Comparison of Dasymetric Mapping Techniques for Small-Area Population Estimates
نویسندگان
چکیده
Dasymetric mapping techniques can be employed to estimate population characteristics of small areas that do not correspond to census enumeration areas. Land cover has been the most widely used source of ancillary data in dasymetric mapping. The current research examines the performance of alternative sources of ancillary data, including imperviousness, road networks, and nighttime lights. Nationally available datasets were used in the analysis to allow for replicability. The performance of the techniques used to examine these sources was compared to areal weighting and traditional land cover techniques. Four states were used in the analysis, representing a range of different geographic regions: Connecticut, New Mexico, Oregon, and South Carolina. Ancillary data sources were used to estimate census block group population counts using census tracts as source zones, and the results were compared to the known block group population counts. Results indicate that the performance of dasymetric methods varies substantially among study areas, and no single technique consistently outperforms all others. The three best techniques are imperviousness with values greater than 75 percent removed, imperviousness with values greater than 60 percent removed, and land cover. Total imperviousness and roads perform slightly worse, with nighttime lights performing the worst compared to all other ancillary data types. All techniques performed better than areal weighting.
منابع مشابه
The role of spatial representation in the development of a LUR model for Ottawa, Canada
A land use regression (LUR) model for the mapping of NO(2) concentrations in Ottawa, Canada was created based on data from 29 passive air quality samplers from the City of Ottawa's National Capital Air Quality Mapping Project and two permanent stations. Model sensitivity was assessed against three spatial representations of population: population at the dissemination area level, population at t...
متن کاملRegionalisation of asset values for risk analyses
In risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population densit...
متن کاملDasymetric Mapping Techniques for the San Francisco Bay Region, California
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...
متن کاملGenerating Surface Models of Population Using Dasymetric Mapping*
Aggregated demographic datasets are associated with analytical and cartographic problems due to the arbitrary nature of areal unit partitioning. This article describes a methodology for generating a surface-based representation of population that mitigates these problems. This methodology uses dasymetric mapping and incorporates areal weighting and empirical sampling techniques to assess the re...
متن کاملCultural Dasymetric Population Mapping with Historical GIS: A Case Study from the Southern Appalachians
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 intera...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011