Clustering Detection for Amazonia Deforestation Using Spatio-temporal: Scan Statistics

Carlos Antonio Oliveira Vieira1, Nerilson Terra Santos1, Antonio Policarpo de Souza Carneiro1, Antonio Alcirley da Silva Balieiro2
1.Federal University of Vicosa Vicosa-MG, Brazil
2. Fundacao de Vigilancia em Saiide do Estado Amazonas - FVS/AM, Av. Andre Araiijo n° 701 - Aleixo, CEP. 69.060-001 - Manaus - Amazonas, Brasil

1. {carlos.vieira, nsantos, policarpo}; 2.

Abstract: The spatio-temporal models, developed for analyses of diseases, can also be used for others fields of study, including concerns about forest and deforestation. Therefore, this paper evaluated a methodology for detection of space-time clusters of cases that were mapped through the investigation of deforestation in Amazonas State. The methodology includes the location and the year that the deforestation's alert occurred. These deforestation's alerts are mapped by the DETER (Detection System of Deforestation in Real Time in Amazonia). The area of study, took place the south of Amazonas State, including Boca do Acre, Labrea, Canutama, Humaita, Manicore, Novo Aripuana and Apui County. This area has showed a significant change for the land cover which has increased the number of deforestation's alerts. Therefore this situation becomes a concern and gets more investigation, trying to stop factors that increase the number of cases in the area. The outcome shows an efficient model to detect space-time clusters of deforestation's alerts. The model was efficient to detect the location, the size, the order and characteristics about activities at the end of the study. Two clusters were considered alive clusters and kept alive until the end of the study. These clusters are located in Canutama and Labrea County.

Keywords: deforestation's alert, clusters, Scan statistiscs.

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