The approaches considered are the weighted areal interpolation in the text interpolazione areale ponderata, iap and the intelligent dasymetric mapping idm as implemented in a plugin for. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the united states, we examined methods to estimate mortality within zones at varying distances from these facilities. Using a hybrid methodology of dasyametric mapping and. Areal interpolation in the arcgis geostatistical analyst extension is a geostatistical interpolation technique that extends kriging theory to data averaged or aggregated over polygons. Such maps can be preferable to choropleth maps that show data by enumeration zones, because dasymetric zones more accurately represent underlying data distributions. Pdf intelligent dasymetric mapping and its application. The two types of interpolation that are used in this study are the simple areal weighting and a dasymetricbased interpolation method. A pointbased intelligent approach to areal interpolation. Dasymetric mapping, on the other hand, divides mapped area into zones of relative homogeneity 7. The development of an areal interpolation arcgis extension. When boundaries collide public opinion quarterly oxford.
Diagram showing how dasymetric mapping redistributes ancillary information to better represent population distribution. Modelling the errors in areal interpolation between zonal. Usgs techniques and methods 11c2 usgs publications. Streetweighted interpolation techniques for demographic. Tobler is a python package for areal interpolation, dasymetric mapping, and change of support. The simplest form of areal interpolation is areal weighting, in which a homogeneous distribution of population is assumed to occur throughout each original choropleth map zone. Here a software implementation of the steps to perform areal pycnophylactic interpolation of brain surface area is available, using octavematlab. Despite numerous recent developments in intelligent areal interpolation methods, and studies that have demonstrated their clear advantage over simple areal. Areal weighting is the most basic form of areal interpolation whereby a homogeneous data distribution is assumed to occur within each choropleth map zone. Though dasymetric mapping has existed for well over a century, the methods for producing these maps have not been thoroughly examined. Validating the dasymetric areal interpolation method to.
Dasymetric mapping and areal interpolation are two such techniques. Brewer, 2001, dasymetric mapping and areal interpolation. Dasymetric maps of six socioeconomic variables were produced fm a study area of 159 counties in the eastern u. This paper proposes the application of a combination of dasymetric mapping and areal interpolation techniques to overcome the issues of. In the context of the discussion above areal interpolation based on dasymetric mapping has a number of attractive qualities that suggest it is well placed to overcome the inertia associated with simple areal weighting. Areal interpolation extension for arcgis geonet, the esri.
Integrating areal interpolation and dasymetric refinement to resolve temporal incompatibilities in zoning systems sarah ehresman and matt ruther, ph. If population counts were taken at the county level, a demographer may need to downscale the data to predict the population of census blocks. Using a hybrid methodology of dasyametric mapping and data. Areal interpolation refers to the procedures for transferring attribute data from one partitioning of geographic space a set of source units to another a set of target units goodchild and lam 1980. Data may be collected for individual households, as shown by the four blocks on the left. In the entire areal interpolation workflow, this step takes the most time and is the most critical for obtaining accurate predictions. In contrast, research on areal interpolation has been more thorough and has examined methods of transferring data from one set of map zones to another, an issue that is applicable to dasymetric mapping. Of different methods fallen within this approach, the simplest method is the overlay method called by lam 1983. Areal interpolation is the data transfer from one zonal system to another. The goal is to change the parameters on the right so that most empirical covariances blue crosses fall within the confidence intervals red bars. In practice, dasymetric mapping is often considered a particular type of areal interpolation technique where source zone data are excluded from certain classes in a categorical ancillary data set.
Dasymetric mapping for disaggregating coarse resolution. We thus wish to judge the relative accuracy of the four methods of areal weighting, dasymetric mapping, point kriging, and krigingbased areal interpolation in our use case so we can proceed with the best estimation method for overlaying demographic and voting data. Implementation and evaluation, abstract dasymetric maps display statistical data in meaningful spatial zones. An accessible introduction can be found in mennis who defines dasymetric mapping as areal interpolation that uses ancillary additional and related data to aid in the areal interpolation process p32. It guides the redistribution of source zone values to target zones using auxiliary information as a spatial control. Intelligent dasymetric mapping and its application to areal interpolation article pdf available in cartography and geographic information science 333. Dasymetric maps are used instead of choropleth maps because they represent underlying data distributions more accurately.
