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Information 2017, 8(4), 147;

Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study

Computational Intelligence Group of CTS/UNINOVA, FCT, University NOVA of Lisbon, 2820-516 Caparica, Portugal
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059 Kraków, Poland
Systems Research Institute, Polish Academy of Sciences, 01-447 Warsaw, Poland
Forest Research Centre, School of Agriculture, University of Lisbon, 1349-017 Lisbon, Portugal
Author to whom correspondence should be addressed.
Received: 8 October 2017 / Revised: 7 November 2017 / Accepted: 13 November 2017 / Published: 15 November 2017
(This article belongs to the Special Issue Fuzzy Logic for Image Processing)
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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. View Full-Text
Keywords: image fusion; aggregation operators; remote sensing; land cover classification image fusion; aggregation operators; remote sensing; land cover classification

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Mora, A.; Santos, T.M.A.; Łukasik, S.; Silva, J.M.N.; Falcão, A.J.; Fonseca, J.M.; Ribeiro, R.A. Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study. Information 2017, 8, 147.

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