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Analysis of temperature maps of waterbodies obtained from ASTER TIR images
No full textThermal water pollution is a highly relevant issue to which increasing attention is being paid. Satellite remote sensing represents a useful tool for the mointoring and study of the temperatures of waterbodies. The purpose of this work is to define a methodology for the analysis of the surface temperature maps of coastal waterbodies and watercourses from satellite images for quality assessment and for regulatory purposes. Three different procedures are developed in order to study the temperature field of waterbodies, to extract the temperature profile at a fixed distance from the coastline and to analyse the cross sections of the watercourses as prescribed by the law. Extraction and analysis of surface temperature patterns are undertaken using image segmentation techniques. This work also represents a first test of the advantages given by the Sharpening Water Thermal Imagery (SWTI) algorithm, which improves the spatial resolution of Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images from 90 to 30 m. The developed procedures and the SWTI algorithm are applied to ASTER images acquired on the lagoon of Venice and on the delta of the Po River. Statistical parameters and temperature profile are extracted in order to verify compliance with legal limits. The use of the developed procedures enables the individuation and quantification of thermal anomalies such as industrial discharges both in the sea and in watercourses. © 2013 Copyright Taylor and Francis Group, LLC
IL MIGLIORAMENTO DELLA RISOLUZIONE SPAZIALE DI IMMAGINI SATELLITARI NELLE REGIONI DEL VISIBILE, VICINO INFRAROSSO E INFRAROSSO TERMICO
Get PDFIl telerilevamento, ossia l’acquisizione di immagini da sensori satellitari o aviotrasportati, è una tecnica sempre più utilizzata per il monitoraggio e il controllo ambientale. Un fattore limitante per molte applicazioni è senza dubbio la risoluzione spaziale. È in questo contesto che si inserisce questo lavoro di dottorato. Sono stati effettuati due studi distinti per il miglioramento della risoluzione spaziale di immagini satellitari: il primo relativo ad immagini acquisite nell’infrarosso termico, il secondo relativo al Pan-sharpening di immagini multi- e iperspettrali. Nel primo caso è stato applicato un nuovo algoritmo denominato SWTI (Sharpening Water Thermal Imagery) ad immagini ASTER ed immagini MODIS. L’algoritmo SWTI permette di migliorare la risoluzione spaziale di mappe di temperatura lungo le linee di costa e i tratti fluviali, dove la presenza di pixel misti (acqua-suolo) è un aspetto assai problematico. ASTER e MODIS sono due sensori allocati a bordo del satellite Terra. Nel caso delle immagini ASTER, l’algoritmo è stato applicato per migliorare la risoluzione spaziale da 90 a 30 metri su due immagini acquisite sulle aree della Laguna di Venezia e del Delta del fiume Po. In questo modo è stato possibile valutare l’efficacia dell’algoritmo e definire una metodologia per l’analisi di mappe di temperature superficiali delle acque costiere e dei corsi d’acqua a fini normativi. Nello studio sono state anche inserite immagini acquisite dal sensore MODIS poiché sono gratuite e a libera disposizione per tutti gli utenti, inoltre i dati sono forniti in continuo con una completa copertura del globo ogni 1-2 giorni. L’algoritmo ha permesso di migliorare la risoluzione spaziale delle immagini nel TIR da 1000 a 250 m. Le aree di applicazione sono state le medesime delle immagini ASTER in maniera da poter usare queste ultime come confronto. Il secondo studio è parte del progetto dell’Agenzia Spaziale Italiana denominato “ASI-AGI” (Analisi Geofisiche Integrate). Questo progetto include lo studio di una nuova piattaforma, PRISMA, che consiste in un sensore iperspettrale (HS) accoppiato ad un sensore pancromatico (PAN). Le bande iperspettrali hanno una risoluzione spaziale di 30 m e coprono un range spettrale tra 0.4 e 2.5 μm. La banda pancromatica invece ha una risoluzione spaziale di 5 metri e copre un range spettrale tra 0.4 e 0.75 μm. Lo studio si è concentrato sullo sviluppo e l’implementazione di tecniche di pan-sharpening per le immagini PRISMA. Queste consistono nell’iniezione dell’informazione spaziale dell’immagine pancromatica all’interno dell’immagine iperspettrale in modo da ottenere un’immagine sintetica che contenga il dettaglio spaziale dell’immagine PAN ed il dettaglio spettrale dell’immagine HS. Innanzitutto le immagini sono state simulate tramite immagini MIVIS, Quickbird e AVIRIS, tre sensori