Fire risk assessment in the Brazilian Amazon using MODIS imagery and change vector analysis

Applied Geography

Volumn 31, Issue 1, 2011, Pages 76-84

  Maeda, Eduardo E ^a   Arcoverde, Gustavo F B ^b   Pellikka, Petri K E ^a   Shimabukuro, Yosio E ^b  

^a UNIVERSITY OF HELSINKI   (Finland)

^b INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS   (Brazil)

Author keywords

Brazilian Amazon; Change vector analysis; Forest fire; Remote sensing

Indexed keywords

DECISION SUPPORT SYSTEM; DETECTION METHOD; FOREST FIRE; GIS; IMAGE ANALYSIS; LAND USE CHANGE; MODIS; PIXEL; REMOTE SENSING; RISK ASSESSMENT; SATELLITE IMAGERY; VECTOR; WILDFIRE;

AMAZONIA; BRAZIL;

EID: 78649451386     PISSN: 01436228     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apgeog.2010.02.004     Document Type: Article

References (42)

1. Almeida Filho R., Shimabukuro Y.E. Monitoring biomass burning in the Brazilian Amazônia. International Journal of Remote Sensing 2004, 25(24):5537-5542.
2. Alves D.S. Space-time dynamics of deforestation in Brazilian Amazonia. International Journal of Remote Sensing 2002, 23(14):2903-2908.
3. Aragão L.E.O.C.de, Malhi Y., Barbier N., Lima A., Shimabukuro Y., Anderson L., et al. Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia. Philosophical Transactions of the Royal Society 2008, 363(1498):1779-1785.
4. Aragão L.E.O.C.de, Malhi Y., Roman-Cuesta R.M., Saatchi S., Aanderson L.O., Shimabukuro Y.E. Spatial patterns and fire response of recent Amazonian droughts. Geophysical Research Letters 2007, 34:L07701-L07706.
5. Arima E.Y., Simmons C.S., Walker R.T., Cochrane M.A. Fire in the Brazilian Amazon: a spatially explicit model for policy impact analysis. Journal of Regional Science 2007, 47(3):541-567.
6. Cardille J.A., Foley J.A. Agricultural land-use change in Brazilian Amazônia between 1980 and 1995: evidence from integrated satellite and census data. Remote Sensing of Environment 2003, 87(4):551-562.
7. Cochrane M.A. Fire science for rainforests. Nature 2003, 421:913-919.
8. Costa M.H., Yanagi S.N.M., Souza P.J.O.P., Ribeiro A., Rocha E.J.P. Climate change in Amazonia caused by soybean cropland expansion, as compared to caused by pastureland expansion. Geophysical Research Letters 2007, 34:L07706. 10.1029/2007GL029271.
9. Daughtry C.S.T., Hunt E.R. Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover. Remote Sensing of Environment 2008, 112(4):1647-1657.
10. Daughtry C.S.T., Hunt E.R., Doraiswamy P.C., McMurtrey J.E. Remote sensing the spatial distribution of crop residues. Agronomy Journal 2005, 97:864-871.
11. Eva H., Fritz S. Examining the potential of using remotely sensed fire data to predict areas of rapid forest change in South America. Applied Geography 2003, 23(2-3):189-204.
12. Fearnside P.M. Uso da terra na Amazônia e as mudanças climáticas globais. Brazilian Journal of Ecology 2007, 10(2):83-100.
13. Giglio L., van der Werf G.R., Randerson J.T., Collatz G.J., Kasibhatla P.S. Global estimation of burned area using MODIS active fire observations. Atmospheric Chemistry and Physics 2006, 6:957-974.
14. Gullison R.E., Frumhoff P.C., Canadell J.G., Field C.B., Nepstad D.C., Hayhoe K., et al. Tropical forests and climate policy. Science 2007, 316:985-986.
15. Hansen M.C., Shimabukuro Y.E., Potapov P., Pittman K. Comparing annual MODIS and PRODES forest cover change data for advancing monitoring of Brazilian forest cover. Remote Sensing of Environment 2008, 112(10):3784-3793.
16. IBGE. (2008). Brazilian Institute of Geography and Statistics. SIDRA. Available online at: Accessed 05.12.08. http://www.sidra.ibge.gov.br/bda/tabela/listabl.asp%3Fc%3D1612&z%3Dp&o%3D19.
17. INPE PRODES project: Monitoramento da Floresta Amazônica Brasileira por Satélite Available from, Accessed 19.10.08. http://www.obt.inpe.br/prodes/.
18. Jaiswal R.K., Mukherjee S., Raju K.D., Saxena R. Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth Observation and Geoinformation 2002, 4(1):1-10.
19. Johnson R.D., Kasischke E.S. Change vector analysis: a technique for the multispectral monitoring of land- cover and condition. International Journal of Remote Sensing 1998, 19(3):411-426.
20. Justice C.O., Giglio L., Korontzi S., Owens J., Morisette J.T., Roy D.P., et al. The MODIS fire products. Remote Sensing of Environment 2002, 83(1-2):244-262.
