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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A Soft Computing Approach for Selecting and Combining Spectral Bands

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Author(s):
Albarracin, Juan F. H. [1] ; Oliveira, Rafael S. [2] ; Hirota, Marina [3, 2] ; dos Santos, Jefersson A. [4] ; Torres, Ricardo da S. [5]
Total Authors: 5
Affiliation:
[1] Univ Estadual Campinas, Inst Comp, BR-13000000 Campinas - Brazil
[2] Univ Estadual Campinas, Inst Biol, BR-13000000 Campinas - Brazil
[3] Univ Fed Santa Catarina, Dept Phys, BR-88040900 Florianopolis, SC - Brazil
[4] Univ Fed Minas Gerais, Dept Comp Sci, BR-31270901 Belo Horizonte, MG - Brazil
[5] Norwegian Univ Sci & Technol NTNU, Dept ICT & Nat Sci, N-6009 Alesund - Norway
Total Affiliations: 5
Document type: Journal article
Source: REMOTE SENSING; v. 12, n. 14 JUL 2020.
Web of Science Citations: 0
Abstract

We introduce a soft computing approach for automatically selecting and combining indices from remote sensing multispectral images that can be used for classification tasks. The proposed approach is based on a Genetic-Programming (GP) framework, a technique successfully used in a wide variety of optimization problems. Through GP, it is possible to learn indices that maximize the separability of samples from two different classes. Once the indices specialized for all the pairs of classes are obtained, they are used in pixelwise classification tasks. We used the GP-based solution to evaluate complex classification problems, such as those that are related to the discrimination of vegetation types within and between tropical biomes. Using time series defined in terms of the learned spectral indices, we show that the GP framework leads to superior results than other indices that are used to discriminate and classify tropical biomes. (AU)

FAPESP's process: 15/02105-0 - Identifying temporal changes in tropical South American vegetation: a breakpoint detection approach
Grantee:Alexandre Esteves Almeida
Support type: Scholarships in Brazil - Master
FAPESP's process: 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil
Grantee:Rubens Augusto Camargo Lamparelli
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
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Support type: Research Grants - Research Partnership for Technological Innovation - PITE
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Grantee:Alexandre Esteves Almeida
Support type: Scholarships abroad - Research Internship - Master's degree
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support type: Research Projects - Thematic Grants
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Support type: Research Projects - Thematic Grants
FAPESP's process: 16/26170-8 - Structural breaks detection in time series and its use in the definition of stability measures
Grantee:Nathália Menini Cardoso dos Santos
Support type: Scholarships in Brazil - Master
FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 18/06918-3 - Quantifying Amazon's resilience through structural breaks associated with extreme climatic events
Grantee:Nathália Menini Cardoso dos Santos
Support type: Scholarships abroad - Research Internship - Master's degree