1,698 research outputs found
Accuracy of areal interpolation methods for count data
The combination of several socio-economic data bases originating from
different administrative sources collected on several different partitions of a
geographic zone of interest into administrative units induces the so called
areal interpolation problem. This problem is that of allocating the data from a
set of source spatial units to a set of target spatial units. A particular case
of that problem is the re-allocation to a single target partition which is a
regular grid. At the European level for example, the EU directive 'INSPIRE', or
INfrastructure for SPatial InfoRmation, encourages the states to provide
socio-economic data on a common grid to facilitate economic studies across
states. In the literature, there are three main types of such techniques:
proportional weighting schemes, smoothing techniques and regression based
interpolation. We propose a stochastic model based on Poisson point patterns to
study the statistical accuracy of these techniques for regular grid targets in
the case of count data. The error depends on the nature of the target variable
and its correlation with the auxiliary variable. For simplicity, we restrict
attention to proportional weighting schemes and Poisson regression based
methods. Our conclusion is that there is no technique which always dominates
Developing Population Grid with Demographic Trait: An Example for Milwaukee County, Wisconsin
Population grids have been widely used in estimating population in environmental justice studies and emergency management. The currently available population grids are only for total population. There is an increasing need for population grids that have not only total population but also populations of different age, gender, race, and ethnicity. This study explores the methodology to develop these population grids endowed with the demographic characteristics. Areal interpolation methods are used to transfer total population at census blocks to the cells of the grid. Kernel density method is used to estimate the relative probability of population of different subgroups at the cells, and to disaggregate total population into subgroups. Population grids of black, white, and other, as well as populations of age 20 to 34 and age 65 and over, are derived for Milwaukee County, Wisconsin. Applications of the population grids demonstrate their potentials
Dasymetric distribution of votes in a dense city
[EN] A large proportion of electoral analyses using geography are performed on a small area basis, such as polling units. Unfortunately, polling units are frequently redrawn, provoking breaks in their data series. Previous electoral results play a key role in many analyses. They are used by political party workers and journalists to present quick assessments of outcomes, by political scientists and electoral geographers to perform detailed scrutinizes and by pollsters and forecasters to anticipate electoral results. In this paper, we study to what extent more complex geographical approaches (based on a proper location of electors on the territory using dasymetric techniques) are of value in comparison to simple methods (like areal weighting) for the problem of reallocating votes in a large, dense city. Barcelona is such a city and, having recently redrawn the boundaries of its census sections, it is an ideal candidate for further scrutiny. Although previous studies show the approaches based on dasymetric techniques outperforming simpler solutions for interpolating census figures, our results show that improvements in the process of reallocating votes are marginal. This brings into question the extra effort that entails introducing ancillary sources of information in a dense urban area for this kind of data. Additional research is required to know whether and when these results are extendable. (C) 2017 Elsevier Ltd. All rights reserved.This work was supported by the Spanish Ministry of Economics and Competitiveness under Grant CSO2013-43054-R.Pavia, JM.; Cantarino-MartĂ, I. (2017). Dasymetric distribution of votes in a dense city. Applied Geography. 86:22-31. https://doi.org/10.1016/j.apgeog.2017.06.021S22318
Using a hybrid methodology of dasyametric mapping and data interpolation techniques to undertake population data (dis)aggregation in South Africa
The ability of GIS to produce accurate analysis results is dependent on the accuracy and the resolution of the data. In many instances the resolution of census enumerator tract data is too coarse and therefore inefficient in conducting fine grained spatial analysis. Dasymetric techniques can increase the spatial resolution of data by incorporating related high resolution ancillary data layers allowing the primary data to be represented at finer resolutions. Areal interpolation relates to a geostatistical process of transferring data from one set of polygons to another. This paper proposes the application of a hybrid technique using dasymetric mapping and areal interpolation principals to overcome the issues of transferring data from arbitrary spatial units to fit for purpose analysis zones on demand. As a consequence the technique also overcomes the problems of coarse scale population data as well as issues relating to the modifiable areal unit problem (MAUP). The data used to illustrate the value and accuracy of the developed methodology is that of the 2011 census population data and ESKOM’s SPOT building count. The final outcome is an algorithm allowing the disaggregation and aggregation of population data to any spatial unit with a high level of accuracy.Keywords: Dasymetric Mapping; MAUP; Population; Census; GI
A historical GIS for England and Wales: a framework for reconstructing past geographies and analysing long-term change
PhDThis thesis describes the creation and possible uses of a Geographical Information
System that contains the changing boundaries of the major administrative units of
England and Wales from 1840 to 1974. For over 150 years the census, the General
Register Office, and others have used these units to publish a wealth of data
concerning the population of the country. The key issue addressed by the thesis is that
changes in the administrative geography have hampered much research on long-term
change in society that could have been done using these sources. The goal of the
thesis is the creation of framework to allow the analysis of long-term socio-economic
change that makes maximum use of the available data.