21. Justice C.O., Townshend J.R.G., Vermote E.F., Masuoka E., Wolfe R.E., Saleous N., et al. An overview of MODIS Land data processing and product status. Remote Sensing of Environment 2002, 83(1-2):3-15.
22. Lambin E.F., Strahler A.H. Indicators of land-cover change for change-vector analysis in multitemporal space at coarse spatial scales. International Journal of Remote Sensing 1994, 15(10):2099-2119.
23. Leblon B., Garcia P.A.F., Olford S., MacLean D.A., Flannigan M.D. Using cumulative NOAA-AVHRR spectral indices for estimating fire danger codes in northern boreal forests. International Journal of Applied Earth Observation and Geoinformation 2007, 9:335-342.
24. López, S., & Sierra, R. Agricultural change in the Pastaza River Basin: a spatially explicit model of native Amazonian cultivation. Applied Geography, in press, doi:10.1016/j.apgeog.2009.10.004.
25. Lorena R., Lambin E. The spatial dynamics of deforestation and agent use in the Amazon. Applied Geography 2009, 23(2):171-181.
26. Lu D., Batistella M., Moran E. Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data. International Journal of Remote Sensing 2007, 28(24):5447-5459.
27. Maeda E.E., Formaggio A.R., Shimabukuro Y.E., Arcoverde G.F.B., Hansen M. Predicting forest fire in the Brazilian Amazon using MODIS imagery and artificial neural networks. International Journal of Applied Earth Observation and Geoinformation 2009, 11(4):265-272.
28. Morton D.C., DeFries R.S., Randerson J.T., Giglio L., Schroeder W., van der Werf G.R. Agricultural intensification increases deforestation fire activity in Amazonia. Global Change Biology 2008, 14:2262-2275.
29. Morton D.C., DeFries R.S., Shimabukuro Y.E., Anderson L.O., Espírito-Santo F.D.B., Hansen M., et al. Rapid assessment of annual deforestation in the Brazilian Amazon using MODIS data. Earth Interactions 2005, 9. Paper 8, [online journal].
30. Nepstad D., Moreira A., Veríssimo A., Lefebvre P., Schlesinger P., Potter C., et al. Forest Fire Prediction and Prevention in the Brazilian Amazon. Conservation Biology 1998, 12(5):951-953.
31. Quinlan J.R. C 4.5: Programs for machine learning 1993, Morgan Kaufmann, San Mateo, 302p.
32. Quintano C., Fernández-Manso A., Fernández-Manso O., Shimabukuro Y.E. Mapping burned areas in Mediterranean countries using spectral mixture analysis from a uni-temporal perspective. International Journal of Remote Sensing 2006, 27(4):645-662.
33. Rogan J., Franklin J., Stow D., Miller J., Woodcock C., Roberts D. Mapping land-cover modifications over large areas: a comparison of machine learning algorithms. Remote Sensing of Environment 2008, 112(5):2272-2283.
34. Roy D.P., Boschetti L., Justice C.O., Ju J. The collection 5 MODIS burned area product - global evaluation by comparison with the MODIS active fire product. Remote Sensing of Environment 2008, 112(9):3690-3707.
35. Salovaara K.J., Thessler S., Malik R.N., Tuomisto H. Classification of Amazonian primary rain forest vegetation using Landsat ETM+ satellite imagery. Remote Sensing of Environment 2005, 97(1):39-51.
36. Soler L. de S., Escada M.I., Verburg P. Quantifying deforestation and secondary forest determinants for different spatial extents in an Amazonian colonization frontier (Rondonia). Applied Geography 2009, 29(2):182-193.
37. Tooke T.R., Coops N.C., Goodwin N.R., Voogt J.A. Extracting urban vegetation characteristics using spectral mixture analysis and decision tree classifications. Remote Sensing of Environment 2009, 113(2):398-407.
38. Townshend J.R.G., Justice C.O. Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations. International Journal of Remote Sensing 1988, 9:187-236.
39. Uhl C., Kauffman J.B. Deforestation, fire susceptibility and potential tree responses to fire in the eastern Amazon. Ecology 1990, 71(2):437-449.
40. Verbesselt J., Somers B., Lhermitte S., Jonckheere I., van Aardt J., Coppin P. Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Remote Sensing of Environment 2007, 108:357-368.
41. Wang Y.Y., Li J. Feature-selection ability of the decision-tree algorithm and the impact of features-election/extraction on decision-tree results based on hyperspectral data. International Journal of Remote Sensing 2008, 29(10):2993-3010.
42. Witten I.H., Frank E. Data mining: Practical machine learning tools with java implementations 2005, Morgan Kaufmann, Los Altos, 560p. 2nd ed.