Estimates of the Ambient Population: Assessing the Utility of Conventional and Novel Data Sources
| Autor: | Nicolas Malleson, Jonathan A. Ward, Alison J. Heppenstall, Annabel Whipp |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
novel data Geography Planning and Development Population 0211 other engineering and technologies 0507 social and economic geography lcsh:G1-922 02 engineering and technology Preliminary analysis Population estimate Urban analytics 11. Sustainability Earth and Planetary Sciences (miscellaneous) Computers in Earth Sciences education education.field_of_study 05 social sciences 021107 urban & regional planning Data science ambient population daytime population Identification (information) Work (electrical) spatio-temporal data 050703 geography lcsh:Geography (General) |
| Zdroj: | ISPRS International Journal of Geo-Information Volume 10 Issue 3 ISPRS International Journal of Geo-Information, Vol 10, Iss 131, p 131 (2021) |
| ISSN: | 2220-9964 |
| DOI: | 10.3390/ijgi10030131 |
| Popis: | This paper will critically assess the utility of conventional and novel data sources for building fine-scale spatio-temporal estimates of the ambient population. It begins with a review of data sources employed in existing studies of the ambient population, followed by preliminary analysis to further explore the utility of each dataset. The identification and critiquing of data sources which may be useful for building estimates of the ambient population are novel contributions to the literature. This paper will provide a framework of reference for researchers within urban analytics and other areas where an accurate measurement of the ambient population is required. This work has implications for national and international applications where accurate small area estimates of the ambient population are crucial in the planning and management of urban areas, the development of realistic models and informing policy. This research highlights workday population estimates, in conjunction with footfall camera and Wi-Fi sensors data as potentially valuable for building estimates of the ambient population. |
| Databáze: | OpenAIRE |
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