A general and extensible framework for assessing change detection techniques

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorVictoria University of Wellington — VUW-
Autor(es): dc.creatorNegri, Rogério G.-
Autor(es): dc.creatorFrery, Alejandro C.-
Data de aceite: dc.date.accessioned2025-08-21T20:02:07Z-
Data de disponibilização: dc.date.available2025-08-21T20:02:07Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-09-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.cageo.2023.105390-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247498-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247498-
Descrição: dc.descriptionChange detection techniques play an essential role in Remote Sensing applications, such as environmental monitoring, governmental planning, and studies of areas affected by natural disasters. This fact makes the development of more accurate change detection techniques a constant challenge. However, the lack of public benchmarks available to analyze and compare the performance of change detection techniques hampers quantitative comparisons. In light of this reality, this study proposes and formalizes a novel framework for imagery dataset simulation. In contrast with other image simulation methods, images synthesized by the proposed method are explicitly designed to assess and compare change detection methods. The framework is extensible and general allowing, in particular, the use of both supervised and unsupervised change detection methods. As an application, we compare the performance of well-known algorithms to data sets that mimic what the Landsat 5 TM sensor observed over a forest area subjected to deforestation for agricultural purposes. The results support discussing the performance of methods and show the usefulness of the proposed framework. We provide the source codes in a public repository.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionSão Paulo State University – UNESP Institute of Science and Technology – ICT, São José dos Campos-
Descrição: dc.descriptionSchool of Mathematics and Statistics Victoria University of Wellington — VUW-
Descrição: dc.descriptionSão Paulo State University – UNESP Institute of Science and Technology – ICT, São José dos Campos-
Descrição: dc.descriptionFAPESP: 2018/01033-3-
Descrição: dc.descriptionFAPESP: 2021/01305-6-
Descrição: dc.descriptionCNPq: 305220/2022-5-
Idioma: dc.languageen-
Relação: dc.relationComputers and Geosciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectChange detection-
Palavras-chave: dc.subjectClassification assessment-
Palavras-chave: dc.subjectImage simulation-
Título: dc.titleA general and extensible framework for assessing change detection techniques-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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