535 research outputs found
2019. GISDAY 2018-il GIS per il governo e la gestione del territorio. pp.1-264 - ISBN:978-8825529524 curatori, Barbara Cardone, Ferdinando DI Martino, Salvatore Sessa.
No full textGIS FRAMEWORK PER LA CLASSIFICAZIONE DI ELEMENTI URBANI DA STATI EMOTIVI NELLA RETE SOCIALE
No full textThe research proposes the integration on the GIS platform of a sentiment analysis method aimed at evaluating the moods and impressions that citizens and tourists express in unstructured comments in the various social groups connected to lived and aggregated places, built environments, infrastructures. service of urban fabrics. This approach allows the extraction and classification of users' opinions in terms of emotional categories, and constitutes a knowledge base capable of evaluating appropriate strategies for planning and designing interventions on the urban elements under study in order to make them better usable and perception by users
Un Sistema Informativo Territoriale per la valutazione del valore economico degli edifici nelle zone OMI di Napoli
No full textLa ricerca si pone l’obiettivo di sperimentare un processo valido ed innovativo per la valutazione economica di un bene architettonico, attraverso le qualità intrinseche ed estrinseche del bene stesso nelle zone OMI. Per qualità intrinseche s’intendono tutte le caratteristiche dell’edificio di studio, come ad esempio, se è fornito di riscaldamento, se ha ascensore, se si trova al centro della città, se è un edificio destinato a residenze o ad uffici pubblici, se è in buone condizioni oppure fatiscente, ecc. Per qualità estrinseche s’intendono le caratteristiche del contesto in cui è calato l’edificio di studio, come ad esempio, la vicinanza ai servizi, quali farmacie, scuole, ospedali, mezzi pubblici, oppure se è una zona trafficata, se è una zona isolata, tutte caratteristiche che influenzano la valutazione economica del bene. Supporto alle decisioni è la consultazione dei dati dell’ Agenzia del Territorio stabilite nelle zone OMI di Napol
A new emotion–based hot and cold spots detection method to assess the citizen’s discomfort due to heatwaves in the northeastern area of the province of Naples (Italy)
No full textA spatial analysis technique known as “hot and cold spots identification” is used in a variety of situations to identify areas where a particular phenomena is either highly or weakly concentrated or experienced. Numerous hot (cold) spot detection methods have been proposed in the literature. Clustering methods are typically used to extract hot and cold spots as polygons on maps; the more precisely the hot (cold) spot area is determined, the more computationally complex the clustering algorithm becomes. Furthermore, these methods do not take into account the hidden information provided by users through social networks, significant for detecting the presence of hot (cold) spots based on the emotional reactions of citizens. To overcome these critical points, we propose a GIS–based hot and cold spot detection framework encapsulating a classification model of emotion categories of documents extracted from social streams connected to the investigated phenomenon is implemented. The study area is split into subzones; residents’ postings during a predetermined time period is retrieved and analyzed for each subzone. With the aid of a fuzzy–based approach to classifying emotions, the proposed model measures the prevalence of pleasant and unpleasant emotional categories in each subzone at various time intervals. The subzones in which uneasy emotions predominate over the examined time period are referred to as hot (cold) spots. Since the exact geometric shape of the point is not necessary to be detected, the proposed framework has the advantage of greatly reducing the CPU time required by cluster–based hot and cold spot detection techniques. Our framework has been put to the test in the study region, which is made up of towns in the northeastern part of the province of Naples, to find hot and cold places related to the misery of residents due to heat waves. (Italia). The results show that the hot spots, where the greatest discomfort is felt, correspond to areas with a high population/building density, on the contrary, cold spots cover urban areas having a lower population density
Un GIS per l’abusivismo edilizio nel Comune di Forio d’Ischia (NA)
No full textL’obiettivo del presente lavoro è di fornire un supporto operativo e decisionale per il Comune di Forio d’Ischia riguardo la problematica dell’abusivismo edilizio, che ha prodotto un’enorme quantità di fabbricati abusivi, oggetto di migliaia di richieste di Condono Edilizio. Queste giacciono per la quasi totalità all’interno degli archivi comunali, in attesa di essere esaminate per il rilascio della relativa concessione edilizia in sanatoria. Il Comune di Forio, presenta una situazione particolare, in quanto conta più di 8.000 di istanze di condono da esaminare e non è dotato di nessuno strumento di pianificazione urbanistica. L’intento specifico del presente lavoro è di proporre un “Piano per la valutazione della compatibilità' paesaggistica degli interventi abusivi oggetto di istanze di condono edilizio (cfr. Piano di dettaglio delle opere abusive)”, attraverso l’elaborazione di un GIS che possa essere direttamente fruibile, a tal fine e, nel contempo, fungere da base per la realizzazione di un SIT del Comune. A seguito della catalogazione di alcune delle istanze di Condono Edilizio e per la gestione di queste, è stato, inoltre, creato un database relazionale collegato al tematismo dell’edificato