iper- e multi-spettrali con caratteristiche simili a PRISMA. Poi sono stati testati diversi metodi di fusione presenti in letteratura in modo da identificare i più idonei in termini di conservazione del dettaglio spaziale e spettrale. Sono stati testati algoritmi standard quali le componenti principali, la trasformata Gram-Schmidt, e algoritmi wavelet come la DWT (Discrete Wavelet Transform) e il metodo “à trous”. Per valutare la qualità dei metodi di fusione sono stati utilizzati diversi parametri numerici come RMSE (Root Mean Square Error), ERGAS (“Erreur Relative Globale Adimensionnalle de Synthèse”), coefficienti di correlazione, ecc. I risultati sono stati spesso contraddittori, la valutazione della qualità della fusione è infatti un problema tuttora aperto. Quindi si sta sviluppando un nuovo protocollo per valutare il mantenimento dell’informazione spaziale e spettrale.Spaceborne and airborne remote sensing plays a key role in environmental monitoring, since it allows to monitor in near real time large surfaces. The main limiting factor of remote sensed data is the spatial resolution (pixel size). This PhD work fits into this context. Two separate studies were carried out for the improvement of the spatial resolution of satellite images: the first based on images acquired in the thermal infrared region, the second related to the pan-sharpening of multi- and hyper-spectral images. In the first case a new algorithm called SWTI (Sharpening Water Thermal Imagery) has been applied to ASTER and MODIS images. SWTI is devoted to the sharpening of temperature maps of water surfaces along coastlines and of watercourses, where the presence of mixed (water –soil) pixels is a very problematic aspect.
ASTER and MODIS are two sensors located on the Terra satellite. In the case of ASTER, the algorithm was applied to improve the spatial resolution of remote data from 90 to 30 meters on the areas of the Lagoon of Venice and the Po River Delta. These applications have been used to evaluate not only the effectiveness of the algorithm but also to define a methodology for the analysis of the surface temperature maps of coastal waterbodies and watercourses for quality assessment and for regulatory purposes. MODIS images were also included in the study as they are freely available to all users, and furthermore the data are provided continuously a complete coverage of the globe every 1-2 days. SWTI in this case has allowed to improve the spatial resolution of the images in the TIR bands from 1000 to 250 meters. The areas of application are the same of ASTER images in order to be use the latter as a comparison. The second study is part of the Italian Space Agency project “ASI-AGI” (Analisi Geofisiche Integrate). This project includes the study of a new platform, called PRISMA, consisting of an hyperspectral sensor (HS) and a panchromatic sensor (PAN). Hyperspectral channels have a spatial resolution of 30 m and cover a spectral range from 0.4 to 2.5 μm. Panchromatic channel has a spatial resolution of 5m and cover a spectral range from 0.4 to 0.75 μm. The study is concerned with the development and implementation of data fusion techniques for PRISMA images, in particular the field of application of data fusion usually known as pan-sharpening. This is the synthesis of hyperspectral images to the higher spatial resolution of the panchromatic image. The fused HS images should be as close as possible to those that would have been observed if the corresponding sensors had the spatial resolution of the panchromatic sensor. Firstly, PRISMA images have been simulated using images from MIVIS, Quickbird and AVIRIS, three multi- or hyper-spectral sensors with spatial and spectral characteristics similar to PRISMA. Then several existing fusion methods have been tested in order to identify the most suitable for the platform PRISMA in terms of spatial and spectral information preservation. Both standard and wavelet algorithms have been used: among the former there are PCA (Principal Component Analysis), HIS (Intensity Hue Saturation), and Gram-Schmidt transform, and among the latter are DWT (Discrete Wavelet Transform) and the “à trous” wavelet transform. Several numerical parameters have been used to assess the quality of the image fusion methods, such as RMSE (Root Mean Square Error), ERGAS (“Erreur Relative Globale Adimensionnalle de Synthèse”), correlation coefficients, and histogram based metrics.. The results, however, were often contradictory and the quality assessment of pan-sharpened HS images is still an open problem. Thus currently a new protocol is under development to evaluate the preservation of spatial and spectral information in fusion methods
