{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T05:56:59Z","timestamp":1772690219094,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T00:00:00Z","timestamp":1648771200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002848","name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo","doi-asserted-by":"publisher","award":["22060402"],"award-info":[{"award-number":["22060402"]}],"id":[{"id":"10.13039\/501100002848","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The shadow-height method has been extensively used to extract the heights of buildings from the shadows they cast in non-stereo (single view) aerial and satellite imagery. However, the use of this method in Earth sciences has been limited, partially due to the relatively low accuracy reported, the fuzziness of shadow edges, the complexities of the scanning sensors, and a lack of software tools. In this paper, we present an enhanced shadow-height methodology offering significant accuracy improvement. These improvements are mainly the result of using a physical approach to model the illumination gradient through the edge of shadows and by leveraging meteorological data to precisely estimate atmospheric refraction. We validated 91 shadow-derived height estimations from images obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at three sites with latitudes between 33 and 78\u00b0S: The Andes Mountains, Sentinel Range, and Abbot ice shelf. Reference measurements were obtained from Global Navigation Satellite System (GNSS) surveys and the Ice, Cloud, and land Elevation Satellite (ICESat). The observed errors fell below 6% for small height differences (\u223c20 m) and below 2% for larger height differences (\u2273300 m). Our validation data cover solar elevations ranging from 3.7 to 42.2\u00b0, and we observed smaller absolute errors at lower solar elevations. This novel information can be valuable for studying surface elevation changes in present and old imagery and extending glacier volume variation time-series.<\/jats:p>","DOI":"10.3390\/rs14071702","type":"journal-article","created":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T21:23:55Z","timestamp":1648848235000},"page":"1702","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["High-Precision Measurement of Height Differences from Shadows in Non-Stereo Imagery: New Methodology and Accuracy Assessment"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9865-2530","authenticated-orcid":false,"given":"Camilo Andr\u00e9s","family":"Rada Giacaman","sequence":"first","affiliation":[{"name":"Centro de Investigaci\u00f3n GAIA Ant\u00e1rtica (CIGA), Universidad de Magallanes, Punta Arenas 6210427, Chile"},{"name":"Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/0734-189X(88)90016-3","article-title":"Detecting buildings in aerial images","volume":"41","author":"Huertas","year":"1988","journal-title":"Comput. 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