An innovative method for dasymetric mapping: A case of New York City

Authors: Khila Dahal*, Temple University
Topics: Geographic Information Science and Systems, Quantitative Methods, Spatial Analysis & Modeling
Keywords: Keywords: cadastral parcels, dasymetric mapping, areal interpolation, census geographic units, disaggregation
Session Type: Poster
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded

Cadastral parcels, which come with numerous data attributes, are increasingly being used in fine-scale modeling of socioecological and environmental processes, which itself has coincided with a profusion of advances in computational sciences and availability of these local datasets in recent years. However, the parcel datasets lack population counts and other demographic variables even for highly resource rich locations including New York City. One reason for this paucity of local level demographic data is the fact that national censuses are still the only source of population data, which they publish as aggregates at coarser geographical units such as blocks and tracts. Since accurate demographic and economic information is part and parcel of any such fine-scale study, it is important to transfer census data to cadastral lots. This study outlines an innovative methodology to disaggregate census data to finer-scale areal units of cadastral lots. The proposed dasymetric modeling framework uses residential units as the main ancillary variable employing a heuristics-based expert system and vector-only spatial operations. Census blocks and cadastral lots serve as the source and target areal units respectively. A validation of the model estimates using census block dataset as the reference demonstrates a superior performance of our modeling framework over the existing dasymetric methods.

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