Estimation of subpixel MODIS water temperature near coastlines using the SWTI algorithm
No full textSatellite derived water surface temperature maps are widely used in many environmental studies and applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) is among the widely used sensors in this field and sea surface temperature (SST) is one of the standard quantities derived from MODIS imagery. However, MODIS SST maps have limited applications in near-shore and coastal environments due to inadequate spatial resolution of 1km. This problem means that the MODIS pixels closer than 1km from the shore are mixed pixels, i.e. they include by both water and land, and must be discarded from the SST map. In this work SWTI (Sharpening Water Thermal Imagery) methods were applied to MODIS thermal imagery for the first time. The information required by SWTI regarding cover fractions and perpendicular vegetation index was obtained from the MODIS images in the Visible-Near Infrared bands at a spatial resolution of 250m. In this way, the SST MODIS maps were extended to a minimum distance of 250m from the shore. The SWTI results were evaluated using as a reference the SST computed from two ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images acquired simultaneously to the MODIS images and covering the same areas. The applied validation methodology provides an evaluation of the deviations introduced by SWTI separated from the pre-existing differences between MODIS SST and ASTER SST upscaled to 250m. For sea coast environments, SWTI was able to compute the SST of more than 80% of the pixels close to the shore at a spatial resolution of 250m. This represents an increase of 67% compared to the number of pixels obtainable using a simple downscaling method based on polynomial interpolation; in areas with lagoons and estuaries the increases were +70% and +60% respectively. The ASTER SST comparison showed that the SST bias and the unsystematic deviation introduced by SWTI were S≤0.45K and σ(εS)≤0.88K respectively, corresponding to a total deviation TD≤0.97K. SWTI is written in the IDL language and could be adapted for automatic application to MODIS images
Analisi di mappature termiche di acque costiere e corsi d’acqua ottenute da immagini ASTER
No full textThe ASTER sensor is, currently, the main radiometer that acquires information in the Thermal Infrared (TIR) region with a spatial resolution of 90 m. The purpose of this work is to develop a working methodology for the analysis of water temperature obtained from ASTER images. Images were initially processed with an algorithm that improves spatial resolution from 90 m to 30 m using information drawn from the Visibile-Near infrared (VNIR) ASTER bands. Then data were analyzed and classified with an object-oriented approach. Specific procedures were developed in order to automate the monitoring process and to better interpret and display water temperature of the analyzed images. The studies were performed both on images at 90 m and at 30 m (computed with the algorithm for improving the spatial resolution). In this way it was possible to test the effectiveness and validity of the algorithm. For example, watercourses in the image at 90 m were barely visible while in the image at 30 m can be easily analyzed. This study is not concluded: the procedures will be soon applied to a wider range of case studies. Thus it will be possible to verify the versatility of the procedures themselves, and the advantages from the use of the algorithm for improving the spatial resolution
Miglioramento della risoluzione spaziale di immagini TIR MODIS su aree costiere
No full textThermal mapping of water bodies is an highly relevant tool for the study of thermal pollution, an issue to which increasing attention is paid. Remote sensing is an useful tool for monitoring large surface in near real time, but the main limiting factor is the spatial resolution. In this work it is shown the spatial improvement of MODIS thermal imagery on coastal water obtained with the SWTI (Sharpening Water Thermal Imagery) algorithm that allows to increase spatial resolution from 1 km to 250 m. SWTI is applied to two MODIS images, acquired on the lagoon of Venice and the delta of the Po river. As a reference we use a couple of ASTER images acquired simultaneously to the MODIS images and on the same areas. The root mean square errors computed excluding outliers are lower than 1.5 K that can be considered satisfactory when compared with the ASTER and MODIS temperature accuracies
