{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T06:21:49Z","timestamp":1772086909906,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,11,15]],"date-time":"2017-11-15T00:00:00Z","timestamp":1510704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"FCT","doi-asserted-by":"publisher","award":["UID\/EEA\/00066\/203"],"award-info":[{"award-number":["UID\/EEA\/00066\/203"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000921","name":"COST","doi-asserted-by":"publisher","award":["TD1403 \"Big Data Era in Sky and Earth 364 Observation\""],"award-info":[{"award-number":["TD1403 \"Big Data Era in Sky and Earth 364 Observation\""]}],"id":[{"id":"10.13039\/501100000921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification from satellite images. Further, an unsupervised approach based on k-means clustering has been also taken into consideration for comparison. The fuzzy-inference method includes training the classifier with a fuzzy-fusion technique and then performing land cover classification using reinforcement aggregation operators. To assess the robustness of the four methods, a comparative study including three years of land cover maps for the district of Mandimba, Niassa province, Mozambique, was undertaken. Our results show that the fuzzy-fusion method performs similarly to decision trees, achieving reliable classifications; neural networks suffer from overfitting; while k-means clustering constitutes a promising technique to identify land cover types from unknown areas.<\/jats:p>","DOI":"10.3390\/info8040147","type":"journal-article","created":{"date-parts":[[2017,11,15]],"date-time":"2017-11-15T11:13:35Z","timestamp":1510744415000},"page":"147","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1354-4739","authenticated-orcid":false,"given":"Andr\u00e9","family":"Mora","sequence":"first","affiliation":[{"name":"Computational Intelligence Group of CTS\/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tiago","family":"Santos","sequence":"additional","affiliation":[{"name":"Computational Intelligence Group of CTS\/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Szymon","family":"\u0141ukasik","sequence":"additional","affiliation":[{"name":"Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059 Krak\u00f3w, Poland"},{"name":"Systems Research Institute, Polish Academy of Sciences, 01-447 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5201-9836","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Silva","sequence":"additional","affiliation":[{"name":"Forest Research Centre, School of Agriculture, University of Lisbon, 1349-017 Lisbon, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4788-140X","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Falc\u00e3o","sequence":"additional","affiliation":[{"name":"Computational Intelligence Group of CTS\/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7173-7374","authenticated-orcid":false,"given":"Jos\u00e9","family":"Fonseca","sequence":"additional","affiliation":[{"name":"Computational Intelligence Group of CTS\/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3849-0151","authenticated-orcid":false,"given":"Rita","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Computational Intelligence Group of CTS\/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Santos, T.M.A., Mora, A., Ribeiro, R.A., and Silva, J.M.N. 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