Aim In any region affected, fires exhibit a strong seasonal cycle driven by the dynamic of fuel moisture and ignition sources throughout the year. In this paper we investigate the global patterns of fire seasonality, which we relate to climatic, anthropogenic, land-cover and land-use variables.Location Global, with detailed analyses from single 1°¥ 1°grid cells. MethodsWe use a fire risk index, the Chandler burning index (CBI), as an indicator of the 'natural' , eco-climatic fire seasonality, across all types of ecosystems. A simple metric, the middle of the fire season, is computed from both gridded CBI data and satellite-derived fire detections. We then interpret the difference between the eco-climatic and observed metrics as an indicator of the human footprint on fire seasonality. ResultsDeforestation, shifting cultivation, cropland production or tropical savanna fires are associated with specific timings due to land-use practices, sometimes largely decoupled from the CBI dynamics. Detailed time series from relevant locations provide comprehensive information about these practices and how they are adapted to eco-climatic conditions. Main conclusionsWe find a great influence of anthropogenic activities on global patterns of fire seasonality. The specificity of the main fire practices and their easy identification from global observation is a potential tool to support land-use monitoring efforts. Our results should also prove valuable in the development of a methodological approach for improving the representation of anthropogenic fire practices in dynamic global vegetation models.

Aim This paper presents a new global burned area (BA) product developed within the framework of the European Space Agency's Climate Change Initiative (CCI) programme, along with a first assessment of its potentials for atmospheric and carbon cycle modelling.Innovation Methods are presented for generating a new global BA product, along with a comparison with existing BA products, in terms of BA extension, fire size and shapes and emissions derived from biomass burnings.Main conclusions Three years of the global BA product were produced, accounting for a total BA of between 360 and 380 Mha year 21. General omission and commission errors for BA were 0.76 and 0.64, but they decreased to 0.51 and 0.52, respectively, for sites with more than 10% BA. Intercomparison with other existing BA datasets found similar spatial and temporal trends, mainly with the BA included in the Global Fire Emissions Database (GFED4), although regional differences were found (particularly in the 2006 fires of eastern Europe). The simulated carbon emissions from biomass burning averaged 2.1 Pg C year 21.

Global fire monitoring systems are crucial to study fire behaviour, fire regimes and their impact at the global scale. Although global fire products based on the use of Earth Observation satellites exist, most remote sensing products only partially cover the requirements for these analyses. These data do not provide information like fire size, fire spread speed, how fires may evolve and joint into single event, or the number of fire events for a given area. This high level of abstraction is very valuable; it makes it possible to characterize fires by types (either size, spread, behaviour, etc.). Here, we present and test a data mining work flow to create a global database of single fires that allows for the characterization of fire types and fire regimes worldwide. This work describes the data produced by a data mining process using MODIS burnt area product Collection 6 (MCD64A1). The entire product has been computed until the present and is available under the umbrella of the Global Wildfire Information System (GWIS).

Abstract. Vegetation fires have been acknowledged as an environmental process of global scale, which affects the chemical composition of the troposphere, and has profound ecological and climatic impacts. However, considerable uncertainty remains, especially concerning intra and inter-annual variability of fire incidence. The main goals of our global-scale study were to characterise spatial-temporal patterns of fire activity, to identify broad geographical areas with similar vegetation fire dynamics, and to analyse the relationship between fire activity and the El Niño-Southern Oscillation. This study relies on 10 years (mid 1996–mid 2006) of screened European Space Agency World Fire Atlas (WFA) data, obtained from Along Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) imagery. Empirical Orthogonal Function analysis was used to reduce the dimensionality of the dataset. Regions of homogeneous fire dynamics were identified with cluster analysis, and interpreted based on their eco-climatic characteristics. The impact of 1997–1998 El Niño is clearly dominant over the study period, causing increased fire activity in a variety of regions and ecosystems, with variable timing. Overall, this study provides the first global decadal assessment of spatial-temporal fire variability and confirms the usefulness of the screened WFA for global fire ecoclimatology research.

We explore the large spatial variation in the relationship between population density and burned area, using continental-scale Geographically Weighted Regression (GWR) based on 13 years of satellite-derived burned area maps from the global fire emissions database (GFED) and the human population density from the gridded population of the world (GPW 2005). Significant relationships are observed over 51.5% of the global land area, and the area affected varies from continent to continent: population density has a significant impact on fire over most of Asia and Africa but is important in explaining fire over < 22% of Europe and Australia. Increasing population density is associated with both increased and decreased in fire. The nature of the relationship depends on land-use: increasing population density is associated with increased burned are in rangelands but with decreased burned area in croplands. Overall, the relationship between population density and burned area is non-monotonic: burned area initially increases with population density and then decreases when population density exceeds a threshold. These thresholds vary regionally. Our study contributes to improved understanding of how human activities relate to burned area, and should contribute to a better estimate of atmospheric emissions from biomass burning.