The pyrogeography of sub-Saharan Africa: a study of the spatial non-stationarity of fire-environment relationships using GWR

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 = 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 A. C. L. Sá (&) J. M. C. Pereira B. Mota Department of Forestry, Instituto Superior de Agronomia, Tapada da Ajuda, 1349-017 Lisbon, Portugal e-mail: [email protected] M. E. Charlton A. Stewart Fotheringham National Centre for Geocomputation, National University of Ireland Maynooth, Maynooth, Co. Kildare, Ireland P. M. Barbosa European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi S/N, 21027 Ispra, VA, Italy 123 J Geogr Syst (2011) 13:227–248 DOI 10.1007/s10109-010-0123-7