Urban Planning with Mobile data
| dc.Location | 2019 T 58.6 S93 | |
| dc.Supervisor | Professor Khaled Shaalan | |
| dc.contributor.author | SWAIDAN, WAEL TAWFIQ | |
| dc.date.accessioned | 2019-08-28T08:47:49Z | |
| dc.date.available | 2019-08-28T08:47:49Z | |
| dc.date.issued | 2019-01 | |
| dc.description.abstract | Urban green space is closely related to the quality of life of residents. Researchers and academic scholars from various institutes have also pointed out the important role that urban green space can play in the interaction between human and the environment. Most of the methods for urban green space planning take into consideration neither take in the number of users, nor the area and service capacity of green spaces. To address such problems an optimized 2SFCA method to study public facility planning from both the supply and demand sides was put forward in 2014. In the application of the 2SFCA method, some key data inputs include the number of urban residents that a public facility serves, and also the accurate spatial distribution of urban residents where considered. Traditionally, these data are acquired through social surveys and lack timeliness and precision. In recent years, with the rapid development of computer and information technology, it has become possible to use mobile devices, such as cell phones and various location-based services (LBS) provided by APPs installed on smart devices have become a source of urban data with high availability and practical value. In this study, facilitated by mobile phone location data, more specific features of the spatial distribution of urban residents are identified. Further, population distribution in relation to traffic analysis zones is mapped. On this basis, the two-step floating catchment area method (2SFCA) is adopted in combination with urban green space planning to evaluate the per capita area of green space and its accessibility in practice. Subsequently, classification of per capita area and spatial distribution of green spaces within the study area are obtained; thus, urban districts currently with low accessibility to green areas are identified and can be deemed as key areas for the planning of green areas in the future. The study concludes that mobile phone data can be used to more accurately map the spatial distribution of residents; while, the 2SFCA offers a more comprehensive quantitative measuring of the supply and demand of green spaces. The two combined can be used as an important basis for decision-making in the planning of urban green spaces. Since urban green space can be regarded as a kind of public facility, the methodology of the present study is also believed to be applicable in studies of other types of urban facilities | en_US |
| dc.identifier.other | 2016128018 | |
| dc.identifier.uri | https://bspace.buid.ac.ae/handle/1234/1465 | |
| dc.language.iso | en | en_US |
| dc.publisher | The British University in Dubai (BUiD) | en_US |
| dc.subject | urban planning | en_US |
| dc.subject | mobile data | en_US |
| dc.subject | green space | en_US |
| dc.title | Urban Planning with Mobile data | en_US |
| dc.type | Dissertation | en_US |