Modeling and prediction of the occurrence of fire in the southwest of the Amazon
DOI:
https://doi.org/10.5902/2179460X74679Keywords:
Amazon forest, Use and occupation, Environmental modelingAbstract
This study aims to estimate the probability of fire occurrence in the southern region of the state of Amazonas using the maximum entropy method. Data on climatic variables (precipitation, water deficit and temperature), protected areas, and land-use changes were selected and submitted to a principal component analysis to determine which would be the predictor variables included in the model. The modeling was performed using the MaxEnt 3.3.3. Calibration was performed from fires in August 2018 and the model was applied to simulate the distribution of the probability of occurrence of these events in August 2019. The model fit was evaluated using the area under the curve - AUC (independent evaluation of the threshold), sensitivity and specificity (threshold dependent assessment), and a jackknife test was applied to assess the isolated contribution of predictor variables. The results indicated that both the threshold-independent (AUC = 0.9439 ± 0.0007) and the threshold-dependent assessment show a satisfactory performance of the model. The most susceptible areas were concentrated mainly in the municipalities of Lábrea and Boca do Acre, which have the highest deforestation rates and pasture areas in the region. The most effective variables in the predictive performance of the model were the distance of roads and the Normalized Difference Vegetation Index – NDVI. The maximum entropy method proved to be an important tool to guide decisions on actions to prevent and fight fires in southern Amazonas.
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Anderson, L. O., Yamamoto, M., Cunningham, C., Fonseca, M. G., Fernandes, L. K. & Pimentel, A. (2017). Utilização de dados orbitais de focos de calor para caracterização de riscos de incêndios florestais e priorização de áreas para a tomada de decisão. Revista Brasileira de Cartografia, 69, 163-177. DOI: https://doi.org/10.14393/rbcv69n1-44038
Alvares, C. A., Stape, J. L., Sentelhas, P. C., Gonçalves, J. L. C., Sparovek, G. (2013). Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift, 22, 711-728. DOI: 10.1127/0941-2948/2013/0507
Arpaci, A., Malowersching, B., Sass, O. & Vacik, H. (2014). Using multi variate data mining techniques for estimating fire susceptibility of Tyrolean forest. Applied Geography, 53, 258-270. DOI: https://doi.org/10.1016/j.apgeog.2014.05.015
Bisquert, M., Caselles, E., Sánchez, J. M. & Caselles, V. (2012). Application of artificial neural network and logistic regression to the prediction of forest fire danger in Galicia using MODIS data. International Journal of Wildland Fire, v. 21, p. 1025-1029. DOI: https://doi.org/10.1071/WF11105
Borma, S. & Nobre, C. (2013). Secas na Amazônia: causas e consequências. 1ª. Ed. São Paulo: Oficina de Textos, 367p.
Cohen, J. C. P., Beltrão, J. C., Gandu, A. W. & Silva R. R. (2007). Influência do desmatamento sobre o ciclo hidrológico na Amazônia. Cience e Cultura, v. 59, p. 36-39.
Coutinho, M. A. N., Fernandes, A. C. G., Santos, V. G. & Nascimento, C. R. (2016). Análise comparativa dos índices de vegetação NDVI, SAVI, RATIO e IAF para identificação de queimadas. Caderno Ciências Agrárias, 8, 70-81.
