Abstract

Urban areas globally are vulnerable to warming climate trends exacerbated by their growing populations and heat island effects. The Local Climate Zone (LCZ) typology has become a popular framework for characterizing urban microclimates in different regions using various classification methods, including a widely adopted pixel-based protocol by the World Urban Database and Access Portal Tools (WUDAPT) Project. However, few studies to date have explored the potential of object-based image analysis (OBIA) to facilitate classification of LCZs given their inherent complexity, and few studies have further used the LCZ framework to analyze land cover changes in urban areas over time. This study classified LCZs in the Salt Lake Metro Region, Utah, USA for 1993 and 2017 using a supervised object-based analysis of Landsat satellite imagery and assessed their change during this time frame. The overall accuracy, measured for the most recent classification period (2017), was equal to 64% across 12 LCZs, with most of the error resulting from similarities among highly developed LCZs and non-developed classes with sparse or low-stature vegetation. The observed 1993–2017 changes in LCZs indicated a regional tendency towards primarily suburban, open low-rise development, and large low-rise and paved classes. However, despite the potential for local cooling with landscape transitions likely to increase vegetation cover and irrigation compared to pre-development conditions, summer averages of Landsat-derived top-of-atmosphere brightness temperatures showed a pronounced warming between 1992–1994 and 2016–2018 across the study region, with a 0.1–2.9 °C increase among individual LCZs. Our results indicate that future applications of LCZs towards urban change analyses should develop a stronger understanding of LCZ microclimate sensitivity to changes in size and configuration of urban neighborhoods and regions. Furthermore, while OBIA is promising for capturing the heterogeneous and multi-scale nature of LCZs, its applications could be strengthened by adopting more generalizable approaches for LCZ-relevant segmentation and validation, and by incorporating active remote sensing data to account for the 3D complexity of urban areas.

Highlights

  • Worldwide expansion and warming of urban regions present an important concern for the well-being of their residents, creating an urgent need for cost-effective strategies to track changing microclimates and inform current and future planning [1,2,3,4]

  • Our results show that urbanization of the study area during this period was accompanied by several notable Local Climate Zone (LCZ) transformations, the expansion of open low-rise development common in residential neighborhoods and large low-rise and paved LCZs common in commercial/industrial areas

  • While hypothetically the observed transitions could be expected to produce both local warming and local cooling, the mean values for Landsat-based surface temperature increased for all LCZs by 0.1-2.9◦C, showing the warming tendency across the vast majority of the region

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Summary

Introduction

Worldwide expansion and warming of urban regions present an important concern for the well-being of their residents, creating an urgent need for cost-effective strategies to track changing microclimates and inform current and future planning [1,2,3,4]. Previous research has extensively focused on urban heat island (UHI) phenomena manifested in significantly higher temperatures of cities compared to their surroundings due to unique thermal properties of urban land cover/use (LULC), building materials, human activities and other factors [5,6,7,8,9] Increases in both ambient urban temperatures and frequency of extreme heat events [10] pose major threats to human health, especially in areas with higher population densities and vulnerable social and demographic groups [1,2,11]. We subsequently discuss the strengths and challenges in applying OBIA towards LCZ classification from medium-resolution imagery, reflect on the potential of LCZs to characterize long-term urban transformation and outline key future research needs and potential directions

Background on LCZ Applications and Alternative Mapping Methodologies
The Potential of Object-Based Image Analysis for LCZ Mapping
SSttuuddyy AArreeaa
20 July 1993
Image Classification
F: Bare Soil or Sand G
LCZ Change Analysis
Changes in the Proxy of Surface Temperature
Supervised Classification of LCZs
Successes and Challenges in Object-Based LCZ Classification
Other Key Lessons and Future Research Directions
Conclusions

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