A study of areal interpolation by dasymetric mapping. Jun 06, 2017 for more on the use of interpolation in water quality, see. Poddar, the methods i need are not available in geostatistical analyst extension. This paper proposes the application of a combination of dasymetric mapping and areal interpolation techniques to overcome the issues of coarse scale population data. Areal interpolation, dasymetric mapping, address points, cadastral data cartography and geographic information science, vol. Many areal interpolation methods can be incorporated into dasymetric mapping methods to improve the detail of a choropleth map below the level of the enumeration unit fisher. Areal interpolation differs from dasymetric modeling in that it assumes the boundaries of the target regions are arbitrary and that the variable being interpolated varies smoothly across the boundaries of the source and target regions. Other methods and approaches in dasymetric mapping include areal interpolation, filtered areal weighting using the binary method, filtering with land cover data, and cadastralbased expert dasymetric system. In reply to hoang pham nov 24, 2004 just last night i downloaded the trial version of genuine fractals to test against the photoshop 7 standard bicubic enlargement. In most gis literature, areal interpolation specifically means the reaggregation of data from one set of polygons the source polygons to another set of polygons the target polygons. Intelligent dasymetric mapping outperforms areal weighting, and. Wright in a 1936 map of cape cod cartographers use dasymetric mapping for population density over. Pdf intelligent dasymetric mapping and its application to areal. Transforming spatial data from one scale to another is a challenge in geographic analysis.
Despite numerous recent developments in intelligent areal interpolation methods, and studies that have demonstrated their clear. To that end, this study provides an example of dasymetric areal interpolation using the pre. When the geometry of a research area differs signifi. Review of arealinterpolation and dasymetricmapping approaches. Modeling sensitivity to accuracy in classified imagery. It is arguably the simplest and most common approach to areal interpolation, though it does have some drawbacks see the areal weighted interpolation vignette for details. Areal interpolation and dasymetric mapping are closely. Dasymetric mapping depicts quantitative areal data using boundaries that divide the area into zones of relative homogeneity with the purpose of better portraying the population distribution. The need to combine spatial data representing sociodemographic information across incompatible spatial units is a common problem for demographers.
Although this system is appropriate for the dissemination of large amounts of national demographic data, often the boundaries of the enumeration units do not reflect the distribution of the underlying statistical. In recent years, dasymetric interpolation techniques have witnessed fast development given new data sources, improved statistical assessment for estimating accuracy, and advancing multiple areal. Proceedings of the 12th annual gis research uk conference, university of east anglia, uk. Areal weighting assigns to each grid cell population value based on its percentage area of the host areal units mennis 2003. Areal interpolation and dasymetric mapping methods using. Intelligent dasymetric mapping and its application to. Dasymetric method of thematic mapping, which uses areal symbols to spatially classify volumetric data developed and named in 1911 by benjamin petrovich semenovtyanshansky popularized by j. Citeseerx dasymetric mapping and areal interpolation.
With the automated tool, we have the ability to map and analyze any area of interest provided the appropriate data sources. Google scholar crossref fisher, p f, langford, m, 1995, modelling the errors in areal interpolation between zonal systems by monte carlo simulation environment and. Areal interpolation transfers data into a common dataset for use in analysis and comparison mennis, 2003. Geographic information system software to remodel population. Ijgi free fulltext areal interpolation using parcel and census. Jan 22, 2020 tobler is a python package for areal interpolation, dasymetric mapping, and change of support. A survey of previous literature on this subject points out that the most effective methods for areal interpolation are the intelligent approaches, which often take twodimensional 2d land use or onedimensional 1d road network information as ancillary data to give insight on the underlying distribution of a variable. Sep 19, 2007 the need to combine spatial data representing sociodemographic information across incompatible spatial units is a common problem for demographers. Areal interpolation is mostly an areal weighting procedure and does not take ancillary sources into consideration when the spatial distribution of data is refined.
Volumepreserving methods called the areabased areal interpolation approach overcome the aboveshortcoming of nonvolumepreserving methods because no point interpolation process is required. Integrating areal interpolation and dasymetric refinement to. System software to remodel population data using dasymetric mapping methods. A particular concern is computing small area trends when aggregation zone boundaries change during the trend interval. Estimation of spatial distribution of heavy metals in groundwater using interpolation methods and multivariate statistical techniques. A third type of simple areal interpolation is based on pointbased areal interpolation lam 1983. Peek, md, mph, msc section of general internal medicine, university of chicago chicago center for diabetes translation research. For example, demographers frequently need to downscale or upscale the administrative units of their data. To that end, this study provides an example of dasymetric areal interpolation using the preclassified land cover data available.
