{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:47:24Z","timestamp":1760230044169,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"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 Causeway Coast World Heritage Site (Northern Ireland) is subject to rockfalls occurring on the coastal cliffs, thus raising major safety concerns given the number of tourists visiting the site. However, such high tourist frequentation makes this site favorable to implement citizen science monitoring programs. Besides allowing for the collection of a larger volume of data, better distributed spatially and temporally, citizen science also increases citizens\u2019 awareness\u2014in this case, about risks. Among citizen science approaches, Structure-from-Motion photogrammetry based on crowd-sourced photographs has the advantage of not requiring any particular expertise on the part of the operator who takes photos. Using a mock citizen survey for testing purposes, this study evaluated different methods relying on crowd-sourced photogrammetry to integrate surveys performed by citizens into a landslide monitoring program in Port Ganny (part of the touristic site of the Giant\u2019s Causeway). Among the processing scenarios that were tested, the Time-SIFT method allows the use of crowd-sourced data in a very satisfactory way in terms of reconstruction quality, with a standard deviation of 8.6 cm.<\/jats:p>","DOI":"10.3390\/rs14143243","type":"journal-article","created":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T21:15:52Z","timestamp":1657142152000},"page":"3243","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["How to Include Crowd-Sourced Photogrammetry in a Geohazard Observatory\u2014Case Study of the Giant\u2019s Causeway Coastal Cliffs"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7629-9710","authenticated-orcid":false,"given":"Marion","family":"Jaud","sequence":"first","affiliation":[{"name":"Laboratoire Geo-Oceans\u2014UMR 6538, CNRS, University Brest, Rue Dumont D\u2019Urville, 29280 Plouzan\u00e9, France"},{"name":"IUEM-UMS 3113, CNRS, University Brest, IRD, Rue Dumont D\u2019Urville, 29280 Plouzan\u00e9, France"}]},{"given":"Nicolas","family":"Le Dantec","sequence":"additional","affiliation":[{"name":"Laboratoire Geo-Oceans\u2014UMR 6538, CNRS, University Brest, Rue Dumont D\u2019Urville, 29280 Plouzan\u00e9, France"},{"name":"IUEM-UMS 3113, CNRS, University Brest, IRD, Rue Dumont D\u2019Urville, 29280 Plouzan\u00e9, France"}]},{"given":"Kieran","family":"Parker","sequence":"additional","affiliation":[{"name":"British Geological Survey of Northern Ireland, Dundonald House, Upper Newtownards Road, Ballymiscaw, Belfast BT4 3SB, UK"}]},{"given":"Kirstin","family":"Lemon","sequence":"additional","affiliation":[{"name":"British Geological Survey of Northern Ireland, Dundonald House, Upper Newtownards Road, Ballymiscaw, Belfast BT4 3SB, UK"}]},{"given":"Sylvain","family":"Lendre","sequence":"additional","affiliation":[{"name":"CEREMA, Direction Eau Mer et Fleuves, 134 Rue de Beauvais, 60280 Margny-l\u00e8s-Compi\u00e8gne, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2484-1464","authenticated-orcid":false,"given":"Christophe","family":"Delacourt","sequence":"additional","affiliation":[{"name":"Laboratoire Geo-Oceans\u2014UMR 6538, CNRS, University Brest, Rue Dumont D\u2019Urville, 29280 Plouzan\u00e9, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7794-5075","authenticated-orcid":false,"given":"Rui C.","family":"Gomes","sequence":"additional","affiliation":[{"name":"CERIS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Simpson, R., Page, K.R., and De Roure, D. (2014, January 7\u201311). Zooniverse: Observing the world\u2019s largest citizen science platform. Proceedings of the 23rd International Conference on World Wide Web, ACM, Seoul, Korea.","DOI":"10.1145\/2567948.2579215"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Stewart, C., Labr\u00e8che, G., and Gonz\u00e1lez, D.L. (2020). A Pilot Study on Remote Sensing and Citizen Science for Archaeological Prospection. Remote Sens., 12.","DOI":"10.3390\/rs12172795"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Langenk\u00e4mper, D., Simon-Lled\u00f3, E., Hosking, B., Jones, D.O.B., and Nattkemper, T.W. (2019). On the impact of Citizen Science-derived data quality on deep learning based classification in marine images. 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