Improved spatial model for Amazonian deforestation: an empirical assessment and spatial bias analysis

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dc.creatorSouza, Rodrigo Antônio de
dc.creatorMarco Júnior, Paulo De
dc.date.accessioned2023-08-09T15:00:10Z
dc.date.available2023-08-09T15:00:10Z
dc.date.issued2018
dc.description.abstractRainforest deforestation is a process controlled by both environmental and socioeconomic factors unevenly distributed in space. We tested the efficacy of a Machine Learning approach, based on MaxEnt models, to predict deforestation in the Brazilian Amazon, with special attention to the effects of the distance to the areas with higher present deforestation rates on model predictions. We use a set of variables that describe most of the mechanisms involved in the deforestation process such as infrastructure, social-economy and deforestation previous to 2008 to fit the model and evaluate model accuracy using real deforestation within 2009–2011. MaxEnt models were very effective for predicting new deforestation areas in spite of the high heterogeneity among Amazon municipalities. Both model sensitivity and positive predictive rate increased from areas with higher current deforestation to not deforested areas. There is higher model sensitivity near areas where deforestation process is more active. Our results support this approach as an effective tool for spatial prediction of deforestation and guide command & control operations against Amazonian deforestation.pt_BR
dc.identifier.citationSOUZA, Rodrigo Antônio de; MARCO JUNIOR, Paulo De. Improved spatial model for Amazonian deforestation: an empirical assessment and spatial bias analysis. Ecological Modelling, Amsterdam, v. 387, p. 1-9, 2018. DOI: 10.1016/j.ecolmodel.2018.08.015. Disponível em: https://www.sciencedirect.com/science/article/pii/S0304380018302849. Acesso em: 25 jul. 2023.pt_BR
dc.identifier.doi10.1016/j.ecolmodel.2018.08.015
dc.identifier.issn0304-3800
dc.identifier.issne- 1872-7026
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0304380018302849
dc.language.isoengpt_BR
dc.publisher.countryHolandapt_BR
dc.publisher.departmentInstituto de Ciências Biológicas - ICB (RMG)pt_BR
dc.rightsAcesso Restritopt_BR
dc.subjectDeforestationpt_BR
dc.subjectDeforestation frontierpt_BR
dc.subjectLandscape modellingpt_BR
dc.subjectAmazon deforestationpt_BR
dc.subjectPublic policiespt_BR
dc.titleImproved spatial model for Amazonian deforestation: an empirical assessment and spatial bias analysispt_BR
dc.typeArtigopt_BR

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