Add to ORKGstatistical tool suited to reveal clustering behaviour in point processes. The obtained results show the presence of daily and annual periodicities, superimposed onto a scaling be-haviour, which features the sequence of wildfires as a fractal time process with a rather high degree of time-clusterization of the events
The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is...
The concept of fractals provides a means of testing whether clustering in time or space is a scale-i...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
This paper aims at detecting spatio-temporal clustering in fire sequences using spacetime scan stati...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–time...
The paper deals with density-based clustering of events, i.e. objects positioned in space and time, ...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Many objects in space can best be modeled statistically by using point processes. Examples are fires...
AbstractIt has been found that many systems are characterized by scaling behavior. Time-scaling scal...
Euclidean analytical tools for quantifying the patchiness of complex natural patterns such as wild ...
Abstract. Fractal fluctuation analysis is applied to ground-based data during quiet times and during...
A temporal point process is a sequence of points, each representing the occurrence time of an event....
Spatial clustering in fire data recorded from 1997 to 2003 in an area of central Italy has been deep...
The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is...
The concept of fractals provides a means of testing whether clustering in time or space is a scale-i...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
This paper aims at detecting spatio-temporal clustering in fire sequences using spacetime scan stati...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–time...
The paper deals with density-based clustering of events, i.e. objects positioned in space and time, ...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Forest fire sequences can be modelled as a stochastic point process where events are characterized b...
Many objects in space can best be modeled statistically by using point processes. Examples are fires...
AbstractIt has been found that many systems are characterized by scaling behavior. Time-scaling scal...
Euclidean analytical tools for quantifying the patchiness of complex natural patterns such as wild ...
Abstract. Fractal fluctuation analysis is applied to ground-based data during quiet times and during...
A temporal point process is a sequence of points, each representing the occurrence time of an event....
Spatial clustering in fire data recorded from 1997 to 2003 in an area of central Italy has been deep...
The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is...
The concept of fractals provides a means of testing whether clustering in time or space is a scale-i...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...