Abstract
This study analyses the relationship between fire incidence and some environmental factors, exploring the spatial non-stationarity of the phenomenon in sub-Saharan Africa. Geographically weighted regression (GWR) was used to study the above relationship. Environment covariates comprise land cover, anthropogenic and climatic variables. GWR was compared to ordinary least squares, and the hypothesis that GWR represents no improvement over the global model was tested. Local regression coefficients were mapped, interpreted and related with fire incidence. GWR revealed local patterns in parameter estimates and also reduced the spatial autocorrelation of model residuals. All the covariates were non-stationary and in terms of goodness of fit, the model replicates the data very well (R 2 = 87%). Vegetation has the most significant relationship with fire incidence, with climate variables being more important than anthropogenic variables in explaining variability of the response. Some coefficient estimates exhibit locally different signs, which would have gone undetected by a global approach. This study provides an improved understanding of spatial fire–environment relationships and shows that GWR is a valuable complement to global spatial analysis methods. When studying fire regimes, effects of spatial non-stationarity need to be incorporated in vegetation-fire modules to have better estimates of burned areas and to improve continental estimates of biomass burning and atmospheric emissions derived from vegetation fires.
This is a preview of subscription content, access via your institution.









References
Akaike H (1981) Likelihood of a model and information criteria. J Econ 16(1):3–14
Anselin L, Griffith DA (1988) Do spatial effects really matter in regression analysis? Pap Reg Sci Assoc 65:11–34
Archibald S, Roy DP, vanWilgen BW, Sholes RJ (2009) What limits fire? An examination of drivers of burnt area in Southern Africa. Glob Change Biol 15(3):613–630
Barbosa PM, Stroppiana D, Grégoire J-M, Pereira JMC (1999a) An assessment of vegetation fire in Africa (1981–1991): burned areas, burned biomass, and atmospheric emissions. Glob Biogeochem Cycles 13(4):933–950
Barbosa PM, Grégoire J-M, Pereira JMC (1999b) An algorithm for extracting burned areas from time series of AVHRR GAC data applied at a continental scale. Remote Sens Environ 69(3):253–263
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodological) 57(1):289–300
Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat 29(4):1165–1188
Bond WJ (1997) Fire. In: Cowling RM, Richardson DM, Pierce SM (eds) Vegetation of Southern Africa, 1st edn. Cambridge University Press, UK, pp 421–446
Brunsdon CA, Fotheringham AS, Charlton ME (1998) Geographically weighted regression–modelling spatial non-stationarity. The Stat 47(3):431–443
Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York
Butz RJ (2009) Traditional fire management: historical fire regimes and land use change in pastoral East Africa. Int J Wildland Fire 18(4):442–450
Byrne G, Charlton M, Fotheringham S (2009) Multiple dependent hypothesis tests in geographically weighted regression. In: Lees BG, Laffan SW (eds) 10th International conference on geocomputation. UNSW, Sydney November–December
Center for International Earth Science Information Network (CIESIN), Columbia University, Centro Internacional de Agricultura Tropical (CIAT) (2005) Gridded population of the World Version 3 (GPWv3): population density grids. Socioeconomic Data and Applications Center (SEDAC), Columbia University, Palisades
Clerici N, Boschetti L, Eva H, Grégoire J-M (2004) Assessing vegetation fires activity and its drivers in West-Central Africa using MODIS and TRMM data. Paper presented at International Geoscience Remote Sensing Symposium. IEEE Comput Soc, Piscataway
Cliff AD, Ord JK (1981) Spatial processes: models and applications. Pion, London
De Castro MC, Singer BH (2006) Controlling the false discovery rate: a new application to account for multiple and dependent tests in local statistics of spatial association. Geogr Anal 38:180–208
Diniz-Filho JAF, Bini LM, Hawkins BA (2003) Spatial autocorrelation and red herrings in geographical ecology. Glob Ecol Biogeogr 12(1):53–64
Dutilleul P, Clifford P, Richardson S, Hemon D (1993) Modifying the t test for assessing the correlation between two spatial processes. Biom 49(1):305–314
Dwyer E, Pereira JMC, DaCamara CC, Grégoire J-M (2000a) Characterization of the spatio-temporal patterns of global fire activity. J Biogeogr 21(6):1289–1302
Dwyer E, Grégoire J-M, Pereira JMC (2000b) Climate and vegetation as driving factors in global fire activity. In: Innes JL, Verstraete MM, Beniston M (eds) Biomass burning and its inter-relationships with the climate system. Kluwer, Dordrecht, pp 171–191
Eva H, Lambin EF (1998) Remote sensing of biomass burning in tropical regions: sampling issues and multisensor approach. Remote Sens Environ 64(3):292–315
Eva H, Lambin EF (2000) Fires and land-cover change in the tropics: a remote sensing analysis at the landscape scale. J Biogeogr 27(3):765–776
Foody GM (2004) Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna. Glob Ecol Biogeogr 13(4):315–320
Foody GM (2005) Mapping the richness and composition of British breeding birds from coarse spatial resolution satellite sensor imagery. Int J Remote Sens 26(18):3943–3956
Foody GM, Cutler MEJ (2003) Tree biodiversity in protected and logged Bornean tropical rain forests and its measurement by satellite remote sensing. J Biogeogr 30(7):1053–1066
Fotheringham AS, Brunsdon C, Charlton ME (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, New York
Frost PGH (1996) The ecology of miombo woodlands. In: Campbell B (ed) The Miombo in transition: woodlands and welfare in Africa. CIFOR, Indonesia, pp 11–57
Govaerts YM, Pereira JM, Pinty B, Mota B (2002) Impact of fires on surface albedo dynamics over the African continent. J Geophys Res 107(D22):4629. doi:10.1029/2002JD002388
Hall FG, Collatz G, Los S, Brown de Colstoun E, Landis D (2005) ISLSCP Initiative II. NASA. DVD/CD-ROM
Hansen M, DeFries R, Townshend JR, Carroll M, Dimiceli C, Sohlberg R (2003) Vegetation continuous fields MOD44B, 2001 Percent Tree Cover. Collection 3, University of Maryland, College Park, Maryland, 2001
Hoffman MT (1997) Human impacts on vegetation. In: Cowling RM, Richardson DM, Pierce SM (eds) Vegetation of Southern Africa. Cambridge University Press, UK, pp 507–534
Jetz W, Rahbek C, Lichstein JW (2005) Local and global approaches to spatial data analysis in ecology. Glob Ecol Biogeogr 14(1):97–98
Kupfer JA, Farris CA (2007) Incorporating spatial non-stationarity of regression coefficients into predictive vegetation models. Landsc Ecol 22(6):837–852
Laris P (2005) Spatiotemporal problems with detecting and mapping mosaic fire regimes with coarse-resolution spatial data in savanna environments. Remote Sens Environ 99(4):412–424
Legendre P (1993) Spatial autocorrelation: trouble or new paradigm? Ecol 74(6):1659–1673
Li B, Tao S, Dawson RW (2002) Relations between AVHRR NDVI and ecoclimatic parameters in China. Int J Remote Sens 23(5):989–999
Mayaux P, Bartholomé E, Cabral A, Cherlet M, Defourny P, Di Gregorio A, Diallo O, Massart M, Nonguierma A, Pekel J-F, Pretorius C, Vancutsem C, Vasconcelos M (2003) The Land Cover Map for Africa in the Year 2000. GLC2000 database, European Commission, Joint Research Centre. Available at http://www-tem.jrc.it/glc2000. Accessed 27 Feb. 2009
Moran MD (2003) Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos 100(2):403–405
New M, Hulme M, Jones PD (1999) Representing twentieth century space-time climate variability. Part 1: development of a 1961-90 mean monthly terrestrial climatology. J Clim 12(3):829–856
Olson DM, Dinerstein E, Wikramanatake ED, Burgess ND, Powell GVN, Underwood EC (2001) Terrestrial Ecoregions of the World: a new map of life on earth. Bioscience 51(11):933–938
Osborne PE, Foody GM, Suárez-Seoane S (2007) Non-stationarity and local approaches to modelling the distributions of wildlife. Divers Distrib 13(3):313–323
