence":"additional","affiliation":[{"name":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623-5603, USA"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S38","DOI":"10.1016\/j.rse.2008.09.019","article-title":"Using imaging spectroscopy to study soil properties","volume":"113","author":"Chabrillat","year":"2009","journal-title":"Remote Sens. 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