This involves not only making use of the data's attribute (statistical) component,
but also their spatial and temporal components. In order to do this, the thesis provides
solutions to two key problems: the first is how to build a GIS containing
administrative units that incorporates an accurate record of their changing boundaries
and can be linked to statistical data in a flexible manner. The second is how to remove
the impact of boundary changes when comparing datasets published at different dates.
This is done by devising a methodology for interpolating data from the administrative
units they were published using, onto a single target geography. An evaluation of the
accuracy of this interpolation is performed and examples are given of how this type of
research could be conducted. Taken together, these will release information locked up
within historical socio-economic statistics by allowing space to be explicitly
incorporated into any explorations of the data. This, in turn, allows research to explore
the past with increased levels of both spatial and attribute data for longer time periods
Spatial reallocation of areal data - a review
The analysis of socio-economic data often implies the combination of data bases
originating from different administrative sources so that data have been collected
on several separate partitions of the zone of interest into administrative units. It
is therefore necessary to reallocate the data from the source spatial units to the
target spatial units. We propose a review of the literature on statistical methods of
spatial reallocation rules (spatial interpolation). Indeed one can distinguish several
types of reallocation depending on whether the initial data and the final output
are areal data or point data. We concentrate here on the areal-to-areal change of
support case when initial and final data have an areal support with a particular
attention to disaggregation for continuous data. There are three main types of
such techniques: proportional weighting schemes also called dasymetric methods,
smoothing techniques and regression based interpolation
Les méthodes d'interpolation pour données sur zones
Le résumé en français n'a pas été communiqué par l'auteur.The combination of several socio-economic data bases originating from different administrative sources collected on several different partitions of a geographic zone of interest into administrative units induces the so called areal interpolation problem. This problem is that of allocating the data from a set of source spatial units to a set of target spatial units. At the European level for example, the EU directive ’INSPIRE’, or INfrastructure for Spatial InfoRmation, encourages the states to provide socio-economic data on a common grid to facilitate economic studies across states. In the literature, there are three main types of such techniques: proportional weighting schemes, smoothing techniques and regression based interpolation. We propose a theoretical evaluation of these statistical techniques for the case of count related data. We find extensions of some of these methods to new cases : for example, we extend the ordinary dasymetric weightingmethod to the case of an intensive target variable Y and an extensive auxiliary quantitative variable X and we introduce a scaled version of the Poisson regression method which satisfies the pycnophylactic property. We present an empirical study on an American database as well as an R-package for implementing these methods
Developing a flexible framework for spatiotemporal population modeling
This article proposes a general framework for modeling population distributions in space and time. This is particularly pertinent to a growing range of applications that require spatiotemporal specificity; for example, to inform planning of emergency response to hazards. Following a review of attempts to construct time-specific representations of population, we identify the importance of assembling an underlying data model at the highest resolution in each of the spatial, temporal, and attribute domains. This model can then be interrogated at any required intersection of these domains. We argue that such an approach is necessary to moderate the effects of what we term the modifiable spatiotemporal unit problem in which even detailed spatial data might be inadequate to support time-sensitive analyses. We present an initial implementation of the framework for a case study of Southampton, United Kingdom, using bespoke software (SurfaceBuilder247). We demonstrate the generation of spatial population distributions for multiple reference times using currently available data sources. The article concludes by setting out key research areas including the enhancement and validation of spatiotemporal population methods and model
High resolution global gridded data for use in population studies
Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project websit
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