Analysis of car park etudes with different statistical methods and modeling with GIS: Erzincan province case; [Otopark etütlerinin farklı istatistiksel yöntemler ile analizi ve CBS ile modellenmesi: Erzincan ili örneği]

ArticleAçık Erişim

Özet

Rapidly changing lifestyles, rising expectations, and increased private vehicle ownership have caused increases in the number of urban trips. All these changes that have appeared in time have made the parking requirement more important every day. Parking surveys have been required to determine what actions to be taken leadingly during the location selection and building processes of the parking areas to be built. The failure on planning parking areas correctly reveals environmental and economic problems as well as social problems. In this study, parking surveys were carried out primarily in order to determine location, types and capacities of existing car parks. The capacity and locations of the new parking areas have been determined considering five-year traffic increases. The points where parking needs were most needed were determined counting the vehicles parked at 44 separate on-road parking areas in the city center of Erzincan, where parking fees are charged by the municipality. In determined parking areas, statistical analyses were performed with spatial analysis outputs, artificial neural networks and time series analysis methods counting the vehicles parked regularly during daylight hours for one year. Solutions were offered to reduce parking load in traffic identifying new correctly located car parking areas in Erzincan city center. In the light of the analysis results, the location and capacities of the new parking areas suggested to be built identifying 6 different points in the city center were determined. In conclusion, an additional 1420-vehicle parking capacity in suggested new parking spaces was proposed as a solution-oriented approach for the parking problem in the city center. © 2021, Gumushane University. All rights reserved.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/13380Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.17714/gumusfenbil.685894Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorMazlum, Yusuf
dc.contributor.authorBayata, Halim Ferit
dc.contributor.authorBaş, Fatih İrfan
dc.contributor.authorÇolak, Muhammet Ali
dc.contributor.authorBayrak, Ünsal
dc.date.accessioned2026-10-18T20:28:13.134622048Z
dc.date.available2026-10-18T20:28:13.134622048Z
dc.date.issued2021
dc.description.abstractRapidly changing lifestyles, rising expectations, and increased private vehicle ownership have caused increases in the number of urban trips. All these changes that have appeared in time have made the parking requirement more important every day. Parking surveys have been required to determine what actions to be taken leadingly during the location selection and building processes of the parking areas to be built. The failure on planning parking areas correctly reveals environmental and economic problems as well as social problems. In this study, parking surveys were carried out primarily in order to determine location, types and capacities of existing car parks. The capacity and locations of the new parking areas have been determined considering five-year traffic increases. The points where parking needs were most needed were determined counting the vehicles parked at 44 separate on-road parking areas in the city center of Erzincan, where parking fees are charged by the municipality. In determined parking areas, statistical analyses were performed with spatial analysis outputs, artificial neural networks and time series analysis methods counting the vehicles parked regularly during daylight hours for one year. Solutions were offered to reduce parking load in traffic identifying new correctly located car parking areas in Erzincan city center. In the light of the analysis results, the location and capacities of the new parking areas suggested to be built identifying 6 different points in the city center were determined. In conclusion, an additional 1420-vehicle parking capacity in suggested new parking spaces was proposed as a solution-oriented approach for the parking problem in the city center. © 2021, Gumushane University. All rights reserved.
dc.identifier.doi10.17714/gumusfenbil.685894
dc.identifier.eissn2146-538X
dc.identifier.endpage509
dc.identifier.issn2146-538X
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105003915586
dc.identifier.startpage497
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/13380
dc.identifier.volume11
dc.language.isoen
dc.publisherGumushane University
dc.relation.ispartofGumushane Universitesi Fen Bilimleri Dergisi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial neural networks
dc.subjectLocation selection
dc.subjectParking survey
dc.subjectSpatial analysis
dc.subjectTime series analysis
dc.titleAnalysis of car park etudes with different statistical methods and modeling with GIS: Erzincan province case; [Otopark etütlerinin farklı istatistiksel yöntemler ile analizi ve CBS ile modellenmesi: Erzincan ili örneği]
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus2
rdl.citation.trdizin0
rdl.departmentERZİNCAN BİNALİ YILDIRIM ÜNİVERSİTESİ
rdl.departmentATATÜRK ÜNİVERSİTESİ
rdl.oa.statusgold
rdl.source.indexSCOPUS
rdl.source.indexTRDIZIN