Anthromes displaying evidence of weekly cycles in active fire data cover 70% of the global land surface.

Across the globe, human activities have been gaining importance relatively to climate and ecology as the main controls on fire regimes and consequently human activity became an important driver of the frequency, extent and intensity of vegetation burning worldwide. Our objective in the present study is to look for weekly cycles in vegetation fire activity at global scale as evidence of human agency, relying on the original MODIS active fire detections at 1 km spatial resolution (MCD14ML) and using novel statistical methodologies to detect significant periodicities in time series data. We tested the hypotheses that global fire activity displays weekly cycles and that the weekday with the fewest fires is Sunday.

Religious Affiliation Modulates Weekly Cycles of Cropland Burning in Sub-Saharan Africa.

Vegetation burning is a common land management practice in Africa, where fire is used for hunting, livestock husbandry, pest control, food gathering, cropland fertilization, and wildfire prevention. Given such strong anthropogenic control of fire, we tested the hypotheses that fire activity displays weekly cycles, and that the week day with the fewest fires depends on regionally predominant religious affiliation. We also analyzed the effect of land use (anthrome) on weekly fire cycle significance.

In search of spatial extremes.

In environmental studies attention increasingly focuses on identification of spatial extremes: locations with observations that are apparently higher than either a preset background threshold or neighbouring observations. We consider various procedures for identifying values and locations of these extremes: extreme value theory, conditionally simulated fields and disjunctive kriging. In a recent research project we studied the distribution of nine environmental pollutants (heavy metals, polyaromatic hydrocarbons and mineral oil) in a large industrial estate in the southern Netherlands.

The Measurement of Averages and Extremes of Environmental Variables.

The relationship between the statistics of environmental measurements averaged over different time scales is related to extreme levels of the variables. Results on the asymptotic joint distributions of extreme averages over different time periods are treated.