305,171 research outputs found
Improved MSG-SEVIRI images cloud masking and evaluation of its impact on the fire detection methods
No full textOne 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
Assessment of the fire detection limits using SEVIRI/MSG sensor
No full textForest 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)
Prompt Estimation of the Forest Fires Potential Dangerouness from Geostationary Satellite Data by Using the SFIDE system
No full textQuality 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
No full textThis 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
Continuous Monitoring of Forest Fires in Mediterranean Area Using MSG
No full textForest fires represent one of the main factors of degradation and destruction of the Italian forest heritage. The phenomenon occurrence has increased in the last years from the average of 6426 fires per year in the period 1970-1980, corresponding to a forested area of about 503,000 ha, to 11164 fires in the period 1990-2000, involving 553,000 ha
Estimation of the Burned Biomass Based on the Quasi-Continuous MSG/SEVIRI Earth Observation System
No full textThe estimate of the burned biomass starts from the computation of the FRP (Fire Radiative Power) that is the radiative power released by the fire. By integrating this quantity in the time it is possible to estimate the FRE (Fire Radiative Energy) and the burned biomass, if coefficients providing the burning efficiency of the vegetation interested by the fire are available. The FRP has been estimated by following three different approaches: the method proposed for the MODIS sensor, based on the eighth power of the brightness temperature of the fired pixel times a suitable coefficient; or by using the hypothesis that the fire size and its burning temperature can be computed by means of the Dozier approach and estimating the FRP by using the Stefan-Bolzmann relationship; or avoiding the computation of the brightness temperature of the fired pixel, by using the approach proposed by Wooster, in which the spatial resolution of the satellite image and the fired pixel emitted radiance are considered. Due to the high temporal frequency of the SEVIRI observations, the integration with the time of the FRP (computed every 15 min) can be carried out allowing to estimate the total energy released by the fire (FRE) and possibly the amount of burned biomass (BB). The paper aims at analyzing the suitability of this approach by focusing on the Sardinia region (Italy). The availability of the sizes of burned areas, provided by the Corpo Forestale e di Vigilanza Ambientale of the Sardinia region, allows to check the significance of the retrieved BB value. ©2009 IEEE
Texture Analysis on Time Series of Satellite Images with Variable Illumination Conditions and Spatial Resolution
No full textVersatility of the Mathematical Morphology to Detect any Kind of Target on High and Medium Resolution Images
No full textChange detection analysis on time series of satellite images with variable illumination conditions and spatial resolution
No full textVery recently satellite systems for remote sensing are required to provide images with a spatial and temporal resolution suitable to be applied for disaster management. High resolution (HR) satellite imagery can provide a good insight into the magnitude of a disaster and a detailed assessment of the damage. To meet these objectives, HR imagery has to be collected immediately after the disaster and precisely in the areas that have been damaged by the event. Presently, space based remote sensing systems result unsuitable to provide useful information when disastrous events require simultaneously high temporal and spatial resolutions. Furthermore, due to the technological limits of the transmission systems, a very high resolution is usually coupled with a reduced sensor swath. This means that the observation can be carried out when the area to be imaged is known. Low-resolution satellites (e.g. geostationary satellite) could also provide, in principle, some information with the required promptness in presence of event characterized by sudden temperature increases (fires, explosions, volcanic eruption, etc). The University of Rome (Centro di Ricerca Progetto San Marco) is studying the suitability of a satellite based system able to monitor national borders and/or given regions of the Earth in a quasi-continuous way with an adequate spatial resolution. To meet this requirement, the so-called Multi-Stationary (MS) orbits have been introduced. A constellation of few (4) satellites located on this kind of orbits allows a quasi-continuous monitoring of a selected region of the Earth. This paper is devoted to assess the impact of the variability of the images spatial resolution and illumination conditions on change detection methods based on a time-series of images. ©2007 IEEE
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