The new Unimore interdisciplinary teaching on transversal sustainability skills
Get PDFThe global situation of the Covid-19 pandemic has changed several aspects of University life and management. In this context, the University of Modena and Reggio Emilia (Unimore) has introduced a new course for all of its students called "Transversal Skills on Sustainability". This course consists of 13 Modules offered by the various Unimore Departments to address the issue of Sustainability at 360 degrees. Each Department offers a thematic module concerning Sustainability in its own field of study and research. The course ranges from engineering issues with renewable energy, waste, air quality, to economics and sustainable finance. In addition, the course deals with issues related to sustainability in the medical, chemical and legal fields and many others. In this first year of delivery, this teaching has proven to be highly appreciated among students. Over 950 students have enrolled in teaching for the 2020/2021 academic year. Enrolled students come from all areas of the university: there are students of engineering, geology, economics, chemistry, but also of medicine, pharmacy, and many others.Keyword: Education, Sustainability, Multidisciplinary, global approac
Soil salinization assessment on Iraq using satellite remote sensing imagery
No full textSoil salinization is a form of topsoil degradation due to the formation of soluble salts at deleterious levels. This phenomenon can seriously compromise vegetation health and agricultural productivity, and represents a worldwide environmental problem. Remote sensing is a very useful tool for soil salinization monitoring and assessment. In this work we show some results of a study aimed to define the most suitable remote sensing methodologies for soil salinity assessment in Iraq. This activity is part of the Strategies for Water and Land Resources in Iraq project. The satellite images used were acquired by the ETM+ and by the SPOT5 satellite sensors, in the Visible-Near Infrared electromagnetic region, and with spatial resolution of 30 m (ETM+) and of 10 m (SPOT5). The methods used for the investigation of bare soils and vegetation can be summarized in: pre-elaborations (atmospheric corrections, georeferentiation, reflectance computation); individuation of bare soils and of vegetated soils; analysis of the correlations between several surface quantities computed from the satellite images and soil salinity indicators; analysis of the suitability of these quantities for soil salinity classification of the images using for example class separability analysis, principal component analysis and vegetation indexes. The first results obtained indicate that some areas with soil salinization, in particular those with outcrop of salt at the surface, and different type of vegetation can be individuated. The work carried out until now shows that remote sensing images could be fruitfully used for the soil salinization characterization of the studied area, but the definition of the methodology would require a dataset of ground information that describes in detail the actual soil salinization
Preliminary analysis of urban surfaces for the characterizaͳ tion and the mitigation of the heat island effect
No full textThe urban heat island (UHI) phenomenon is an issue of growing interest and the subject of numerous studies. UHI is defined as the metropolitan area that is significantly warmer than its surrounding rural areas. UHI has significant impacts on the buildings energy consumption and outdoor air quality, therefore it is considered an important environmental topic. The most effective approaches to mitigate UHI include, among others, the albedo increase of materials used for manmade surfaces (e.g. pavements, roofs), the increment of vegetated areas (e.g. parks, flowerbed, gardens), the increment of water surfaces (e.g. ponds). The UHI mitigation results in a reduction of the energy consumption and in an improvement of outdoor air quality. A recent model study carried by Rossi et al. (CIRIAF, University of Perugia) correlated the increase of materials albedo with energy saving in terms of reduction of carbon dioxide emissions. Therefore surfaces characterization is an useful information for planning UHI mitigation actions. Albedo of different types of urban surfaces can be obtained from bibliographic data, from laboratory measurements or retrieved from spaceborne or airborne remote sensing data. This data reported surface reflectance for each band, from which albedo can be directly obtained. In this work, airborne remote sensing data have been used for UHI