Predicting Local Climate Zones using Urban Morphometrics and Satellite Imagery

TL;DR

This study assesses the potential of urban morphometrics and satellite imagery fusion to predict Local Climate Zones, revealing limited and site-dependent effectiveness, and highlighting the tenuous link between urban form measures and LCZ types.

Contribution

It introduces a comprehensive morphometric approach to predict LCZs and evaluates the benefits of combining morphometrics with satellite imagery, revealing their inconsistent predictive power.

Findings

Morphometrics alone show inconsistent LCZ prediction accuracy across sites.

Fusion of morphometrics and imagery improves accuracy modestly at some sites.

The relationship between urban form measures and LCZ types is tenuous and site-dependent.

Abstract

The Local Climate Zone (LCZ) framework is commonly employed to represent urban form in morphological analyses despite its mapping predominantly relies on satellite imagery. Urban morphometrics, describing urban form via numerical measures of physical aspects and spatial relationships of its elements, offers another avenue. This study evaluates the ability of morphometric assessment to predict LCZs using a) a morphometric-based LCZ prediction, and b) a fusion-based LCZ prediction combining morphometrics with satellite imagery. We calculate 321 2D morphometric attributes from building footprints and street networks, covering their various properties at multiple spatial scales. Subsequently, we develop four classification schemes: morphometric-based prediction, baseline image-based prediction, and two techniques fusing morphometrics with imagery. We evaluate them across five sites. Results from the morphometric-based prediction indicate that the correspondence between 2D urban morphometrics and urban LCZ types is selective and inconsistent, rendering the efficacy of this method site-dependent. Nevertheless, it demonstrated that a much broader range of urban form properties is relevant for distinguishing LCZ types compared to standard parameters. Relative to the image-based baseline, the fusion yielded relatively distinct accuracy improvements for urban LCZ types at two sites; however, gains at the remaining sites were negligible or even slightly negative, suggesting that the benefits of fusion are modest and inconsistent. Collectively, these results indicate that the relationship between the LCZs and the measurable, visible aspects of urban form is tenuous, thus the LCZ framework should be used with caution in morphological studies.