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@article{1474856,
author = {Kubíček, Petr and Konečný, Milan and Stachoň, Zdeněk and Shen, Jie and Herman, Lukáš and Řezník, Tomáš and Staněk, Karel and Štampach, Radim and Leitgeb, Šimon},
article_location = {Abingdon},
article_number = {11},
doi = {http://dx.doi.org/10.1080/17538947.2018.1548654},
keywords = {population distribution; modelling; mobile phone data; estimated human presence; emergency management},
language = {eng},
issn = {1753-8947},
journal = {International Journal of Digital Earth},
title = {Population Distribution Modelling at Fine Spatio-temporal Scale Based on Mobile Phone Data},
url = {https://www.tandfonline.com/doi/full/10.1080/17538947.2018.1548654},
volume = {12},
year = {2019}
}
TY - JOUR
ID - 1474856
AU - Kubíček, Petr - Konečný, Milan - Stachoň, Zdeněk - Shen, Jie - Herman, Lukáš - Řezník, Tomáš - Staněk, Karel - Štampach, Radim - Leitgeb, Šimon
PY - 2019
TI - Population Distribution Modelling at Fine Spatio-temporal Scale Based on Mobile Phone Data
JF - International Journal of Digital Earth
VL - 12
IS - 11
SP - 1319-1340
EP - 1319-1340
PB - Taylor & Francis Ltd
SN - 17538947
KW - population distribution
KW - modelling
KW - mobile phone data
KW - estimated human presence
KW - emergency management
UR - https://www.tandfonline.com/doi/full/10.1080/17538947.2018.1548654
L2 - https://www.tandfonline.com/doi/full/10.1080/17538947.2018.1548654
N2 - 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.
ER -
KUBÍČEK, Petr, Milan KONEČNÝ, Zdeněk STACHOŇ, Jie SHEN, Lukáš HERMAN, Tomáš ŘEZNÍK, Karel STANĚK, Radim ŠTAMPACH and Šimon LEITGEB. Population Distribution Modelling at Fine Spatio-temporal Scale Based on Mobile Phone Data. \textit{International Journal of Digital Earth}. Abingdon: Taylor \&{} Francis Ltd, 2019, vol.~12, No~11, p.~1319-1340. ISSN~1753-8947. Available from: https://dx.doi.org/10.1080/17538947.2018.1548654.
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