Dalapicolla, J. (2016). Tutorial de modelos de distribuição de espécies: guia prático usando o MaxEnt e o ArcGIS 10. 1ª. Ed. Vitória: Universidade Federal do Espírito Santo,
Fearnside, P. M., Laurance, W. F., Cocbrane, M. A., Bergen, S., Sampaio, P. D. & Barber, C., et al. (2012). O futuro da Amazônia: modelos para prever as consequências da infraestrutura futura nos planos plurianuais. Novos Cadernos NAEA, 15, 25-52. DOI: https://doi.org/10.5801/ncn.v15i1.865
Fernandes, M. C., Coura, P. H. F., Sousa, M. G. & Avelar, A. S. (2011). Avaliação geoecológica de susceptibilidade à ocorrência de incêndios no estado do Rio de Janeiro, Brasil. Floresta e Ambiente, v. 18, p. 299-309. DOI: https://doi.org/10.4322/floram.2011.050
Fonseca, M. G., Aragão, L. E. O. C., Lima, A., Shimabukuro, Y. E., Arai, E. & Anderson, L. O. (2016). Modelling fire probability in the Brazilian Amazon using the maximum entropy method. International Journal of Wildland Fire, 25, 955-969. DOI: https://doi.org/10.1071/WF15216
Fonseca, M. G., Anderson, L. O., Arai, E., Shimabukuro, Y. E., Xaud, H. A. M. & Xaud, M. R. (2017). Climatic and anthropogenic drivers of northen Amazon fires during the 2015-2016 El Niño event. Ecological Applications, 27, 2514-2527. DOI: https://doi.org/10.1002/eap.1628
Giannini, T. C., Siqueira, M. F., Acosta, A. L., Barreto, F. C. C., Saraiva, A. M. & Santos, I. A. (2012). Desafios atuais da modelagem preditiva de distribuição de espécies. Rodriguésia, 63, 733-749. DOI: https://doi.org/10.1590/S2175-78602012000300017
Goldarag, Y. J., Mohammadzadeh, A. & Ardakani, A. S. (2016). Fire risk assessment using neural network and logistic regression. Journal of the Indian Society of Remote Sensing, 44, 885-894. DOI: https://doi.org/10.1007/s12524-016-0557-6
Hongyu, K., Sandanielo, V. L. M. & Oliveira Junior, G. J. (2015). Análise de componentes principais: resumo teórico, aplicação e interpretação. Engineering and Science, 5, 83-90, DOI: https://doi.org/10.18607/ES20165053
IBGE – Instituto Brasileiro de Geografia e Estatística. Manual técnico da vegetação brasileira, 2004. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/monografias/GEBIS%20-%20RJ/ManuaisdeGeociencias/Manual%20Tecnico%20da%20Vegetacao%20Brasileira%20n.1.pdf Acesso em: 12 de abril de 2019.
IBGE – Instituto Brasileiro de Geografia e Estatística. Mapas regionais, 2014. Disponível em: https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapas-regionais/15819-amazonia-legal.html Acesso em: 31 de janeiro de 2019.
INPE – Instituto Nacional de Pesquisas Espaciais. Portal do Monitoramento de Queimadas e Incêndios, 2016. Disponível em: http://queimadas.dgi.inpe.br/queimadas/portal Acesso em: 14 de fevereiro de 2019.
Lemos, N. S. A., Cunha, J.M., Campos, M. C. C. & Brito Filho, E. G. (2025). Forest fire distribution standard in the south of Amazonas state. Natural Hazards. 121,6011–6042. DOI: https://doi.org/10.1007/s11069-024-07030-0
Mallman, C. L., Prado, D. A. & Pereira Filho, W. (2015). Índice de vegetação por diferença normalizada para caracterização da dinâmica florestal no parque estadual Quarta Colônia, estado do Rio Grande do Sul – Brasil. Revista Brasileira de Geografia Física, 8, 1454-1469. DOI: https://doi.org/10.5935/1984-2295.20150080
MAPBIOMAS – Projeto de Mapeamento Anual da Cobertura e Uso do Solo no Brasil. Cobertura e Uso do Solo, 2018. Disponível em: https://plataforma.mapbiomas.org/map#coverage Acesso em 13 de maio de 2020.