A new fuzzy rule-based model to partition a complex urban system in homogeneous urban contexts
No full textGISDAY2016
No full textCome già avvenuto dal 2008 in poi, il 18 novembre 2016 si è tenuto l’evento “GIS DAY 2016: il GIS per la gestione del territorio” nell’aula magna del Dipartimento di Architettura dell’Università degli Studi di Napoli Federico II. Con questa nona raccolta di articoli riguardanti i Sistemi Informativi Territoriali, continua il contributo degli esperti di questa tecnologia intervenuti all’evento per presentare i loro lavori. Ancora una volta si ringraziano tutti gli autori che hanno inviato il loro contributo ed ESRIITALIA, la cui sponsorizzazione è stata fondamentale per la riuscita e l’organizzazione dell’evento. Un particolare ringraziamento a Silvia d’Ambrosio che ha coordinato la realizzazione complessiva dell’evento medesimo, in particolare tenendo i contatti con gli interessati, i docenti e i relatori e ha gestito la revisione grafica degli abstract, degli articoli, l’impaginazione professionale e la pubblicazione di questi atti
A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts
No full textHere, we present a new unsupervised method aimed at obtaining a partition of a complex urbansysteminhomogenousurbanareas,calledurbancontexts.Ourmodelintegratesspatialanalysis processes and a fuzzy rule-based system applied to manage the knowledge of domain experts; it is implemented using a GIS platform. The area of study is initially partitioned in microzones, homogeneous portions of the urban system, which are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental, and socio-economic indicators needed to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary for determining the type of urban context. We implement the set of spatial analysis processes required to calculate the indicators for the microzones and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples, Italy); the reliability of the out model is measured by comparing the results with the ones obtained through a detailed analysis
A Fuzzy Rule-Based GIS Framework to Partition an Urban System Based on Characteristics of Urban Greenery in Relation to the Urban Context
No full textWe present a GIS-based framework implementing a Mamdani fuzzy rule-based system to partition in an unsupervised mode an urban system in urban green areas. The proposed framework is characterized by high usability and flexibility. The study area is partitioned in homogeneous regions regarding the characteristics of public green areas and relations with the residents and buildings. The urban system is initially partitioned in microzones, given the smallest areas in which is taken a census of the urban system in terms of resident population, type and number of buildings and properties, industrial and service activities. During a pre-processing phase, the values of specific indicators defined by a domain expert that characterize the type of urban green and the relationship with the residents and buildings are calculated for each microzone. Subsequently, the fuzzy rule-based system component is executed to classify each microzone based on the fuzzy rule set constructed by the domain expert. Spatially adjoining microzones belonging to the same class are dissolved to form homogeneous areas called Urban Green Contexts. The membership degrees of the microzones to the fuzzy set of their class are used to evaluate the reliability of the classification of the Urban Green Context. We test our framework on the municipality of Pozzuoli (Italy), comparing the results with the ones obtained in a supervised manner by the expert appropriately partitioning and classifying the study area based on his knowledge of the urban study area
A Novel Method Based on the Fuzzy Entropy Measure to Optimize the Fuzziness in Trapezoidal Strong Fuzzy Partitions
No full textAnalyzing the uncertainty of outcomes based on estimates of the data’s membership degrees to fuzzy sets is essential for making decisions. These fuzzy sets are often designated by experts as strong fuzzy partitions of the data domain with trapezoidal fuzzy numbers. Some indices of the fuzzy set’s fuzziness provide an assessment of the degree of uncertainty of the results. It is feasible to bring the fuzzy sets’ fuzziness below a tolerable level by suitably redefining the strong fuzzy partition. Significant differences in the original fuzzy partition, however, result in disparities concerning the decision maker’s approximative reasoning and the interpretability of the results. In light of this, we provide in this study a technique applied to trapezoidal strong fuzzy partitions that, while not appreciably altering the original fuzzy partition, reduces the fuzziness of its fuzzy sets. The fuzziness of the fuzzy sets is assessed using the De Luca and Termini fuzzy entropy. An iterative process is then executed, with the aim of modifying the cores of the trapezoidal fuzzy partitions to decrease their fuzziness. This technique is tested on datasets containing average daily temperatures measured in various cities. The findings demonstrate that this approach strikes a great balance between the goal of lessening the fuzziness of the fuzzy sets and the goal of not appreciably altering the original fuzzy partition
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