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HIGH-RESOLUTION DATASET OF URBAN CANOPY PARAMETERS FOR HOUSTON, TEXAS
Citation:
Burian, S., S. W. Stetson, W. Han, J.K S. Ching, AND D W. Byun. HIGH-RESOLUTION DATASET OF URBAN CANOPY PARAMETERS FOR HOUSTON, TEXAS. Presented at 5th Symposium on the Urban Environment, Vancouver, BC, Canada, August 23-27, 2004.
Impact/Purpose:
The objective of this task is to develop and evaluate numerical and physical modeling tools for simulating ground-level concentrations of airborne substances in urban settings at spatial scales ranging from ~1-10 km. These tools will support client needs in the areas of air toxics and homeland security. The air toxics tools will benefit the National Air Toxics Assessment (NATA) program and human exposure modeling needs within EPA. The homeland security-related portion of this task will help in developing tools to assess the threat posed by the release of airborne agents. Both sets of tools will consider the effects induced by urban morphology on fine-scale concentration distributions.
Description:
Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the representation of urban morphological structures requires much greater detail. To provide the most accurate surface characterization possible for an air quality modeling study of Houston, Texas, airborne LIDAR (Light Detection and Ranging) data were obtained from TerraPoint LLC at 1-m horizontal grid cell spacing for Harris County, Texas, an area of approximately 5800 km2. The data were managed in a GIS software package and scripts and codes were written in Avenue, VBA, and Fortran to compute 20 urban canopy parameters (UCPs) including building height statistics and histograms, height-to-width ratio, plan area density function, frontal area density function, roughness length, displacement height, mean orientation of streets, and sky view factor. In addition, procedures were developed to approximate several UCPs that could not be determined from the LIDAR elevation data, including surface cover type, building material fraction, and percent directly connected impervious area. In this paper, we describe the Houston dataset derivation techniques and results, report on correlations of the UCPs to land use, population, and other nationally consistent datasets, as well as reporting on the accuracy of methods to extrapolate UCPs to outlying areas of the city where high-resolution full-feature terrain datasets are not available.
This paper has been reviewed in accordance with the United States Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication.