Tecniche integrate di Remote Sensing e GIS a supporto della stima del potenziale fotovoltaico su tetti in aree urbane

Le ultime linee guida approvate dal Governo Italiano per sostenere finanziariamente il fotovoltaico (PV) e lo sviluppo della produzione di energia solare (Quarto e Quinto Conto Energia, Gennaio 2012 e succ.), al fine di evitare il consumo di suolo in aree agricole o naturali, comprendono indicazioni specifiche che rendono più vantaggiosa l’installazione d’impianti su tetti o superfici di copertura di edifici. In questo contesto diventa importante, per una adeguata attività di pianificazione e monitoraggio del PV, la mappatura estensiva delle superfici a disposizione, coincidenti con i tetti e l’accurata valutazione del loro potenziale fotovoltaico. Dal momento che tali coperture si trovano soprattutto nelle aree urbane o industriali, in cui fattori come eterogeneità tridimensionale, albedo, torbidità atmosferica ed ombreggiamenti reciproci influenzano in modo significativo l’irraggiamento solare locale, è necessario tenere conto adeguatamente di questi elementi mediante una mappatura GIS tridimensionale ed avanzati strumenti di modellazione, in modo da stimare efficacemente la radianza solare disponibile a livello dei tetti. La metodologia implementata, basata su tecniche di telerilevamento e GIS, ha permesso di valutare e mappare la radiazione solare globale su tutti i tetti presenti nel territorio del Comune di Avellino. Partendo da dati di tipo LIDAR, è stato ottenuto in primo luogo il DSM di tutta l’area di interesse (~ 42 Km2), quindi il modello tridimensionale di ogni edificio da cui sono stati derivati i parametri geometrici di tutte le coperture. Per tenere conto della trasparenza atmosferica e della percentuale di radiazione solare (diffusa/diretta) sulle superfici di interesse, sono stati utilizzati i dati e gli strumenti applicativi presenti sul sito web PVGIS, sviluppato dalla UE. L’elaborazione finale, basata sull’utilizzo di strumenti GIS anche di tipo open source, ha permesso di ottenere le mappe di radianza solare e di potenziale PV per tutti i tetti presenti nell’area di studio.The last guidelines approved by Italian government to financially support the solar Photovoltaic (PV) Energy production development (Fourth and Fifth feed-in-scheme, January 2012 and later), in order to avoid soil consumption in agricultural or naturals areas, include specific indications for more advantageously funding the installations exploiting roofs or covers surfaces. In this context it becomes important, for a suitable PV planning and monitoring, the extensive mapping of the available surfaces extent, usually corresponding to covers and properly assessing their quality in term of PV potential. Since the covers are mainly located in urban or industrial areas, whose 3D heterogeneity, albedo, atmospheric turbidity and casting shadows significantly influence the local solar irradiance, it is necessary to suitably account for these distributed factors by means of GIS mapping and advanced modeling tools in order to provide realistic estimates of solar available radiance at roofs level. The implemented methodology, based on remote sensing techniques, has allowed to estimate and map the global solar radiance over all the roofs within Avellino municipality. Starting from LIDAR data, DSM of the entire area of interest (~42 Km2) has been firstly obtained; then the 3D model of each building and related cover has been derived. To account for the atmospheric transparency and the related time-dependent diffuse/direct radiation percentage on the area, data and tools from EU PVGIS web application have been also used. The final processing to obtain the solar radiance maps has been carried out using specific software modules available within commercial and open-source GIS packages

Decision Support System for smart urban management: resilience against natural phenomena and aerial environmental assessment

A new concept of Decision Support System (DSS) is presented. It is able to account for and support all phases of the risk analysis process: event forecast, prediction of reliable and accurate damage scenarios, estimate of their impact on Critical Infrastructures (CI), estimate of the possible consequences. It also provides an estimate of the consequences in terms of service degradation and of impact on citizens, on urban area and on production activities, essential for the mitigation of the adverse events. It can be used in two different modes, either in an operational mode (on a 24/7 basis) or in a simulation mode to produce risk analysis, setting up synthetic natural hazards and assessing the resulting chain of events (damages, impacts and consequences). Among the various possible external data sources an aerial, drone based one is presented. The system may capture both thermal and visual images of CI, processing them into 3D models or collect chemical pollutants concentrations for the monitoring of dangerous air quality due to catastrophic events such as volcano eruptions or large fires. The obtained models and the chemical data can be easily displayed within the framework of the DSS

