Big urban data visualization approaches within the smart city: Gis-based open-source dashboard example
| dc.contributor.author | Bovkır, Rabia | |
| dc.contributor.author | Aydinoğlu, Arif Çağdaş | |
| dc.date.accessioned | 2025-10-29T12:10:07Z | |
| dc.date.issued | 2021 | |
| dc.department | Gebze Teknik Üniversitesi | |
| dc.description | 6th International Conference on Smart City Applications -- Safranbolu; Karabuk University -- 175815 | |
| dc.description.abstract | The change and rapid development in information and communication technologies in recent years has caused increasing the data sources and the volume of data. With the smart city concept, big and complex data collected from the internet of things (IoT), smart sensors, and wearable technologies has been introduced into our lives. Such big data can provide various opportunities and possibilities in urban management, however, to obtain meaningful information from big volume complex data is challenging. Visual analytics techniques provide an effective way for extracting significant information from big data. With the integration of geographic information systems (GIS) and its ability on geographic analysis, big data produced by the IoT and sensors can be analysed and represented in real time via city dashboards. In this study, literature research about big data visualization approaches within the smart cities is examined. Dashboard examples with the integration of GIS is examined and an open-source GIS-based dashboard example is designed in Apache Superset. The relationship between air quality and traffic density is demonstrated with different visualization methods. © 2021 Elsevier B.V., All rights reserved. | |
| dc.identifier.doi | 10.5194/isprs-Archives-XLVI-4-W5-2021-125-2021 | |
| dc.identifier.endpage | 130 | |
| dc.identifier.isbn | 9781629935126 | |
| dc.identifier.isbn | 9781629934297 | |
| dc.identifier.isbn | 9781629935201 | |
| dc.identifier.issn | 1682-1750 | |
| dc.identifier.issue | 4/W5-2021 | |
| dc.identifier.scopus | 2-s2.0-85122297149 | |
| dc.identifier.scopusquality | Q3 | |
| dc.identifier.startpage | 125 | |
| dc.identifier.uri | https://doi.org/10.5194/isprs-Archives-XLVI-4-W5-2021-125-2021 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14854/14952 | |
| dc.identifier.volume | 46 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | International Society for Photogrammetry and Remote Sensing | |
| dc.relation.ispartof | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.snmz | KA_Scopus_20251020 | |
| dc.subject | Big Data | |
| dc.subject | City Dashboard | |
| dc.subject | Dashboard | |
| dc.subject | Smart City | |
| dc.subject | Visualization | |
| dc.title | Big urban data visualization approaches within the smart city: Gis-based open-source dashboard example | |
| dc.type | Conference Object |








