The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
A Framework for the Areal Interpolation of Socioeconomic Data
Abstract
Spatial data are collected and represented as attributes of spatial objects embedded in a plane. Basis change is defined as the transfer of attributes from one set of objects to another. Methods of basis change for socioeconomic data are reviewed and are seen to differ in the assumptions made in each about underlying density surfaces. These methods are extended to more general cases, and an illustration is provided by using Californian data. The implementation of this framework within a geographical information system is discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,525
Principles of geographical information systems for land resources assessment
Burrough, P. A. (1986) · Geocarto International · doi:10.1080/10106048609354060 · Cited by 2,709
Clark, C. (1951) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2981088 · Cited by 950
Spatial Interpolation Methods: A Review
Lam, N. S.-N. (1983) · The American Cartographer · doi:10.1559/152304083783914958 · Cited by 940
The Accuracy Of Spatial Databases
(1989) · CRC Press eBooks · doi:10.1201/b12612 · Cited by 770
Smooth Pycnophylactic Interpolation for Geographical Regions
Tobler, W. R. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10481647 · Cited by 678
Statistical Foundations of Econometric Modelling
Spanos, A., & Hendry, D. (1986) · Cambridge University Press eBooks · doi:10.1017/cbo9780511599293 · Cited by 503
Quantitative geography : a British view
Wrigley, N., & Bennett, R. (1981) · Routledge eBooks · Cited by 373
Spatial Data Configuration in Statistical Analysis of Regional Economic and Related Problems
Arbia, G. (1989) · Advanced Studies in Theoretical and Applied Econometrics · doi:10.1007/978-94-009-2395-9 · Cited by 312
Antithetic acceleration of Monte Carlo integration in Bayesian inference
Geweke, J. F. (1988) · Journal of Econometrics · doi:10.1016/0304-4076(88)90027-9 · Cited by 244
Cited by
Spatial data analysis: theory and practice
(2004) · Choice Reviews Online · doi:10.5860/choice.41-3486 · Cited by 965
Towards a general theory of geographic representation in GIS
Goodchild, M. F., Yuan, M., & Cova, T. J. (2007) · International Journal of Geographical Information Science · doi:10.1080/13658810600965271 · Cited by 458
Self-citationMapping urban risk: Flood hazards, race, & environmental justice in New York
Maantay, J., & Maroko, A. (2009) · Applied Geography · doi:10.1016/j.apgeog.2008.08.002 · Cited by 283
Spatially Integrated Social Science
(2006) · Encyclopedia of Human Geography · doi:10.4135/9781412952422.n278 · Cited by 269
Estimating the accuracy of geographical imputation
Henry, K. A., & Boscoe, F. P. (2008) · International Journal of Health Geographics · doi:10.1186/1476-072x-7-3 · Cited by 81
“Previous research covering population interpolation, areal interpolation, and dasymetric mapping of socioeconomic data could be adapted to allow for more accurate geographical imputation [36,40-43].”
Method
Metadata
- Authors
- Goodchild, M. F., Anselin, L., & Deichmann, U.
- Venue
- Environment and Planning A: Economy and Space
- Publisher
- SAGE Publications
- Published
- 1993-03
- Volume
- 25
- Issue
- 3
- Pages
- 383-397
- ISSN
- 0308-518X (ISSN-L)
- 1472-3409
- OpenAlex
- W2059195846
- Cited by
- 417
- References
- 14
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Framework for the Areal Interpolation of Socioeconomic Data. https://app.cochat.ai/papers/10.1068/a250383
- The paper
- Goodchild, M. F., Anselin, L., & Deichmann, U. (1993). A Framework for the Areal Interpolation of Socioeconomic Data. Environment and Planning A: Economy and Space. https://doi.org/10.1068/a250383
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.