Massada, A. B., Syphard, A. D., Stewart, S. I. & Radeloff, V. C. (2013). Wildfire ignition-distribution modelling: a comparative study in the Huron-Manistee National Forest, Michigan, USA. International Journal of Wildland Fire, 22, 174-183. DOI: https://doi.org/10.1071/WF11178
Mistry, J. & Bizerril, J. (2011). Por que é importante entender as interrelações entre pessoas, fogo e áreas protegidas? Biodiversidade Brasileira, 1, 40-49, 2011. DOI: https://doi.org/10.37002/biodiversidadebrasileira.v1i2.137
Nepstad, D., Carvalho, G., Barros, A. C., Alencar, A., Capobianco, J. P. & Bishop, J. (2001). Road paving, fire regime feedbacks, and the future of the Amazon forests. Forest Ecology and Managenment, 154, 1–13. https://doi.org/10.1016/S0378-1127(01)00511-4
Nogueira, C. B. C., Osoegawa, D. K. & Almeida, R. L. (2019). Políticas desenvolvimentistas na Amazônia: análise do desmatamento nos últimos dez anos (2009-2018). Revista Culturas Jurídicas, 6, 145-169. DOI: DOI: https://doi.org/10.22409/rcj.v6i13.752
Oliveira, S., Friderike, O., San-Miguel-Ayans, J., Camia, A. & Pereira, J. M. C. (2012). Modeling spatial patterns of fire occurrence in Mediterranean Europe using Multiple Regression and Random Forest. Forest Ecology and Managenment, 275, 117-129. DOI: https://doi.org/10.1016/j.foreco.2012.03.003
Pedreira Junior, A. L., Querino, C. A. S., Querino, J. K. A. S., Santos, L. O. F., Moura, A. R. M., Machado, N. G. & Biurdes, M. S. (2018). Variabilidade horária e intensidade sazonal da precipitação no município de Humaitá – AM. Revista Brasileira de Climatologia, 22, 463-475. DOI: https://doi.org/10.5380/abclima.v22i0.58089
Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. (2017). Opening the black box: an open-source release of Maxent. Ecography, 40, 887-893. DOI: https://doi.org/10.1111/ecog.03049
Phillips, S. J., Anderson, R. P. & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259. DOI: https://doi.org/10.1016/j.ecolmodel.2005.03.026
QGIS: Softwere of Geographic Information System. https://qgis.org/en/site/index.html
Ribeiro, S., Almeida, O., Ávila, S. & Oliveira, W. (2009). Pecuária e desmatamento: uma análise das principais causas diretas do desmatamento na Amazônia. Nova Economia, 19, 41-66. DOI: https://doi.org/10.1590/S0103-63512009000100003
Sabino, C. V. S., Lage, L. V. & Almeida, K. C. B. (2014). Uso de métodos estatísticos robustos na análise ambiental. Engenharia Sanitária e Ambiental, 19, 87-94. DOI: https://doi.org/10.1590/S1413-41522014019010000588
Santos, A. F., Cunha, J. M. da, Andrade, A. O. de, Campos, M. C. C., Brito, W. B. M., Santos, A. S. dos, Santos, R. F. dos, & Brito Filho, E. G. (2023). Rural agroecosystems under the sustainability aspect: an analysis in the southern Amazonas state. Ciência e Natura, 45, e22. https://doi.org/10.5902/2179460X70866
Santos, T. O., Andrade Filho, V. S., Rocha, V. M. & Menezes, J. S. (2017) Os impactos do desmatamento e queimadas de origem antrópica sobre o clima da Amazônia Brasileira: um estudo de revisão. Revista Geografia Acadêmica, 11, 157-181.
Silva Júnior, L. A. S., Delgado, R. C. & Wanderley, H. S. (2018). Estimativa da temperatura de superfície por sensoriamento remoto para a região da Amazônia Ocidental Brasileira. Revista Brasileira de Geografia Física, 11, 237-250. DOI: https://doi.org/10.26848/rbgf.v11.1.p237-250
Silvestrini, R. A., Soares-Filho, B. S., Nepstad, D., Coe, M., Rodrigues, H. & Assunção, R. (2011). Simulating fire regimes in the Amazon in response to climate change and deforestation. Ecological Applications, 21, 1573–1590, DOI: https://doi.org/10.1890/10-0827.1.
Sodré, G. R. C., Souza, E. B., Oliveira, J. V. & Moraes, B. C. (2018). Cálculo de risco e detecção de queimadas: uma análise na Amazônia Oriental. Revista Brasileira de Ciências Ambientais, 49, 1-14. DOI: https://doi.org/10.5327/Z2176-947820180345
Vasconcelos, S. S., Fearnside, P. M., Graça, P. M. L. A., Silva, P. R. T. & Dias, D. V. (2015). Suscetibilidade da vegetação ao fogo no sul do Amazonas sob condições meteorológicas atípicas durante a seca de 2005. Revista Brasileira de Meteorologia, 30, 134-144. DOI: https://doi.org/10.1590/0102-778620140070
White, B. L. A. (2018). Spatiotemporal variation in fire occurrence in the state of Amazonas, Brazil, between 2003 and 2016. Acta Amazônica, 48, 358-367. DOI: https://doi.org/10.1590/1809-4392201704522
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