Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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

Browse

Filters

20212

Settings

Publisher: search.filters.publisher.ElsevierSubject: search.filters.subject.GIS

Search Results

Now showing 1 - 2 of 2
  • Article
    Citation - WoS: 13
    Citation - Scopus: 12
    Identification of Groundwater Potential Zones in Kabul River Basin, Afghanistan
    (Elsevier, 2021) Tani, Hamidullah; Tayfur, Gökmen
    Groundwater (GW) plays a vital role in the socio-economic growth of Kabul River Basin (KRB) in Afghanistan. Since the GW resources in the basin have not been properly managed, there is a need for sound strategies by first identifying the potential GW zones. This study assesses the potential groundwater zones for the KRB using the Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). In this direction, seven different thematic maps of rainfall, lithology, land use/land cover, slope, soil, drainage density, and lineament density are first prepared using the GIS. The AHP is then employed to assess the weights of different themes. Finally, the weighted overlay option in the GIS is used to generate the map of the groundwater potential zones (GWPZ). The Very Good zones are mostly located in the downstream and central parts of the KRB, covering around 1543 km(2) area. The Good and the Poor zones are found to be randomly distributed, covering about 39 444 km(2) and 27 658 km(2), respectively. The Very Poor zones are located in the west, southwest, and in some central parts of the basin, covering about 2272 km(2). It is found that only 18% of the total average annual precipitated water of 6.88 x 10(9) m(3)/year infiltrates into the subsurface and ultimately contributes to recharging of the groundwater.
  • Article
    Citation - WoS: 27
    Citation - Scopus: 38
    Loose Coupling of Gis and Bim Data Models for Automated Compliance Checking Against Zoning Codes
    (Elsevier, 2021) Demir Altıntaş, Yelin; İlal, Mustafa Emre
    Modeling urban data is crucial for supporting automated code checking processes. Ideally, digitally modelled building codes and urban data should be retrieved from municipalities, and the digital building model should be checked automatically based on the collected information. However, BIM tools do not contain and do not allow managing geographical information at a neighborhood scale. Current GIS applications also do not store all of the information required by building codes. Even if they did, interoperability between GIS and BIM environments are problematic. This paper describes the development of a zoning domain model for automated compliance checking of building projects. The proposed model is illustrated through a proof-of-concept GIS application, where geometric and semantic data are stored, queried and exported as a GML file. Use of this data model for automated code checking is an example for how GIS data can seamlessly complement BIM data making expansion of BIM schemas unnecessary.