Remote sensing-based prediction of forest fire characteristics

Forest fires are a major ecosystem disturbance at global scale, put pressure on agencies in charge of citizens and infrastructure security and cause unvaluable human losses. Fires are controlled by multiple static and dynamic drivers related to topography, land cover, climate, weather, and anthropic activity. Among these, weather is an active...

Combining multi-spectral and thermal remote sensing to predict forest fire characteristics

Forest fires preparedness strategies require the assessment of spatial and temporal variability of fire danger. While several tools have been developed to predict fire occurrence and behaviour from weather data, it is acknowledged that fire danger models may benefit from direct assessment of live fuel condition, as allowed by Earth Observation...

Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements

Operational forest fire danger rating systems rely on the recent evolution of meteorological variables to estimate dead fuel condition. Further combining the latter with meteorological and environmental variables, they predict fire occurrence and spread. In this study we retrieved live fuel condition from MODIS multispectral measurements in...

Relating spatiotemporal patterns of forest fires burned area and duration to diurnal land surface temperature anomalies

Forest fires are a major source of ecosystem disturbance. Vegetation reacts to meteorological factors contributing to fire danger by reducing stomatal conductance, thus leading to an increase of canopy temperature. The latter can be detected by remote sensing measurements in the thermal infrared as a deviation of observed land surface...

Remote sensing evaluation of fire hazard: Towards operational tools for improving the security of citizens and protecting the environment

Forest fires are a threat for both the environment and the security of citizens. This is particularly relevant in the Mediterranean, where the population density is high, and long dry summers drive vegetation into fireprone conditions. Policy makers underline the key role of prevention over damage reparation, and indeed efforts are conducted at...

Remote sensing estimation of vegetation moisture for the prediction of fire hazard

Various factors contribute to forest fire hazard, and among them vegetation moisture is the one that dictates susceptibility to fire ignition and propagation. The scientific community has developed a number of spectral indexes based on remote sensing measurements in the optical domain for the assessment of vegetation equivalent water thickness ...

Fire risk assessment: The role of hyperspectral remote sensing

The increasing demand for effective forest fire prevention instruments has faced operational and future Earth observation instruments with the challenge of producing updated and reliable maps of vegetation moisture. Various empirical band-ratio indexes have been proposed so far, based on multispectral remote sensing data, that have been found to...