{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:01:08Z","timestamp":1769691668912,"version":"3.49.0"},"reference-count":58,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,8]],"date-time":"2018-08-08T00:00:00Z","timestamp":1533686400000},"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>Satellite imagery is increasingly being used to provide estimates of bathymetry in near-coastal (shallow) areas of the planet, as a more cost-effective alternative to traditional methods. In this paper, the relative accuracy of radiative-transfer and photogrammetric stereo methods applied to World View 2 imagery are examined, using LiDAR bathymetry and towed video as ground truth, and it is demonstrated, with a case study, that these methods are complementary; where one method might have limited accuracy, the other method often has improved accuracy. The depths of uniform, highly-reflective (sand) sea bed are better estimated with a radiative transfer-based method, while areas where there is high visual contrast in the scene, as identified by using a local standard deviation measure, are better estimated using the photogrammetric technique. In this paper, it is shown that a hybrid method can give a potential improvement in accuracy of more than 50% (from 2.84 m to 1.38 m RMSE in the ideal case) compared to either of the two methods alone. Metrics are developed that can be used to characterize regions of the scene where each technique is superior, realizing an improved overall depth accuracy over either method alone of between 16.9% and 19.7% (demonstrating a realised RMSE of 2.36 m).<\/jats:p>","DOI":"10.3390\/rs10081247","type":"journal-article","created":{"date-parts":[[2018,8,9]],"date-time":"2018-08-09T03:33:48Z","timestamp":1533785628000},"page":"1247","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method"],"prefix":"10.3390","volume":"10","author":[{"given":"Simon","family":"Collings","sequence":"first","affiliation":[{"name":"Commonwealth Scientific and Industrial Research Organisation (CSIRO), Data 61, 65 Brockway Road, Floreat, WA 6014, Australia"}]},{"given":"Elizabeth J.","family":"Botha","sequence":"additional","affiliation":[{"name":"CSIRO Oceans and Atmosphere, GPO Box 1700, Canberra, ACT 2601, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1681-9630","authenticated-orcid":false,"given":"Janet","family":"Anstee","sequence":"additional","affiliation":[{"name":"CSIRO Oceans and Atmosphere, GPO Box 1700, Canberra, ACT 2601, Australia"}]},{"given":"Norm","family":"Campbell","sequence":"additional","affiliation":[{"name":"Commonwealth Scientific and Industrial Research Organisation (CSIRO), Data 61, 65 Brockway Road, Floreat, WA 6014, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Collings, S., Campbell, N.A., and Keesing, J. 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