Estimating Urban Canopy Parameters Using Synthetic Aperture Radar Data

Abstract

Abstract This paper introduces a remote sensing–based approach to rapidly derive urban morphological characteristics using radar satellite data. The approach is based on the expectation that the magnitude of the synthetic aperture radar (SAR) backscatter can be related to urban canopy parameters (UCPs) describing the height, density, and roughness of buildings, trees, and other objects in cities. This hypothesis was tested with full-feature terrain elevation and SAR datasets for the Houston, Texas, metropolitan area. The backscatter magnitude was found to vary as expected across the city with higher backscatter values in the downtown tall building district relative to adjacent residential and commercial areas. To demonstrate the concept of using radar backscatter to estimate UCPs, relationships were derived between SAR backscatter and mean height, plan area fraction, and frontal area index of roughness elements (e.g., buildings and trees). In addition, SAR backscatter relationships were derived with roughness lengths computed using morphometric approaches. In all cases, the derived relationships were found to provide estimates of UCPs acceptable for use in meteorological models. Further testing using data from the Salt Lake City, Utah, metropolitan area validated the relationships and identified key areas for improvement for future research, including SAR instrument view angle differences and buildings split between SAR pixels.