• DocumentCode
    2321433
  • Title

    Population spatialization in Gansu Province based on RS and GIS

  • Author

    Yang, Mei ; Wang, Shixin ; Zhou, Yi ; Wang, Litao ; Zeng, Chuiqing

  • fYear
    2009
  • fDate
    20-22 May 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Spatialized population data is much closer to actual circumstances than population distribution represented in administrative units. It is also crucial for analyzing the relationship among economic growth, environment protection, resource utilization, and other interdisciplinary study. Remote Sensing (RS) and Geographic Information System (GIS) are both effective research tools of spatializing census data of human population. The advance in population spatial distribution during the last several decades based on RS and GIS was briefly introduced at the beginning. Through multi-variable regression analysis with statistical population data and fourteen land use indices in county scale for Gansu Province in 2000, it was found that there was a strong relation between population distribution at administrative unit level and land use knowledge. Thus it would be reasonable to generate the population grid from land use grids for Gansu Province in 2000. The final output was a population map at a 1 km2 resolution for study area. Corresponding validation was carried out at last.
  • Keywords
    demography; economics; environmental management; geographic information systems; land use planning; regression analysis; remote sensing; AD 2000; Gansu Province; economic growth; environment protection; geographic information system; land use index; multivariable regression analysis; population distribution; population spatialization; remote sensing; resource utilization; Biological system modeling; Environmental economics; Geographic Information Systems; Humans; Image databases; Mesh generation; Regression analysis; Remote sensing; Spatial databases; Water resources; GIS; Gansu; Land use; Population; Remote sensing; Spatialize;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Urban Remote Sensing Event, 2009 Joint
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3460-2
  • Electronic_ISBN
    978-1-4244-3461-9
  • Type

    conf

  • DOI
    10.1109/URS.2009.5137641
  • Filename
    5137641