Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Subject: search.filters.subject.Geographic information systemsWoS Q: search.filters.wosQuartile.Q2

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  • Article
    Citation - WoS: 17
    Citation - Scopus: 24
    A Gis-Based Fahp and Fedas Analysis Framework for Suitable Site Selection of a Hybrid Offshore Wind and Solar Power Plant
    (Elsevier B.V., 2023) Karipoğlu, Fatih; Ozturk, S.; Efe, B.
    This study presents a Geographic Information System (GIS) based suitable site selection methodology for a hybrid system that includes offshore wind and solar PV. The methodology utilizes open source databases about decision criteria and applies this data using GIS to determine suitable sites for offshore wind and solar PV systems. For the assessment of multi-criteria which affect the potential hybrid energy power plants and the determination of the best suitable areas, Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Evaluation based on Distance Average Solution (FEDAS) are used in the study. Results show that technical criteria has the priority weight of 0.60 while the weight of social criteria is about 0.07. Among sub-criteria, the wind speed has the highest priority weight while distance to port and visibility are the highest criteria of priority weight under economic and social main criteria, respectively. Among the alternatives, Area 2 (A-2) is determined as the best alternative for hybrid offshore power plants in the study area. This proposed methodology can be utilized by decision-makers to determine the best suitable locations for hybrid offshore wind and solar PV systems at any location. This paper suggests a new approach integrating GIS, fuzzy setbased AHP and EDAS as a novelty. © 2023 International Energy Initiative
  • Article
    Citation - WoS: 11
    Citation - Scopus: 11
    The Utilization of Supervised Classification Sampling for Environmental Monitoring in Turin (italy)
    (MDPI, 2021) Salata, Stefano
    In a world threatened by climate change, the need to observe the land transformation is crucial to set environmental policies. One of the most prominent issues of environmental monitoring is the availability of updated and reliable land use data. The last land-use release in Piedmont Region (Italy) is in 2010, while the most updated Normalized Difference Vegetation Index is in 2016. To overcome this limit, in this study, a supervised classification sampling has been applied on a Sentinel-2 image produced by the Copernicus Program on 29 September 2020, using Esri ArcGIS (ver.10.8 Redlands, California, US) by accessing via ONDA-DIAS services to L2A products. After land classification, three maps were generated-the Habitat Quality, the Habitat Decay, and the Normalized Difference Vegetation Index. This study aimed at classifying the environmental status in five classes ranging from critical to health with a double perspective-(i) to make a comparative metropolitan assessment between municipalities and (ii) to evaluate the quality of urban public green areas in the city of Turin while defining a different kind of intervention. Results indicate that products derived from supervised classification sampling can be applied in a wide range of applications while reaching seasonal monitoring of the environmental status and delivering just-in-time solutions.