Population distribution modelling at fine spatio-temporal scale based on mobile phone data
Population distribution modelling can benefit many different domains, for example, transportation, urban planning, ecology or emergency management. Information about the location and number of people in an affected area is crucial for decision-makers during emergencies and crises. Mobile phone data...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2019-11-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2018.1548654 |
| _version_ | 1797678529162248192 |
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| author | Petr Kubíček Milan Konečný Zdeněk Stachoň Jie Shen Lukáš Herman Tomáš Řezník Karel Staněk Radim Štampach Šimon Leitgeb |
| author_facet | Petr Kubíček Milan Konečný Zdeněk Stachoň Jie Shen Lukáš Herman Tomáš Řezník Karel Staněk Radim Štampach Šimon Leitgeb |
| author_sort | Petr Kubíček |
| collection | DOAJ |
| description | Population distribution modelling can benefit many different domains, for example, transportation, urban planning, ecology or emergency management. Information about the location and number of people in an affected area is crucial for decision-makers during emergencies and crises. Mobile phone data represents relatively reliable and time accurate information on real-time population distribution, movement and behaviour. In this study, we evaluate the spatio-temporal distribution of population derived from phone data of the selected pilot area (City of Brno, Czech Republic). Analysis is based on the dataset describing the estimated human presence (EHP) with two values – visitors and transiting persons. The temporal change of data is first analysed and further processed using two methodological approaches. First, the dasymetric method is used where the building geometry and technical attributes served as a target layer. Second, the results of building level analysis are transformed into a regular grid zone of both visitors and the general EHP. Resulting spatio-temporal patterns are compared to the census data. Results demonstrate how the proposed building level dasymetric approach can improve the spatial granularity of EHP. Potential use of proposed methodology within selected emergency situations is further discussed. |
| first_indexed | 2024-03-11T23:01:07Z |
| format | Article |
| id | doaj.art-0085408e54e245d68cd4aa85aac46869 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:01:07Z |
| publishDate | 2019-11-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-0085408e54e245d68cd4aa85aac468692023-09-21T14:57:08ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552019-11-0112111319134010.1080/17538947.2018.15486541548654Population distribution modelling at fine spatio-temporal scale based on mobile phone dataPetr Kubíček0Milan Konečný1Zdeněk Stachoň2Jie Shen3Lukáš Herman4Tomáš Řezník5Karel Staněk6Radim Štampach7Šimon Leitgeb8Masaryk UniversityMasaryk UniversityMasaryk UniversityNanjing Normal UniversityMasaryk UniversityMasaryk UniversityMasaryk UniversityMasaryk UniversityMasaryk UniversityPopulation distribution modelling can benefit many different domains, for example, transportation, urban planning, ecology or emergency management. Information about the location and number of people in an affected area is crucial for decision-makers during emergencies and crises. Mobile phone data represents relatively reliable and time accurate information on real-time population distribution, movement and behaviour. In this study, we evaluate the spatio-temporal distribution of population derived from phone data of the selected pilot area (City of Brno, Czech Republic). Analysis is based on the dataset describing the estimated human presence (EHP) with two values – visitors and transiting persons. The temporal change of data is first analysed and further processed using two methodological approaches. First, the dasymetric method is used where the building geometry and technical attributes served as a target layer. Second, the results of building level analysis are transformed into a regular grid zone of both visitors and the general EHP. Resulting spatio-temporal patterns are compared to the census data. Results demonstrate how the proposed building level dasymetric approach can improve the spatial granularity of EHP. Potential use of proposed methodology within selected emergency situations is further discussed.http://dx.doi.org/10.1080/17538947.2018.1548654population distribution modellingmobile phone dataestimated human presenceemergency management |
| spellingShingle | Petr Kubíček Milan Konečný Zdeněk Stachoň Jie Shen Lukáš Herman Tomáš Řezník Karel Staněk Radim Štampach Šimon Leitgeb Population distribution modelling at fine spatio-temporal scale based on mobile phone data International Journal of Digital Earth population distribution modelling mobile phone data estimated human presence emergency management |
| title | Population distribution modelling at fine spatio-temporal scale based on mobile phone data |
| title_full | Population distribution modelling at fine spatio-temporal scale based on mobile phone data |
| title_fullStr | Population distribution modelling at fine spatio-temporal scale based on mobile phone data |
| title_full_unstemmed | Population distribution modelling at fine spatio-temporal scale based on mobile phone data |
| title_short | Population distribution modelling at fine spatio-temporal scale based on mobile phone data |
| title_sort | population distribution modelling at fine spatio temporal scale based on mobile phone data |
| topic | population distribution modelling mobile phone data estimated human presence emergency management |
| url | http://dx.doi.org/10.1080/17538947.2018.1548654 |
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