55 research outputs found
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
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
Prompt Estimation of the Forest Fires Potential Dangerouness from Geostationary Satellite Data by Using the SFIDE system
No full textImproved 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
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
Versatility of the Mathematical Morphology to Detect any Kind of Target on High and Medium Resolution Images
No full textApplication of Mathematical Morphology to Automatically Extract roads on Radar Images
No full textThe 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
Change 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
Fire damage assessment in Sardinia: the use of ALOS/PALSAR data for the management of post-fire effects
No full textFires in the Sardinia Island are one of the most important environmental factors controlling the ecosystem ́s function and structure. The evaluation of fire effects by means of remote sensing is economically and practically the best way to assess fire damage, before going to the field. The use of alternative techniques for fire effects assessment is needed, in particular to characterize the biomass loss at the regional level. Radar remotely sensed data can provide great advantages with respect to optical sensors. The paper is devoted to show the results obtained by applying a semi-automatic algorithm to the images of the L-band SAR sensor PALSAR, on board of the ALOS satellite, for the estimate of the burned area. To assess the quality of the estimate, the radar based results have been compared with those obtained from optical data and ground based information
Osservazioni sulla dispersione dei fenicotteri (Phoenicopterus ruber roseus, Pallas, 1811) nati nelle lagune di Cagliari (1997-2000)
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