{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T15:38:01Z","timestamp":1771256281919,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T00:00:00Z","timestamp":1617753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["870005\/1997-9, 310283\/2019-1, 306334\/2020-8"],"award-info":[{"award-number":["870005\/1997-9, 310283\/2019-1, 306334\/2020-8"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Aquaculture and salt-culture are relevant economic activities in the Brazilian Coastal Zone (BCZ). However, automatic discrimination of such activities from other water-related covers\/uses is not an easy task. In this sense, convolutional neural networks (CNN) have the advantage of predicting a given pixel\u2019s class label by providing as input a local region (named patches or chips) around that pixel. Both the convolutional nature and the semantic segmentation capability provide the U-Net classifier with the ability to access the \u201ccontext domain\u201d instead of solely isolated pixel values. Backed by the context domain, the results obtained show that the BCZ aquaculture\/saline ponds occupied ~356 km2 in 1985 and ~544 km2 in 2019, reflecting an area expansion of ~51%, a rise of 1.5\u00d7 in 34 years. From 1997 to 2015, the aqua-salt-culture area grew by a factor of ~1.7, jumping from 349 km2 to 583 km2, a 67% increase. In 2019, the Northeast sector concentrated 93% of the coastal aquaculture\/salt-culture surface, while the Southeast and South sectors contained 6% and 1%, respectively. Interestingly, despite presenting extensive coastal zones and suitable conditions for developing different aqua-salt-culture products, the North coast shows no relevant aqua or salt-culture infrastructure sign.<\/jats:p>","DOI":"10.3390\/rs13081415","type":"journal-article","created":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T11:31:59Z","timestamp":1617795119000},"page":"1415","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Large-Scale Deep-Learning Approach for Multi-Temporal Aqua and Salt-Culture Mapping"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7718-0992","authenticated-orcid":false,"given":"Cesar","family":"Diniz","sequence":"first","affiliation":[{"name":"Solved\u2014Solutions in Geoinformation, Bel\u00e9m 66075-750, Brazil"},{"name":"Geoscience Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}]},{"given":"Luiz","family":"Cortinhas","sequence":"additional","affiliation":[{"name":"Solved\u2014Solutions in Geoinformation, Bel\u00e9m 66075-750, Brazil"},{"name":"Technology Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}]},{"given":"Maria Luize","family":"Pinheiro","sequence":"additional","affiliation":[{"name":"Solved\u2014Solutions in Geoinformation, Bel\u00e9m 66075-750, Brazil"},{"name":"Technology Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}]},{"given":"Lu\u00eds","family":"Sadeck","sequence":"additional","affiliation":[{"name":"Solved\u2014Solutions in Geoinformation, Bel\u00e9m 66075-750, Brazil"},{"name":"Philosophy and Human Sciences Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}]},{"given":"Alexandre","family":"Fernandes Filho","sequence":"additional","affiliation":[{"name":"Solved\u2014Solutions in Geoinformation, Bel\u00e9m 66075-750, Brazil"},{"name":"Institute of Agricultural Sciences, UFRA\u2014Federal Rural University of the Amazon, Bel\u00e9m 66077-813, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5308-9721","authenticated-orcid":false,"given":"Luis R. F.","family":"Baumann","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Statistics, UFG\u2014Federal University of Goias, Goiania 74690-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4247-4477","authenticated-orcid":false,"given":"Marcos","family":"Adami","sequence":"additional","affiliation":[{"name":"Geoscience Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"},{"name":"INPE\u2014National Institute for Space Research, Amazon Spatial Coordination, S\u00e3o Paulo 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0252-808X","authenticated-orcid":false,"given":"Pedro Walfir M.","family":"Souza-Filho","sequence":"additional","affiliation":[{"name":"Geoscience Institute, UFPA\u2014Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"},{"name":"ITV\u2014Instituto Tecnol\u00f3gico Vale, Bel\u00e9m 66055-090, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,7]]},"reference":[{"key":"ref_1","unstructured":"Food And Agriculture Organization (FAO) (2019). 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