DASYMETRIC MAPPING TECHNIQUES FOR THE SAN FRANCISCO BAY REGION, CALIFORNIA (original) (raw)
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Dasymetric mapping techniques for the San Francisco Bay region
2015
Abstract: Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census block-group populations of Alameda County, California using the U.S. Geological Survey’s 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method pr...
A New Interpretation of the Dasymetric Mapping Method: Abstract and Table of Contents
We all want governmental agencies to use the most accurate and realistic depiction of the real world during their decision-making process. For more than 200 years one critical component to that process has been choropleth maps. A major obstacle for geographers as they attempt to present actionable information has been to precisely assign population data available for one set of geographic areal units, for instance census tracts, to the geographies of primary interest, such as neighborhood or police beat. This restriction, known as spatial incongruity, is commonplace for applied demographers trying to create maps used in the decision-making processes for customized geographies. We will cover three historic models that attempt to resolve this predicament of spatial incongruity including choropleth mapping, areal interpolation, and dasymetric mapping, and then we will introduce our new interpretation of dasymetric mapping that includes the use of publicly available housing information to create a better model for population distribution and allow geographers to assign precise and realistic population distribution estimates to any custom geographic boundary of interest. Our new technique, if successful, will overcome many of the limitations found in the previous iterations of population distribution models and will be adopted by governmental officials and other decision-makers. We believe that linking publicly available population data with publicly available parcel level land use data, through a 19-step process, can potentially make the maps we use in the decision-making process more accurate and more widely available for use by non-governmental agencies.
Cartography and …, 2007
This paper discusses the importance of determining an accurate depiction of total population and specific sub-population distribution for urban areas in order to develop an improved "denominator," which would enable the calculation of more correct rates in GIS analyses involving public health, crime, and urban environmental planning. Rather than using data aggregated by arbitrary administrative boundaries such as census tracts, we use dasymetric mapping, an areal interpolation method using ancillary information to delineate areas of homogeneous values. We review previous dasymetric mapping techniques (which often use remotely sensed land-cover data) and contrast them with our technique, Cadastralbased Expert Dasymetric System (CEDS), which is particularly suitable for urban areas. The CEDS method uses specific cadastral data, land-use filters, modeling by expert system routines, and validation against various census enumeration units and other data. The CEDS dasymetric mapping technique is presented through a case study of asthma hospitalizations in the Bronx, New York City, in relation to proximity buffers constructed around major sources of air pollution. The case study shows the impact that a more accurate estimation of population distribution has on a current environmental justice and health disparities research project, and the potential of CEDS for other GIS applications.
Improving Dasymetric Population Estimates for Land Parcels: Data Pre-processing Steps
2018
Abstract:The Cadastral-based Expert Dasymetric System (CEDS) is an established and effective areal interpolation technique for mapping populations by disaggregating census data from coarse collection units to smaller property parcels. Frequently, the boundaries of census units (whether tract, block group or block level in the United States) and the boundaries of parcels do not geometrically align completely, resulting in populations being erroneously assigned to neighboring parcels. In addition, property cadasters typically do not contain information on group living—nursing homes, college dormitories, correctional institutions, military quarters, and shelters—resulting in undercounting. As the two shortcomings are inter-related, we propose a pre-processing stage prior to implementing CEDS. The stage involves corrections for incongruent spatial geometries and cross-tabulation of census Group Quarter data with property cadastral parcels to improve estimations of group living. We test ...
2021
The wide availability of remote sensing data, the development of computer technology, and the accessibility of census data in the digital form created new opportunities for highly accurate population estimates. Of particular scientific interest is the method of dasymetric mapping, which can significantly improve the spatial accuracy of mapping socio-demographic processes. In addition to population density, the method has considerable potential in mapping the distribution of other social, economic and demographic variables, such as income level, crime, ethnicity, etc. Another significant gap in the existing studies is the development of three-dimensional dasymetric mapping methods. This study is focused on developing intelligent dasymetric mapping methods to create algorithms for near real-time display demographic and other socio-economic parameters and assess their accuracy and their potential for geovisual analytics. The study is developed and tested in Minneapolis-Saint Paul area, Minnesota, USA as a key study site given the relative diversity of urban areas and the accessibility for field surveys. The goal of this study is to develop and test an effective geospatially-intelligent method and GIS algorithm for the creation of multivariable three-dimensional dasymetric (3DM) geographic visualizations for the Twin Cities Metropolitan area. 2D and 3D binary dasymetric mapping methods, as well as floor fraction and intelligent dasymetric mapping method were used to identify the best performing method in terms of accuracy. The 3D dasymetric mapping method yielded the best accuracy in estimation of population counts in conditions of the given study area. 3D dasymetric mapping method proved to improve the accuracy of population mapping in an urban environment compared to 2D methods. The improvement is more significant at a smaller scale of analysis that reflects a more heterogeneous residential building infrastructure. Finally, the additional socio-economic variables, such as aggregated income and three different types of spending (for food, household supplies, and apparel) were mapped. The study faced the limitations of the inability to obtain data, perfectly synchronized in time between all the spatial layers, non-straightforward nature of the selection of residential/non-residential buildings and low height variance in the study area. The future directions of the study are to integrate the developed methods with the existing web mapping platform, test the dasymetric mapping approach on the extended set of socioeconomic variables and explore the usefulness of the dasymetric mapping approach on the smaller scales of the enumeration units and dasymetric mapping polygons.
Current Urban Studies, 2016
It is well-known that, when dealing with density of population, most of the proposed maps choose the easiest and probably the most understandable cartographic method, i.e. the choropleth method. Nevertheless, for heterogonous spaces and those observing intense spatial dynamic, it is proven that this method has many lacks and deficiencies. This is the case of Jeddah city (the second largest city in Saudi Arabia), which is a very contrasted urban place with regards to its social structure, spatial organization and land use besides the fact that it witnesses a profound and continuous urban growth. Yet, most of the planning decisions are often taken on these types of maps and may mislead the urban planners. In this context, the dasymetric maps reveal very useful because they may give the real distribution of the population. Therefore, we think that establishing a dasymetric map at a convenient scale with regards to the results of satellite image processing may help the planners and the geographers as well as the common users. Indeed, this method may be an interesting alternative to the classic choropleth map. First it may improve our estimations towards the density within the various areas of the districts. Second it may refine the original enumeration units often using the administrative apportionment and therefore help the planning and agricultural agencies when establishing their base maps. The satellite image processing and GIS were used as tools in this study.