Urban morphology parameters from global digital elevation models: implications for aerodynamic roughness for wind-speed estimation

Kent, C. W., Grimmond, S. ORCID: https://orcid.org/0000-0002-3166-9415, Gatey, D. and Hirano, K. (2019) Urban morphology parameters from global digital elevation models: implications for aerodynamic roughness for wind-speed estimation. Remote Sensing of Environment, 221. pp. 316-339. ISSN 0034-4257 doi: 10.1016/j.rse.2018.09.024

Abstract/Summary

Urban morphology and aerodynamic roughness parameters are derived from three global digital elevation models (GDEM): Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), and TanDEM-X. Initially, each is compared to benchmark elevation data in London (UK). A moving window extracts ground heights from the GDEMs, generating terrain models with root-mean-square accuracy of up to 3 m. Subtraction of extracted ground heights provides roughness-element heights only, allowing for calculation of morphology parameters. The parameters are calculated for eight directional sectors of 1 km grid-squares. Apparent merging of roughness elements in all GDEMs causes height-based parameter underestimation, whilst plan and frontal areas are over- and under-estimated, respectively. Combined, these lead to an underestimation of morphometrically-derived aerodynamic roughness parameters. Parameter errors are least for the TanDEM-X data. Further comparison in five cities (Auckland, Greater London, New York, Sao Paulo, Tokyo) provides basis for empirical corrections to TanDEM-X-derived geometric parameters. These reduce the error in parameters across the cities and for a separate location. Meteorological observations in central London give insight to wind-speed estimation accuracy using roughness parameters from the different elevation databases. The proposed corrections to TanDEM-X parameters lead to improved wind-speed estimates, which combined with the improved spatial representation of parameters across cities demonstrates their potential for use in future studies.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/79656
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Elsevier
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