Teresa J. Calado

Atmospheric conditions associated with extreme fire activity in the Western Mediterranean region

Active fire information provided by TERRA and AQUA instruments on-board sun-synchronous polar MODIS platform is used to describe fire activity in the Western Mediterranean and to identify and characterize the synoptic patterns of several meteorological fields associated with the occurrence of extreme fire activity episodes (EEs). The spatial distribution of the fire pixels during the period of 2003-2012 leads to the identification of two most affected sub-regions, namely the Northern and Western parts of the Iberian Peninsula (NWIP) and Northern Africa (NAFR). The temporal distribution of the fire pixels in these two sub-regions is characterized by: (i) high and non-concurrent inter- and intra-annual variability with maximum values during the summer of 2003 and 2005 in NWIP and 2007 and 2012 in NAFR; and, (ii) high intra-annual variability dominated by a prominent annual cycle with a main peak centred in August in both sub-regions and a less pronounced secondary peak in March only evident in NWIP region. The 34 EEs identified were grouped according to the location, period of occurrence and spatial configuration of the associated synoptic patterns into 3 clusters (NWIP-summer, NWIP-winter and NAFR-summer). Results from the composite analysis reveal similar fire weather conditions (statistically significant positive anomalies of air temperature and negative anomalies of air relative humidity) but associated with different circulation patterns at lower and mid-levels of the atmosphere associated with the occurrence of EEs in each cluster of the Western Mediterranean region.

Calibration of the Fire Weather Index over Mediterranean Europe based on fire activity retrieved from MSG satellite imagery

Here we present a procedure that allows the operational generation of daily maps of fire danger over Mediterranean Europe. These are based on integrated use of vegetation cover maps, weather data and fire activity as detected by remote sensing from space. The study covers the period of July–August 2007 to 2009. It is demonstrated that statistical models based on two-parameter generalised Pareto (GP) distributions adequately fit the observed samples of fire duration and that these models are significantly improved when the Fire Weather Index (FWI), which rates fire danger, is integrated as a covariate of scale parameters of GP distributions. Probabilities of fire duration exceeding specified thresholds are then used to calibrate FWI leading to the definition of five classes of fire danger. Fire duration is estimated on the basis of 15-min data provided by Meteosat Second Generation (MSG) satellites and corresponds to the total number of hours in which fire activity is detected in a single MSG pixel during one day. Considering all observed fire events with duration above 1h, the relative number of events steeply increases with classes of increasing fire danger and no fire activity was recorded in the class of low danger. Defined classes of fire danger provide useful information for wildfire management and are based on the Fire Risk Mapping product that is being disseminated on a daily basis by the EUMETSAT Satellite Application Facility on Land Surface Analysis.

A User-Oriented Simplification of the (

Remote sensing from spaceborne sensors combining near- and middle-infrared information has proved to be an efficient means to monitor the effects of vegetation fires. Burn-sensitive spectral indices, such as the (V, W) index system, have been developed and successfully applied for burned area discrimination. The (V, W) index system provides useful capability to discriminate burned pixels, but the elaborate numerical computations involved are a major drawback in operational applications. This letter presents a simplified algorithm to compute the approximate values of indices V and W. The methodology developed is tested in a region located in the Brazilian Cerrado using remote-sensed data from the MODIS instrument. The simplification allows performing burned area discrimination with the same quality as the original algorithm. The methodology may be extended to other sensors and different combinations of bands and opens new perspectives to the generation of synergic longterm databases of burned area.

V,W

Forested areas cover circa 38% of Continental Portugal and the observed increasing trend in the extent and severity of wildfires points to the need for accurate and timely knowledge of the total burnt area. The official fire database is the one provided by the Portuguese Forest Service (DGRF) and is based on information supplied by fire and forest services. Since 1990, maps of burnt areas have been yearly produced based on information from Landsat-TM. A recent study for the period 1984–1989 has pointed out severe discrepancies between ground- and satellite-based data, raising the need to devise procedures aiming to correct such discrepancies. The present work represents a first attempt to assess the potential of using NOAA/AVHRR imagery to assigning dates to burnt scars on end of season maps as the ones derived from Landsat-TM. We begin by degrading to the AVHRR scale a MODIS-based end of season map of burnt scars. Degradation was simply performed by computing the fraction of burnt MODIS pixels inside each AVHRR pixel. Then, we built up a neuro-fuzzy model that assigns to each AVHRR pixel the “possibility” of representing a burnt area. The model uses as input pixel values of AVHRR channel 2 and was trained using a composite of minimum values of that channel and the corresponding fractions of burnt MODIS pixels of the degraded end of season map. The model was then applied to individual AVHRR images and further refined in order to eliminate errors associated to contamination by clouds and water bodies, geo-rectification problems and dark backgrounds. It is shown that the refined model underestimated by 11% the total amount of burnt area as obtained from DGRF data and that the differences reduced to 1% when DGRF data were restricted to records greater than 100 ha. The model was then used to assign dates to burnt scars in the MODIS-based end of season map. Obtained results are quite encouraging since deviations (NOAA-MODIS) between –2 (–1) and +1 (0) days represent 85% (70%) of the total and may be attributed to differences in orbital times of passage of NOAA and TERRA/AQUA.

) Burn-Sensitive Vegetation Index System

An automated procedure is here presented that allows identifying and dating burned areas in Portugal using values of daily reflectance from near-infrared and middle-infrared bands, as obtained from the MODIS instrument. The algorithm detects persistent changes in monthly composites of the so-called (V,W) Burn-Sensitive Index and the day of maximum change in daily time series of W is in turn identified as the day of the burning event. The procedure is tested for 2005, the second worst fire season ever recorded in Portugal. Comparison between the obtained burned area map and the reference derived from Landsat imagery resulted in a Proportion Correct of 95.6%. Despite being applied only to the months of August and September, the algorithm is able to identify almost two-thirds of all scars that have occurred during the entire year of 2005. An assessment of the temporal accuracy of the dating procedure was also conducted, showing that 75% of estimated dates presented deviations between -5 and 5 days from dates of hotspots derived from the MODIS instrument. Information about location and date of burning events as provided by the proposed procedure may be viewed as complementary to the currently available official maps based on end-of-season Landsat imagery.