Incorporating GIS Building Data and Census Housing Statistics for Sub-Block-Level Population Estimation

This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating...

Full description

Saved in:
Bibliographic Details
Published inThe Professional geographer Vol. 60; no. 1; pp. 121 - 135
Main Authors Wu, Shuo-sheng, Wang, Le, Qiu, Xiaomin
Format Journal Article
LanguageEnglish
Published Cambridge, MA Taylor & Francis Group 01.02.2008
Blackwell
Taylor & Francis Ltd
Subjects
Bgi / Prodig
block population
Census of Population
Censuses
cálculo de la población
dasymetric mapping
Geographic information systems
Geographical information systems
Housing
Human geography
interpolación de la población
mapeo dasimétrico
Mapping
población en bloque
population estimation
population interpolation
Statistical analysis
sub-block
sub-bloque
Surveying errors
Urban development
Urban geography
Urban planning
Urban population and society
Urban sociology
人口估算
人口插值
人口板块
分区密度制图
分板块
United States of America
Texas
Aggregation
Interpolation
Methodology
Local population
Urban population
Estimation
Online AccessGet full text

Cover

More Information
Summary:This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:0033-0124
1467-9272
DOI:10.1080/00330120701724251