Páez A, Uchida T, Miyamoto K (2002) A general framework for estimation and inference of geographically weighted regression models: 1. Location-specific kernel bandwidths and a test for locational heterogeneity. Environ Plan A 34:733–754
Palmer AR, Hoffman MT (1997) Nama-karoo. In: Cowling RM, Richardson DM, Pierce SM (eds) Vegetation of Southern Africa. Cambridge University Press, United Kingdom, pp 167–187
Pereira JMC (2003) Remote sensing of burned areas in tropical savannas. Int J Wildland Fire 12(3–4):259–270
Perneger TV (1998) What’s wrong with Bonferroni adjustments. Br Med J 316(7139):1236–1238
Price C, Rind D (1993) What determines the cloud-to-ground lightning fraction in thunderstorms. Geophys Res Lett 20(6):463–466
Prince SD, Goward SJ (1995) Global primary production: a remote sensing approach. J Biogeogr 22(4–5):815–835
Ramankutty N, Foley JA (1999) Estimating historical changes in global land cover: Croplands from 1700 to 1992. Glob Biogeochem Cycles 13(4):997–1027
Rice WR (1989) Analyzing tables of statistical tests. Evol 43(1):223–225
Roy DP, Lewis PE, Justice CO (2002) Burned area mapping using multi-temporal moderate spatial resolution data__a bi-directional reflectance-based expectation approach. Remote Sens Environ 83(1–2):263–286
Roy DP, Jin Y, Lewis PE, Justice CO (2005) Prototyping a global algorithm for systematic fire affected area mapping using MODIS time series data. Remote Sens Environ 97(2):137–162
Sá ACL, Pereira JMC, Gardner RH (2007) Analysis of the relationship between spatial pattern and spectral detectability of areas burned in southern Africa using satellite data. Int J Remote Sens 28(16):3583–3601
Shi H, Laurent EJ, LeBouton J, Racevskis L, Hall KR, Donovan M, Doepker RV, Walters MB, Lupi F, Liu J (2006) Local spatial modelling of white-tailed deer distribution. Ecol Model 190(issues 1–2):171–189
Silva JMN, Pereira JMC, Cabral AI, Sá ACL, Vasconcelos MJP, Mota B, Grégoire J–M (2003) An estimate of the area burned in southern Africa during the 2000 dry season using SPOT-VEGETATION satellite data. J Geophys Res 108(D13):8498. doi:10.1029/2002JD002320
Silva JMN, Sá ACL, Pereira JMC (2005) Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: influence of spatial pattern and vegetation type. Remote Sens Environ 96(2):188–201
Tansey K, Grégoire J–M, Stroppiana D, Sousa A, Silva J, Pereira JMC, Boschetti L, Maggi M, Brivio PA, Fraser R, Flasse S, Ershov D, Binaghi E, Graetz D, Peduzzi P (2004) Vegetation burning in the year 2000: global burned area estimates from SPOT VEGETATION data. J Geophys Res 109:D14S03. doi:10.1029/2003JD003598
van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Kasibhatla PS, Arellano AF Jr (2006) Interannual variability in global biomass burning emissions from 1997 to 2004. Atmos Chem Phys 6:3423–3441
van Wilgen B, Scholes RJ (1997) The vegetation and fire regimes of southern hemisphere Africa. In: van Wilgen MO, Andreae BW, Goldammer JG, Lindsay JA (eds) Fire in Southern African Savannas. Witwatersrand University Press, Witwatersrand, pp 27–46
Wang Q, Ni J, Tenhunen J (2005) Application of a geographically-weighted regression analysis to estimate net primary production of Chinese forest ecosystem. Glob Ecol Biogeogr 14(4):379–393
Wint W, Robinson T (2007) Gridded livestock of the world–2007. Food and Agriculture Organization of the United Nations, Rome
Zhang LJ, Gove JH, Heath LS (2005) Spatial residual analysis of six modelling techniques. Ecol Model 186(2):154–177
Acknowledgments
We would like to thank to Chris Brunsdon who kindly gave his advice on some of the questions related with GWR methodology. Stewart Fotheringham and Martin Charlton research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/l1168) by Science Foundation Ireland under the National Development Plan. The authors gratefully acknowledge this support.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sá, A.C.L., Pereira, J.M.C., Charlton, M.E. et al. The pyrogeography of sub-Saharan Africa: a study of the spatial non-stationarity of fire–environment relationships using GWR. J Geogr Syst 13, 227–248 (2011). https://doi.org/10.1007/s10109-010-0123-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10109-010-0123-7