Giorgio Libertà

Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)

Fires are an integral component of ecosystem dynamics in European landscapes. However, uncontrolled fires cause large environmental and economic damages, especially in the Mediterranean region. On average, about 65000 fires occur in Europe every year, burning approximately half a million ha of wildland and forest areas; most of the burnt area, over 85%, is in the European Mediterranean region. Trends in number of fires and burnt areas in the Mediterranean region are presented in Fig. 1.

Chapter 8 Assessment of Forest Fire Impacts and Emissions in the European Union Based on the European Forest Fire Information System

An analysis on the number of forest fires and burned area distribution as retrieved by the European Forest Fire Information System (EFFIS) database is presented. On average, from 2000 to 2005 about 95,000 fires occurred annually in 23 European countries, burning almost 600,000 ha of forest land every year. Of these about two-thirds or 65,000 fires occurred in 5 European Union (EU) Mediterranean countries (France, Greece, Italy, Portugal, and Spain) where on average half a million hectares of forest land were burned every year. In addition, out of the 23 European countries, the total burned area was 86% within those 5 countries alone during the 6-year study period, and out of the 19 EU countries the total for the 5 countries was 96%. Estimates of atmospheric emissions of carbon dioxide (CO2) and other trace gases were done for the 2000–2005 period in which burned area maps were retrieved using remote sensing imagery, and then combined with fuel load and burning efficiency figures, to estimate the quantity of burned biomass. Emission factors were further used to estimate trace gas and aerosol emissions produced by vegetation fires. Fuel load was estimated based on values found in the literature and from existing land cover maps of Europe. Average burning efficiency and emission factors were retrieved from the literature. The results obtained show that the forest fires atmospheric emissions of the 23 European countries considered in this study ranged from 8.4 to 20.4 Tg of CO2/year.

Climate Impacts in Europe. The JRC PESETA II Project

The objective of the JRC PESETA II project is to gain insights into the sectoral and regional patterns of climate change impacts in Europe by the end of this century. The study uses a large set of climate model runs and impact categories (ten impacts: agriculture, energy, river floods, droughts, forest fires, transport infrastructure, coasts, tourism, habitat suitability of forest tree species and human health). The project integrates biophysical direct climate impacts into a macroeconomic economic model, which enables the comparison of the different impacts based on common metrics (household welfare and economic activity). Under the reference simulation the annual total damages would be around €190 billion/year, almost 2% of EU GDP. The geographical distribution of the climate damages is very asymmetric with a clear bias towards the southern European regions. More than half of the overall annual EU damages are estimated to be due to the additional premature mortality (€120 billion). Moving to a 2°C world would reduce annual climate damages by €60 billion, to €120 billion (1.2% of GDP).

Fire scar detection in Central Portugal using RADARSAT-1 and ERS-2 SAR data

A comparative study on backscatter returns from multi-temporal RADARSAT-1 and ERS-2 SAR data has been conducted on a fire-disturbed region of Central Portugal. Six images were examined to detect changes between forest and burnt forest areas. A local incidence angle normalization to 23/spl deg/ was applied to allow a comparison between scenes from different beam modes and SAR instruments. A number of widely distributed sample plots were chosen to characterize different vegetation classes. Both sensors were able to discriminate burnt and unburnt classes. However, no discrimination was possible between the three cover type classes considered, neither before nor after the fire. The similar response from both instruments was associated to the volumetric scattering produced on C-band by vegetation. Small differences in backscatter values can only be explained by the soil moisture changes between the dates in which the images were acquired.

Forest fire risk estimation from time series analisys of NOAA NDVI data

The values of the Normalized Difference Vegetation Index obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) have often been used for forestry application, including the assessment of fire risk. Forest fire risk estimates were based mainly on the decrease of NDVI values during the summer in areas subject to summer drought. However, the inter-annual variability of the vegetation response has never been extensively taken into account. The present work was based on the assumption that Mediterranean vegetation is adapted to summer drought and one possible estimator of the vegetation stress was the inter-annual variability of the vegetation status, as reflected by NDVI values. This article presents a novel methodology for the assessment of fire risk based on the comparison of the current NDVI values, on a given area, with the historical values along a time series of 13 years. The first part of the study is focused on the characterization of the Minimum and Maximum long term daily images. The second part is centered on the best method to compare the long term Maximum and Minimum with the current NDVI. A statistical index, Dynamic Relative Greenness, DRG, was tested on as a novel potential fire risk indicator.

Non-supervised method for early forest fire detection and rapid mapping

Natural hazards are a challenge for the society. Scientific community efforts have been severely increased assessing tasks about prevention and damage mitigation. The most important points to minimize natural hazard damages are monitoring and prevention. This work focuses particularly on forest fires. This phenomenon depends on small-scale factors and fire behavior is strongly related to the local weather. Forest fire spread forecast is a complex task because of the scale of the phenomena, the input data uncertainty and time constraints in forest fire monitoring. Forest fire simulators have been improved, including some calibration techniques avoiding data uncertainty and taking into account complex factors as the atmosphere. Such techniques increase dramatically the computational cost in a context where the available time to provide a forecast is a hard constraint. Furthermore, an early mapping of the fire becomes crucial to assess it. In this work, a non-supervised method for forest fire early detection and mapping is proposed. As main sources, the method uses daily thermal anomalies from MODIS and VIIRS combined with land cover map to identify and monitor forest fires with very few resources. This method relies on a clustering technique (DBSCAN algorithm) and on filtering thermal anomalies to detect the forest fires. In addition, a concave hull (alpha shape algorithm) is applied to obtain rapid mapping of the fire area (very coarse accuracy mapping). Therefore, the method leads to a potential use for high-resolution forest fire rapid mapping based on satellite imagery using the extent of each early fire detection. It shows the way to an automatic rapid mapping of the fire at high resolution processing as few data as possible.