Spatio-Temporal Building Population Estimation for Highly Urbanized Areas Using GIS

被引:23
|
作者
Greger, Konstantin [1 ]
机构
[1] Univ Tsukuba, Div Spatial Informat Sci, Tsukuba, Ibaraki 3058572, Japan
关键词
SYSTEM; MODELS; RISK;
D O I
10.1111/tgis.12086
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Detailed population information is crucial for the micro-scale modeling and analysis of human behavior in urban areas. Since it is not available on the basis of individual persons, it has become necessary to derive data from aggregated census data. A variety of approaches have been published in the past, yet they are not entirely suitable for use in the micro-scale context of highly urbanized areas, due mainly to their broad spatial scale and missing temporal scale. Here we introduce an enhanced approach for the spatio-temporal estimation of building populations in highly urbanized areas. It builds upon other estimation methodologies, but extends them by introducing multiple usage categories and the temporal dimension. This allows for a more realistic representation of human activities in highly urbanized areas and the fact that populations change over time as a result of these activities. The model makes use of a variety of micro-scale data sets to operationalize the activities and their spatio-temporal representations. The outcome of the model provides estimated population figures for all buildings at each time step and thereby reveals spatio-temporal behavior patterns. It can be used in a variety of applications concerning the implications of human behavior in urban areas.
引用
收藏
页码:129 / 150
页数:22
相关论文
共 50 条
  • [1] Estimation of a continuous spatio-temporal population model
    Javier Alvarez
    Pascal Mossay
    [J]. Journal of Geographical Systems, 2006, 8 : 307 - 316
  • [2] Estimation of a continuous spatio-temporal population model
    Alvarez, Javier
    Mossay, Pascal
    [J]. JOURNAL OF GEOGRAPHICAL SYSTEMS, 2006, 8 (03) : 307 - 316
  • [3] Visualization of Spatio-Temporal Building Changes Using 3D Web GIS
    Templin, Tomasz
    Brzezinski, Grzegorz
    Rawa, Marcelina
    [J]. WORLD MULTIDISCIPLINARY EARTH SCIENCES SYMPOSIUM (WMESS 2018), 2019, 221
  • [4] Toxic metals in a highly urbanized industry-impacted estuary (Bahia Blanca Estuary, Argentina): spatio-temporal analysis based on GIS
    Melisa Daiana Fernández Severini
    María Elizabeth Carbone
    Diana Mariel Villagran
    Jorge Eduardo Marcovecchio
    [J]. Environmental Earth Sciences, 2018, 77
  • [5] Models and queries in a spatio-temporal GIS
    El-Geresy, B
    Jones, C
    [J]. INNOVATIONS IN GIS: GIS AND GEOCOMPUTATION, 2000, 7 : 27 - 39
  • [6] Toxic metals in a highly urbanized industry-impacted estuary (Bahia Blanca Estuary, Argentina): spatio-temporal analysis based on GIS
    Fernandez Severini, Melisa Daiana
    Elizabeth Carbone, Maria
    Mariel Villagran, Diana
    Eduardo Marcovecchio, Jorge
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2018, 77 (10)
  • [7] Estimation of siltation in Tuirial dam: a spatio-temporal analysis using GIS technique and bathymetry survey
    Lawmchullova, Imanuel
    Rao, Ch. Udaya Bhaskara
    [J]. JOURNAL OF SEDIMENTARY ENVIRONMENTS, 2024, 9 (01) : 81 - 97
  • [8] Estimation of siltation in Tuirial dam: a spatio-temporal analysis using GIS technique and bathymetry survey
    Imanuel Lawmchullova
    Ch. Udaya Bhaskara Rao
    [J]. Journal of Sedimentary Environments, 2024, 9 : 81 - 97
  • [9] Research progress on spatio-temporal distribution estimation of urban population
    Wu, Huayi
    Hu, Qiushi
    Li, Rui
    Liu, Zhaohui
    [J]. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2022, 51 (09): : 1827 - 1847
  • [10] Urban population density estimation based on spatio-temporal trajectories
    Xue, Fei
    Cao, Yang
    Ding, Zhiming
    Tang, Hengliang
    Yang, Xi
    Chen, Lei
    Li, Juntao
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2020, 32 (14):