{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T23:44:43Z","timestamp":1775000683860,"version":"3.50.1"},"reference-count":67,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T00:00:00Z","timestamp":1668556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"IN114119, PAPIIT-DGAPA, UNAM"},{"name":"LANRESC CONACyT P. 271544 2a Consolidaci\u00f3n"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A five-band short-range multispectral sensor (MicaSense RedEdge-M) was adapted to an underwater housing and used to obtain data from coral reef benthos. Artificial illumination was required to obtain data from most of the spectral range of the sensor; the optimal distance for obtaining these data was 0.5 m, from the sensor to the bottom. Multispectral orthomosaics were developed using structure-from-motion software; these have the advantage of producing ultra-high spatial resolution (down to 0.4 \u00d7 0.4 mm\/pixel) images over larger areas. Pixel-based supervised classification of a multispectral (R, G, B, RE bands) orthomosaic accurately discriminated among different benthic components; classification schemes defined 9 to 14 different benthic components such as brown algae, green algae, sponges, crustose coralline algae, and different coral species with high accuracy (up to 84% overall accuracy, and 0.83 for Kappa and Tau coefficients). The least useful band acquired by the camera for this underwater application was the near-infrared (820\u2013860 nm) associated with its rapid absorption in the water column. Further testing is required to explore possible applications of these multispectral orthomosaics, including the assessment of the health of coral colonies, as well as the automation of their processing.<\/jats:p>","DOI":"10.3390\/rs14225782","type":"journal-article","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T03:27:44Z","timestamp":1668655664000},"page":"5782","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Coral Reef Benthos Classification Using Data from a Short-Range Multispectral Sensor"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4209-3738","authenticated-orcid":false,"given":"Joaqu\u00edn Rodrigo","family":"Garza-P\u00e9rez","sequence":"first","affiliation":[{"name":"PIESACOM, UMDI-Sisal, Facultad de Ciencias, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Sisal 97356, Mexico"},{"name":"Laboratorio Nacional de Resiliencia Costera, Sisal 97356, Mexico"}]},{"given":"Frida","family":"Barr\u00f3n-Coronel","sequence":"additional","affiliation":[{"name":"PIESACOM, UMDI-Sisal, Facultad de Ciencias, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Sisal 97356, Mexico"},{"name":"Posgrado en Ciencias del Mar y Limnolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Ciudad de M\u00e9xico 04510, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hedley, J.D., Roelfsema, C.M., Chollett, I., Harborne, A.R., Heron, S.F., Weeks, S., Skirving, W.J., Strong, A.E., Eakin, C.M., and Christensen, T.R.L. 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