Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 12265195

Spatial aggregation in gravity models: 2. One-dimensional population density models.

M Batty·P K Sikdar
View original source ↗Export metadata ↓

Abstract

"This paper, the second of four, is concerned with applying a methodology for analysing the spatial aggregation problem in gravity models outlined in the first paper. The methodology is based on a consistent framework for linking measures of pattern in interaction data to the derivation and estimation of related interaction models using spatial information. In this quest, a link is forged between information in data and the parameters of an associated model.... This relationship can be formalised for the case of the continuous one-dimensional interaction model such as the population density model, and this paper is concerned with demonstrating such an application to aggregations of zones in the Reading [England] region."

Explore related subjects

DemographyDeveloped CountriesEnglandEuropeGeographyModels, TheoreticalPopulationPopulation DensityResearchStatistics as TopicUnited KingdomData AnalysisEstimation TechnicsGeographic FactorsMathematical ModelNorthern EuropeResearch MethodologySpatial DistributionJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M Batty, P K Sikdar. 1982. Spatial aggregation in gravity models: 2. One-dimensional population density models.. https://doi.org/10.1068/a140525

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2004

Satisfaction with medical rehabilitation after spinal cord injury.

STUDY DESIGN: Retrospective. OBJECTIVE: To predict satisfaction with medical rehabilitation. SUMMARY OF BACKGROUND DATA: While spinal cord injury (SCI) patient satisfaction with life and community services has been investigated, satisfaction with medical rehabilitation has not. METHODS: Information submitted to the Uniform Data System for Medical Rehabilitation (1998-2001) by 134 hospitals/rehabilitation facilities in the United States (n = 6,205 patients with SCI) was examined. Predictors were sociodemographic variables, Case Mix Groupings (CMG) (401-505, 5001), length of stay, rehospitalization, follow-up therapy, and health maintenance. Satisfaction was assessed at a mean of 92.2 days (SD 11.9 days) postdischarge. Data were analyzed according to who reported the outcome (patient, n = 3,858 or family/other, n = 1,869). Statistical modeling was conducted using logistic regression. RESULTS: High overall satisfaction was reported (94%). Significant predictors for the patient report data were CMG and rehospitalization. Compared with CMG 5001 (short stay, <3 days), patients in CMGs 401/2/3 and 501/2/3/4/5 had a 54% to 74% lower likelihood of being dissatisfied. Rehospitalized patients had a higher likelihood of dissatisfaction (odds ratio 2.3, 95% confidence interval 1.7 to 3.2). Significant predictors for the family/other report data were CMG (compared to CMG 5001, CMGs 401/2, 403, and 501/2 had a 70% lower likelihood of dissatisfaction), rehospitalization (odds ratio 1.7, 95% confidence interval 1.1-2.5), and marital status (married = 50% lower likelihood of dissatisfaction, 95% confidence interval 0.26-0.96). CONCLUSIONS: Satisfaction with medical rehabilitation services following SCI is related to functional abilities, rehospitalization, and marital status. Slightly different results were found for whether satisfaction was rated by the patient or family/other. The complex relationships among satisfaction, patient demographics, and functional status require continued examination.

Demography↗
PubMed2004

Coherence and discontinuity in the scaling of species' distribution patterns.

The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 m to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.

Demography↗