characterization and for the study of UHI mitigation. The area of interest is the city of Modena in the Emilia Romagna region (Italy). On this area four orthorectified images acquired in the electromagnetic regions of the visible and near-infrared by an airborne sensor with a spatial resolution of 2 meters are used. Using an object-oriented technique, the four images have been segmented and classified into categories representing different types of land cover significant for UHI: Cultivated Soils, Green Areas, Roads, Parking, Railways and Buildings. The "Buildings" class is further divided in pitched roofs made of tiles (typical buildings of the historical center of the city) and in flat roofs of industrial buildings with both bright and dark coverings. This information will be used in the model described above in order to study UHI mitigation. This study presents some preliminary results of the application of this methodology that will be developed in the upcoming years for the application to various sites of interest
A multi-temporal analyses of Land Surface Temperature using Landsat-8 data and open source software: The case study of Modena, Italy
Get PDFThe Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the anthropic causes of UHI. The UHI phenomenon has a negative impact on the life quality of the local population (thermal discomfort, summer thermal shock, etc.), thus investigations and analyses on this topic are really useful and important for correct and sustainable urban planning; this study is included in this context. A multi-temporal analysis was performed in the municipality of Modena (Italy) to identify and estimate the Surface Urban Heat Island (SUHI, strictly correlated to the UHI phenomenon) from 2014 to 2017. For this purpose, Landsat-8 satellite images were processed with Quantum Geographic Information System (QGIS) to obtain the Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). For every pixel, LST and NDVI values of three regions of interest (ROI, i.e., Countryside, Suburbs, and City Center) were extracted and their correlations were investigated. A maximum variation of 6.4 °C in the LST values between City Center and Countryside was highlighted, confirming the presence of the SUHI phenomenon even in a medium-sized municipality like Modena. The implemented procedure demonstrates that satellite data are suitable for SUHI identification and estimation, therefore it could be a useful tool for public administration for urban planning policies
Methods and metrics for the assessment of Pan-sharpening algorithms
No full textRecent remote sensing applications require sensors that provide both high spatial and spectral resolution, but this is often not possible for economic and constructive reasons. The "fusion" of images at different spatial and spectral resolution is a method widely used to solve this problem. Pan-sharpening techniques have been applied in this work to simulate PRISMA images. The work presented here is indeed part of the Italian Space Agency project “ASI-AGI”, which includes the study of a new platform, PRISMA, consisting of an hyperspectral sensor with a spatial resolution of 30 m and a panchromatic sensor with a spatial resolution of 5 m, for monitoring and understanding the Earth's surface. Firstly, PRISMA images have been simulated using images from MIVIS and Quickbird sensors. Then several existing fusion methods have been tested in order to identify the most suitable for the platform PRISMA in terms of spatial and spectral information preservation. Both standard and wavelet algorithms have been used: among the former there are Principal Component Analysis and Gram-Schmidt transform, and among the latter are Discrete Wavelet Transform and the “à trous” wavelet transform. Also the Color Normalized Spectral Sharpening method has been used. Numerous quality metrics have been used to evaluate spatial and spectral distortions introduced by pan-sharpening algorithms. Various strategies can be adopted to provide a final rank of alternative algorithms assessed by means of a battery of quality indexes. All implemented statistics have been standardized and then three different methodologies have been used to achieve a final score and thus a classification of pan-sharpening algorithms. Currently a new protocol is under development to evaluate the preservation of spatial and spectral information in fusion methods. This new protocol should overcome the limitations of existing alternative approaches and be robust to changes in the input dataset and user-defined parameters
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