Using household counts as ancillary information for areal interpolation of population
Comparing formal and informal, online data sources
Bibliographic Data
| ID | 21478843 |
|---|---|
| Authors | Wen Zeng (0000-0001-7049-7997, Shandong University of Science and Technology, corresponding author), Alexis Comber (0000-0002-3652-7846, University of Leeds) |
| Year | 2020 |
| Volume | 80 |
| Pages | 101440 |
| Publication date | 2020-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Computers Environment and Urban Systems (JOURNAL) |
| Journal identifiers | ISSN: 0198-9715 • E-ISSN: 1873-7587 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.compenvurbsys.2019.101440 |
| OpenAlex | W2985193458 |
| Language | EN |
| Citations received | 3 |
| References cited | 59 |
Fine-scale population estimates are needed to support both public and private planning. Previous areal interpolation research has used various types and sources of data as ancillary information to guide and constrain the disaggregation from (usually) larger source zones to (usually) smaller target zones. Many new forms of open and free to access geo-located data are available, and as yet little research has evaluated the use of these data in areal interpolation. This study evaluates the effectiveness of household data as ancillary information from two sources: formal census household counts and informal data on residential (house) sales from commercial websites, applied to 2 case studies with different contexts - Leeds in UK and Qingdao in China. The proposed Household Proportion method uses household counts as ancillary information for areal interpolation of population. It is compared with other interpolation and the results show that HP method yields significantly better results than other interpolation approaches using ancillary data, with lower errors. This research also demonstrates that such data support the application of a suite of interpolation methods that make fewer assumptions about underlying spatial processes. The need to examine issues of representativeness and data coverage are identified and discussed, but the study demonstrates the opportunities for including freely available geo-located data to inform geographic analyses
Ancillary data · Census · Data collection · Geography · Multivariate interpolation · Population · Remote sensing · Representativeness heuristic · Spatial analysis · Statistics · Suite · Telecommunications · Computer Science · Demography · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Mathematics · Urban Transport and Accessibility
Generating Surface Models of Population Using Dasymetric Mapping
Interpolating U.S. Decennial Census Tract Data from as Early as 1970 to 2010
A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management
How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets
Spatial Interpolation Methods
Smooth Pycnophylactic Interpolation for Geographical Regions
Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model
A regression approach to estimating the average number of persons per household
Spatial interpolation using areal features
Measuring environmental inequality
Areal Interpolation and Dasymetric Mapping Methods Using Local Ancillary Data Sources
Dasymetric Mapping and Areal Interpolation
A Comparative Analysis of Areal Interpolation Methods
A Process Oriented Areal Interpolation Technique
Intelligent Dasymetric Mapping and Its Application to Areal Interpolation
Population at risk
Comparison of Dasymetric Mapping Techniques for Small-Area Population Estimates
City profile – Leeds
Areal Interpolation of Population Counts Using Pre-classified Land Cover Data
An Evaluation of Population Estimates in Florida
Mapping Population Data from Zone Centroid Locations
A Quantile Regression Approach to Areal Interpolation
Improving Small-Area Population Estimation
The Generation of Spatial Population Distributions from Census Centroid Data
A Framework for the Areal Interpolation of Socioeconomic Data
Street-Weighted Interpolation Techniques for Demographic Count Estimation in Incompatible Zone Systems
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2025 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |