1,720,973 research outputs found
Modello di dati GIS per studi di qualità dell’aria basati su simulazioni modellistiche della dispersione di inquinanti
No full textA geographic data model has been set up, to support display and analysis of air dispersion simulations. The goal was to create a global environment where to manage input data to the model and model results, to perform spatial analyses and to evaluate the risk coming from the modelled pollution field, for people (exposure) and environment. The GIS model was also set up to include epidemiological data to be correlated with exposure estimates. The geographical database has been tested by populating it with data for a case study located on the industrial area of Terni, where air dispersion simulations were performed. The data model will be the basis for the GIS aimed to manage information coming from the LIFE+2009 Project "Population Exposure to PAH" (EXPAH), recently approved
Miglioramento della spazializzazione di dati satellitari mediante l’uso di misure a terra
No full textThis work shows a procedure for the evaluation of the spatial distributions of chemical-physical parameters measured by ground stations and satellite remote sensing. The description of the procedure is focused on the measures of atmospheric parameters characteristic of air quality and on the MODIS sensor, but it can be used for other cases also. The evaluation of the spatial distributions is done following two main approaches: in the first the distributions are computed separately for the two data sets; in the second, which is the principal subject of this work, the spatialisation of the remote sensing data set is done by using information extracted by ground measurements also. The procedure has been developed and provided with a graphic user interface in IDL
Impiego di dati MODIS in supporto alla valutazione del rischio associato a microrganismi patogeni in ambiente acquatico
No full textWe show the first results of a study aimed to set simplified procedures and methodologies to use MODIS data and derived products for activities of sea water control and monitoring. The research is carried out in the framework of a project supported by the Ministry for Health, concerning the development of criteria to evaluate the environmental and sanitary risk due to pathogenic micro-organisms in water environment. The remote sensing team acts in support of the biologic research teams that study the environmental conditions that favour the development and growth of such micro-organisms. MODIS data are selected, downloaded, organized in an easy-to-read format and analyzed by integrating with measurements performed by the other teams, in a georeferenced data-base. The goal of this study is to make the great information content of MODIS data available for operational use, providing public organizations in charge of environmental risk management with an operative tool, easy to use and at low cost, to support conventional techniques
Estrazione di parametri superficiali da immagini ETM+ per modelli di dispersione di inquinanti in atmosfera
No full textWe present the first results of a study aimed to use data retrieved from remote sensing as input to pollutants atmospheric dispersion models. These models require data on the local meteorological conditions and on the physical characteristics of the surface to model the dynamic of the first atmospheric layers. The surface parameters are usually assigned to a land use map on the basis of tables of reference mean values. Remotely sensed data can give a direct, up-to-date, spatially continuous information on some of these parameters. In this work we extract an empirical relation to calculate the surface albedo from Landsat 7 ETM+ images; the results are compared with reference mean values available from literature. The effects of the found differences on the model are evaluated by comparing maps of net radiation calculated with the equation used in the SPRAY dispersion model used at ISPESL
Impiego di immagini telerilevate per modelli di dispersione di inquinanti in atmosfera
No full textIn many cases, atmospheric dispersion models require in input maps of surface parameters, as landcover, usually extracted from the CLC2000 dataset, and albedo. But, CORINE data do not describeseasonal changes and, some times, require upgrades. In this work a procedure, based on remote sensingdata, for the improvement of CORINE data and for albedo assessment is shown. The procedure was setfor the ARIA INDUSTRY dispersion model, and in the final part of the paper, a case study is shown
Dati di copertura nuvolosa SEVIRI-MSG per i modelli di dispersione atmosferica degli inquinanti
No full textThe fraction of cloud cover is very important for the atmospheric turbulence parameterization schemes adopted by many models of atmospheric dispersion of pollutants. This information is required when there are no direct measurements of net flow of radiation at the surface. In these cases, the net radiation is estimated from measures of cloud cover and incident solar radiation flux, or it is calculated directly using semi empirical and astronomical relationships which, in turn, require cloud cover. This work evaluated the usability of the cloud cover Cloud Analysis Images (CLAI) extracted from the images obtained by the sensor SEVIRI - MSG as input data to software for simulation of the dispersion of pollutants in the atmosphere Air Industry. The primary assessment of this experiment is the comparison between the values of net radiation measured at the ground with those calculated using the cloud cover extracted from CLAI. As a further experiment, is shown an application of the dispersion model, set to use the cloud cover CLAI; the concentration maps obtained were compared with those obtained using similar measures of solar radiation. This study highlights that data from MSG-SEVIRI cloud cover can effectively compensate for the lack of measures of solar radiation on the ground, although by that parameter's importance in modeling the dispersion of pollutants has not yet been well investigated and is still under study
Remote sensing for landfill investigations
No full textREMOTE SENSING IS APPLIED FOR LANDFILL INVESTIGATIONS
TECNICHE DI INVERSIONE PER LA STIMA DELL"EMISSIONE DI ANIDRIDE SOLFOROSA DELL"ETNA DALLE IMMAGINI TELERILEVATE DAL MIVIS NELL"INFRAROSSO TERMICO
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SIMULAZIONI DI IMMAGINI ASTER DA IMMAGINI MIVIS PER LA STIMA DEL FLUSSO DI SO2 DELL"ETNA
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Improving of the thermal mapping of coastal and river waters obtained from satellite remote sensing
No full textThe temperature of coastal and river water is very important in various areas of environmental concern. Very often, the heat released by human activities in water bodies is classified as a pollutant and it is subjected to regulatory. Remote sensing images acquired by the satellite sensor ASTER could be a very valuable tool in this area. Nevertheless, the spatial resolution (90 m) of this sensor in the thermal infrared is very important limiting factor for the compute of temperature of narrow watercourses or of coastal waters. In this work, an algorithm for the improvement of ASTER images acquired in the TIR based on information on the type of coverage of the area extracted from ASTER images acquired in the VIS-NIR and with spatial resolution varying between 15 m and 30 m. The algorithm produces a downscaling of the ASTER TIR images, from 90 m to 30 m, more complete than those obtainable by usual interpolation techniques. In this paper it is given a summary description of the structure of the algorithm followed by two applications on the coastal areas of the lagoon of Venice and the Po River delta
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