Modeling Resilience in Electrical Distribution Networks

Electrical distribution networks deliver a fundamental service to citizens. However, they are still highly vulnerable to natural hazards as well as to cyberattacks; therefore, additional commitment and investments are needed to foster their resilience. Toward that, this paper presents and proposes the use of a complex simulation model, called reconfiguration simulator (RecSIM), enabling to evaluate the effectiveness of resilience enhancement strategies for electric distribution networks and the required resources to implement them. The focus is, in particular, on one specific attribute of resilience, namely, the readiness, i.e., the promptness and efficiency to recover the service functionality after a crisis event by managing and deploying the available resources rapidly and effectively. RecSIM allows estimating how and to what extent technological, topological, and management issues might improve electrical distribution networks’ functionality after the occurrence of accidental faults, accounting for interdependency issues and reconfiguration possibilities. The viability of implementing RecSIM on a real and large urban network is showcased in the paper with reference to the study case of the electrical distribution network (EDN) of Rome city

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

AbstractRisk assessment of urban areas aims at limiting the impact of harmful events by increasing awareness of their possible consequences. Qualitative risk assessment allows to figure out possible risk situations and to prioritize them, whereas quantitative risk assessment is devoted to measuring risks from data, in order to improve preparedness in case of crisis situations. We propose an automatic approach to comprehensive risk assessment. This leverages on a semantic and spatiotemporal representation of knowledge of the urban area and relies on a software system including: a knowledge base; two components for quantitative and qualitative risk assessments, respectively; and a WebGIS interface. The knowledge base consists of the TERMINUS domain ontology, to represent urban knowledge, and of a geo‐referenced database, including geographical, environmental and urban data as well as temporal data related to the levels of operation of city services. CIPcast DSS is the component devoted to quantitative risk assessment, and WS‐CREAM is the component supporting qualitative risk assessment based on computational creativity techniques. Two case studies concerning the city of Rome (Italy) show how this approach can be used in a real scenario for crisis preparedness. Finally, we discuss issues related to plausibility of risks and objectivity of their assessment

design of dss for supporting preparedness to and management of anomalous situations in complex scenarios

Decision Support Systems (DSS) are complex technological tools, which enable an accurate and complete scenario awareness, by integrating data from both "external" (physical) situation and current behaviour and state of functioning of the technological systems. The aim is to produce a scenario analysis and to guess identify educated the most efficient strategies to cope with possible crises. In the domain of Critical Infrastructures (CI) Protection, DSS can be used to support strategy elaboration from CI operators, to improve emergency managers capabilities, to improve quality and efficiency of preparedness actions. For these reasons, the EU project CIPRNet, among others, has realised a new DSS designed to help operators to deal with the complex task of managing multi-sectorial CI crises, due to natural events, where many different CI might be involved, either directly or via cascading effects produced by (inter-)dependency mechanisms. This DSS, called CIPCast, is able to produce a real-time operational risk forecast of CI in a given area; other than usable in a real-time mode, CIPCast could also be used as scenario builder, by using event simulators enabling the simulation of synthetic events whose impacts on CI could be emulated. A major improvement of CIPCast is its capability of measuring societal consequences related to the unavailability of primary services such as those delivered by CI

Clinical characteristics and risk factors associated with COVID-19 severity in patients with haematological malignancies in Italy: a retrospective, multicentre, cohort study

Several small studies on patients with COVID-19 and haematological malignancies are available showing a high mortality in this population. The Italian Hematology Alliance on COVID-19 aimed to collect data from adult patients with haematological malignancies who required hospitalisation for COVID-19