Areal interpolation differs from dasymetric modeling. Areal interpolation between one partitioning of geographical space and another remains an important topic, particular in terms of population counts and related statistics which are often required in order to compute an incidence ratio. Kentucky state data center, university of louisville. In the context of dasymetric mapping, where data are redistributed to subchoropleth map zone units via overlay with an area. Areal interpolation is needed to estimate attribute information for different geographic. Cartography and geographic information science 28 2, 12538. Inspired by this work, we tested five dasymetric mapping methods, including methods derived from work on areal interpolation. A local polycategorical approach to areal interpolation. Enhancing areal interpolation frameworks through dasymetric. Geographic information system software to remodel population data using dasymetric mapping methods. Eicher, c, brewer, c, 2001, dasymetric mapping and areal interpolation. This approach requires intensive data, so spatially extensive attributes are first converted into density values. Demographic data is usually represented by a choropleth map, where the statistical data is aggregated to areal units. Choropleth map top and dasymetric map bottom of astoria, oregon from figure.
As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the united states, we examined methods to estimate mortality within zones at varying distances from these. Mar 29, 2019 areal weighting is a type of an areal interpolation used to transform geographic data from one set of boundaries to another. Predictions and standard errors can be made for all points within and between the input polygons, and predictions along with standard errors can then be. Areal interpolation and dasymetric mapping methods using local ancillary data sources. Areal weighting is a type of an areal interpolation used to transform geographic data from one set of boundaries to another.
The typology delineates methods for combining choropleth and areaclass maps. Comparison of population distribution models using areal. The process of dasymetric mapping is the transformation of data from a set of arbitrary source zones to a dasymetric map via the overlay of the source zones with an ancillary data set. Intelligent dasymetric mapping and its comparison to other. Areal interpolation of population counts using preclassified. Using geographically weighted regression to solve the areal. Creating an extension that overcomes the obstacles inherent in dasymetric mapping, the method becomes transferable to a wider spectrum of users.
Areal interpolation refers to interpolation using polygons or areas. In recent years, dasymetric interpolation techniques have witnessed fast development given new data sources, improved statistical assessment for. Implementation and evaluation cartography and geographic information science 28 125 8. To overcome inconsistent spatial units between hospital discharge data and health policy needs in chicago, we developed and evaluated a dasymetric areal interpolation method, which disaggregates and allocates incidence rates from zip code to chicago community area.
Data interpolation food and agriculture organization. The method can be used for area itself, or for of any other quantity that needs massconservative interpolation, including cortical volumes and possibly other measurements. Dasymetric modelling of population distribution large data. Validating the dasymetric areal interpolation method to inform health policy chieko maene, ms social sciences computing services, university of chicago monica e. The approaches considered are the weighted areal interpolation in the text interpolazione areale ponderata, iap and the intelligent dasymetric mapping. Modeling the errors in areal interpolation between zonal systems by monte carlo simulation. Community level rates of diabetesrelated hospitalizations were.
Dasymetric spatiotemporal interpolation request pdf. All of these studies suggest that the accuracy of areal interpolation depends on a combination of factors, including method used, the nature of the variable being interpolated, the nature of the ancillary data, and the shape and size of both the source and target zones. There are six types of areal interpolation models included in this study. Areal interpolation involves the transfer of data often socioeconomic statistics and especially population data from one zonation of a region to another, where the two zonations are geographicall. Geographic information system software to remodel population data using dasymetric mapping methods by rachel sleeter and michael gould 2007 choropleth map top and dasymetric map bottom of astoria, oregon from figure 11. Jan 01, 2014 areal interpolation and dasymetric modeling are similar in that both are methods for downscaling spatial data. Fundamentals of geographic information systems 0 citeseerx. Areal interpolation and dasymetric modeling are similar in that both are methods for downscaling spatial data. Mrozinski and cromley 1999 provide a helpful typology of areal interpolation within which dasymetric mapping may be placed. A survey of previous literature on this subject points out that the most effective methods for areal interpolation are the intelligent approaches, which often take twodimensional 2d land use or onedimensional 1d road network information as ancillary data to give insight on the underlying distribution of a.
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