Improved MSG-SEVIRI images cloud masking and evaluation of its impact on the fire detection methods

One of the most important factors responsible of the firedetection algorithms fail is represented by the inaccurate cloud detection methods. In fact, the cloud-contaminated pixels are often associated with false fire pixel because of the brightness temperature increase in the mid-infrared channel. On the other hand an incorrect cloud masking could hide a real fire pixel, especially at the borders of clouds. Together with, the SEVIRI images EUMETSAT provides its own cloud mask (CLM product). This mask is computed by making full use of the MSG-SEVIRI spectral channels. Among the 12 channels, only channels 8 (IR 9.7) and 12 (HRV) are not included in the cloud detection and analysis. Due to the particular application for which CRPSM is using SEVIRI images, detection of fire at its early stage (sizes lower than 0.1 ha), a high sensitivity to changes in the radiance measured by the sensor in channel 4 (3.9 μm) is required. Since the presence of a cloud covering only a fraction of the pixel (∼4x4 km at mid latitude) can produce an increase in the estimated brightness temperature, in such channel, capable to provoke a false alarm we decided to use also channel 12 in the cloud detection algorithm. Thus, in order to improve the cloud masks provided by EUMETSAT a new methodology has been introduced. The approach, is firstly based on the application of the HRV channel during daytime. This paper aims to describe the cloud detection method and to present the results of the comparison with the CLM-EUMETSAT product as well as to assess the impact of the new process in the fire detection method. ©2008 IEEE

Quality assessment of the fire hazard forecast based on a fire potential index for the Mediterranean area by using a MSG/SEVIRI based fire detection system

This paper is devoted to describe the activity carried out by CRPSM (Centro di Ricerca Progetto San Marco) in the framework of the SIGRI (Italian acronym for Integrated System for Fire Risks Management) project. This project aims to develop a system, based on satellite data, able to support operationally the activities of users like Italian Civil Protection Agencies or Fire Dept. involved in fighting wild fires. In particular, the system should be able to support all the phases in which a fire fighting activity can be distinguished, namely: Territory management and resources dislocation (fire risk indices), Fires detection and monitoring, Damage assessment (burned areas and emissions in atmosphere). This paper presents the results obtained in the process of assessing the quality of a fire hazard forecast based on a Fire Potential Index especially designed for the Mediterranean areas. This quality assessment is carried out comparing the daily computed indices with the fire distribution obtained by using a fire detection algorithm based on SEVIRI/MSG images. In fact, using a fire detection algorithm (SFIDE, System for Fires Detection), recently proposed by the authors, a despite of its low spatial resolution, the SEVIRI system is able to reveal, at latitudes corresponding to Italy, fires covering an area of the order of 0.1 ha. The Fire Potential Index (FPI) is one of the most suitable to be computed by using satellite data even if ancillary information are still needed. The computation of this index requires: the estimate of the Relative Greenness, the evaluation of the leaves humidity, the preparation of vegetation fuel maps. Among the parameters needed to compile this index the fuel type map is particularly crucial. In fact, accurate maps of this kind are not available for the Italian territory. Then, first of all, using Corine Land Cover and other available vegetation maps, medium resolution satellite images and "in situ" observations CRPSM carried out the development of these maps for a couple of Italian regions where the summer wild fires problem has higher incidence. © 2007 IEEE

Assessment of the fire detection limits using SEVIRI/MSG sensor

Forest fires represent the main cause of forest degradation in Italy and in the Mediterranean area countries. This phenomenon, progressively increasing, reached an average of 11000 fires per year in the period 1990-2000 with the destruction of 553,000 ha of vegetated areas in the Italian peninsula. It has high relevance also for other countries in the region such as Spain, Portugal, Greece, France. Damages caused by forest fires have a direct economic impact related to the cost of burned wood, and the cost of the activities of prevention, firefighting and recover of burned areas. Less easy is the estimate of the economic impact of forest loss as part of the eco-system (reduction of the hydro-geological defenses, spoiling of tourist and landscape attractions, etc.). An efficient way to manage this problem involves an observation system able to provide a prompt detection and monitoring of fires and a synoptic view of the area of interest Thus, satellites seem to be the ideal instrument for this purpose, even if the temporal frequency of the observations is generally still a problem. In several previous paper the capability of setting up an early fire detection system using the sensor SEVIRI (Spinning Enhanced Visible and Infrared Imager) on board of the geostationary satellite MSG (Meteosat Second Generation) has been demonstrated. The present paper aims at assessing the limits of the SEVIRI sensor in detecting fires taking into account the spatial resolution of this sensor and the new algorithms especially developed to exploit its temporal resolution characteristics. The assessment of the limits of this sensor performances will be obtained mainly comparing its results with those obtainable from higher resolution sunsynchronous sensor data (MODIS and ASTER)

Continuous Monitoring of Forest Fires in Mediterranean Area Using MSG

Fires represent one of the main factors of degradation and destruction of the Mediterranean forest heritage. According to fire-fighting agencies, a satellite-based fire-detection system can be considered operationally useful for Mediterranean countries when fires with a minimum extent of 1500 m2 can be detected with a temporal resolution of 30 min. In fact, such a system should be able to detect fires at their first stage when it is possible to extinguish them more easily. The Centro di Ricerca Progetto San Marco has been analyzing for several years the possibility of using images acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) for this purpose. A new processing approach exploiting the increase in both spatial and temporal resolution (15 min) with respect to previous Meteosat systems is described in this paper. The idea is based on the use of a change detection technique to maximize the detection capabilities of the system in spite of its limited spatial resolution. This technique consists of comparing two or more images acquired at 15-min intervals, for which any temperature change can be attributed to fast dynamic phenomena, such as fires, when natural changes are modeled and removed. An assessment of the performances of this algorithm is carried out comparing its results with the report made available by Italian fire-fighting agencies and with fire products based on higher resolution sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS)

Application of Mathematical Morphology to Automatically Extract roads on Radar Images

The new constellation of remote sensing satellite COSMO/SkyMed will guarantee a combination of spatial and temporal resolution never reached by previously systems. The full exploitation of this system can allow the development of new applications, like these aiming at providing insight into the magnitude of a disaster and a detailed assessment of the damages as required by first responders for planning relief actions. The problem posed by the necessity of processing a huge number of images looking for given objects cannot be afforded by using visual approaches. This paper aims at describing the results obtained by applying some algorithms able to fully exploit the performances of the COSMO constellation. The technique herein described represent a generalization to radar images of the methods successfully applied to optical data. The techniques we are referring to are based on Mathematical Morphology and have been developed in the mainframe of the EU funded Network of Excellence (NoE) GMOSS (Global Monitoring for Stability and Security). In that case this technique has been applied to the problem of detecting objects, belonging to very different contexts, like dwelling units in refugee camps, roads of complex shapes and different background, main structures in nuclear plants, etc. In particular, techniques able to automatically: extract mademan structures, which could be present in mosaic of images, detect and counting dwelling units in refugee camps, extract roads of complex shape or for monitoring nuclear plants, have been developed. The purpose of the present study is the assessment of the suitability of the same mathematical morphology techniques for detecting automatically roads/streets, verifying their state after a disastrous event, in both urban and extra-urban areas on radar images. Actually the objects of interest are detected by exploiting mathematical morphology and some ancillary information regarding the shape and size of the required object. ©2009 IEEE