Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been identified and analysed by using the scan statistic, a method which was devised to evidence clusters in epidemiology. Results showed that the method is reliable to find clusters of events and to evaluate their significance via Monte Carlo replication. The evaluation of the presence of spatial and temporal patterns in fire occurrence and their significance could have a great impact in forthcoming studies on fire occurrences prediction
Climate and weather are two of the main key factors influencing fire regime and they have a number o...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
In Mediterranean areas, some studies suggest universal increases in fire frequency due to climatic w...
Spatio-temporal clusters in 1997-2003 fire sequences of Tuscany region (central Italy) have been ide...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–time...
This paper aims at detecting spatio-temporal clustering in fire sequences using spacetime scan stati...
Temporal variation of spatial clustering in fire data recorded from 1997 to 2003 in Tuscany region, ...
Spatial clustering in fire data recorded from 1997 to 2003 in an area of central Italy has been deep...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
This technical note aims to exemplify the potential of annual time series of wildfire geodatasets to...
Fire ignitions tend to be aggregated in time and space creating a clustered spatio-temporal pattern ...
This research note aims to exemplify the potential of annual time series of wildfire geodatasets to ...
Climate and weather are two of the main key factors influencing fire regime and they have a number o...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
In Mediterranean areas, some studies suggest universal increases in fire frequency due to climatic w...
Spatio-temporal clusters in 1997-2003 fire sequences of Tuscany region (central Italy) have been ide...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–time...
This paper aims at detecting spatio-temporal clustering in fire sequences using spacetime scan stati...
Temporal variation of spatial clustering in fire data recorded from 1997 to 2003 in Tuscany region, ...
Spatial clustering in fire data recorded from 1997 to 2003 in an area of central Italy has been deep...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
This technical note aims to exemplify the potential of annual time series of wildfire geodatasets to...
Fire ignitions tend to be aggregated in time and space creating a clustered spatio-temporal pattern ...
This research note aims to exemplify the potential of annual time series of wildfire geodatasets to ...
Climate and weather are two of the main key factors influencing fire regime and they have a number o...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
In Mediterranean areas, some studies suggest universal increases in fire frequency due to climatic w...