Application of airborne remote sensing data on mapping local climate zones: Cases of three metropolitan areas of Texas, U.S.

Abstract

Urban and vegetation morphology profiles are important factors in local climate-related studies, but they are not as easily measured as land cover information to study urban landscape at metropolitan area. This study aims to develop a GIS-based Local Climate Zones (LCZs) mapping scheme to map and compare the LCZs for three major metropolitans in Texas: Dallas-Fort Worth (DFW), Austin, and San Antonio. Based on an analysis of the land cover and urban morphology, variables including land cover, height of roughness elements, building surface fraction, pervious surface fraction (PSF), and land use planning codes were generated and selected as LCZs classification properties. Then we designed the LCZs mapping scheme with decision-making algorithm was built for LCZs mapping. The key findings of LCZs of our study areas are that: 1) Most of the urbanized area are categorized into LCZ “open” types (characterized by building surface fraction of 15–40% and pervious surface fraction of 30–60%) for all three metropolitan areas with different proportions and spatial diversity; 2) LCZ D Low plants is dominant in areas surrounding DFW, while LCZ A Dense trees and LCZ D Low plants are dominant in Austin and San Antonio with clear regional contrast; 3) LCZs maps are in accordance with the underlying regional environment of the areas. Our study indicated that LiDAR-derived products can support LCZs mapping to identify urban morphological information and standardize the mapping scheme for further comparative studies of metropolitan areas.