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...
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 ...
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.
Computers, Environment and Urban Systems, 2006
Interpolating population data between incompatible spatial zones is an important task in many GIS applications. This paper investigates whether regional regression models between population and land cover outperform a global approach, and whether the 3-class dasymetric method improves upon the binary dasymetric approach. In the experiments conducted, regional regressions resulted in better areal interpolation, but also highlighted spatial non-stationarity in the relationship between population and land cover. The benefits of a 3-class dasymetric model over a binary model were inconclusive. However, it is suggested that greater flexibility in model calibration to more fully incorporate spatial non-stationarity could improve 3-class dasymetric performance. Accurate urban residential density mapping is also important since the 3-class dasymetric method seems less robust than the binary approach to land cover classification error.
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.
Scientific Data
Assessment of socio-environmental problems and the search for solutions often require intersecting geospatial data on environmental factors and human population densities. In the United States, Census data is the most common source for information on population. However, timely acquisition of such data at sufficient spatial resolution can be problematic, especially in cases where the analysis area spans urban-rural gradients. With this data release, we provide a 30-m resolution population estimate for the contiguous United States. The workflow dasymetrically distributes Census block level population estimates across all non-transportation impervious surfaces within each Census block. The methodology is updatable using the most recent Census data and remote sensing-based observations of impervious surface area. The dataset, known as the U.G.L.I (updatable gridded lightweight impervious) population dataset, compares favorably against other population data sources, and provides a usefu...
Cultural Dasymetric Population Mapping with Historical GIS
International Journal of Applied Geospatial Research, 2011
There has been a recent flurry of interest in dasymetric population mapping. However, the ancillary coverages that underlie current dasymetric methods are unconnected to cultural context. The resulting regions may indicate density patterns, but not necessarily the boundaries known to inhabitants. Dasymetric population mapping is capable of capturing the cultural commonality and community interaction that define social spaces. Dasymetric mapping may be improved with methodologies that reflect the ways in which social spaces are established. This research applies a historical GIS methodology for identifying early 20th Century agricultural neighborhoods in southern Appalachia. The case study is intended to encourage discovery of additional methods for mapping population on the scale of lived experience.