This paper aims at detecting spatio-temporal clustering in fire sequences using spacetime scan statistics, a powerful statistical framework for the analysis of point processes. The methodology is applied to active fire detection in the state of Florida (US) identified by MODIS (Moderate Resolution Imaging Spectroradiometer) during the period 200306. Results of the present study show that statistically significant clusters can be detected and localized in specific areas and periods of the year. Three out of the five most likely clusters detected for the entire frame period are localized in the north of the state, and they cover forest areas; the other two clusters cover a large zone in the south, corresponding to agricultural land and the pr...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–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...
Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been ide...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
Abstract. We analyse the spatio-temporal structure of wildfire ignitions in the St Johns River Water...
The paper deals with density-based clustering of events, i.e. objects positioned in space and time, ...
The spatio-temporal analysis of residential fires could allow decision makers to plan effective reso...
This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moder...
statistical tool suited to reveal clustering behaviour in point processes. The obtained results show...
This thesis develops and applies novel techniques for the study of complex data structures with appl...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...
This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan stat...
Abstract. This paper aims at detecting spatio-temporal clustering in fire sequences using space–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...
Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been ide...
The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1...
Abstract. We analyse the spatio-temporal structure of wildfire ignitions in the St Johns River Water...
The paper deals with density-based clustering of events, i.e. objects positioned in space and time, ...
The spatio-temporal analysis of residential fires could allow decision makers to plan effective reso...
This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moder...
statistical tool suited to reveal clustering behaviour in point processes. The obtained results show...
This thesis develops and applies novel techniques for the study of complex data structures with appl...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...
The spatial and temporal distribution of forest fires displays a complex pattern which strongly infl...
Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is ...