Thesis Format

Monograph

Resolving Street Canyon Elements for Microscale Urban Climate Models with Ground-Based Lidar

Author

Steffen F. Shaigec Mr., Western UniversityFollow

Degree

Master of Science

Program

Geography and Environment

Collaborative Specialization

Planetary Science and Exploration

Supervisor

Voogt, James A.

Abstract

Numerical models used to study urban microclimates require high-resolution data of canyon structures and vegetation morphologies to resolve microscale urban form; however, current morphologic data acquisition methods are limited by technical constraints, time, and cost. This thesis assessed the accuracy of three linear LiDAR platforms (backpack, vehicle, and fused ground-and-aerial) against legacy measurements of building and street tree morphology. The results show that: (1) generally, the fused data product performed best, followed by the backpack; (2) the backpack and vehicle-based approaches were constrained in measuring building heights above 50 meters but excelled when measuring characteristics underneath street tree canopies, such as trunk height and diameter. Using (3) SLAM for the vehicle-MLS over GNSS and IMU-based positioning produced a low-cost platform, but did not achieve themodels, although the methods may be sufficient for microscale models with +4 m grid spacings.

Summary for Lay Audience

Urban areas are warming, and extreme heat events seriously threaten human health. An increasing population is exposed to this risk due to increasing urbanization and global warming. Urbanization leads to changes in local morphology and surface cover, replacing natural environments with roads, buildings, parks, and other built features, all of which modify the local climate. This climate modification occurs both city-wide and along a street. At the street scale, the structure of surrounding buildings and trees significantly influences the pedestrian-level climate, affecting air temperature, surface temperature, humidity, wind speed and direction, and water retention. Climate-conscious design and heat adaption strategies can improve pedestrian comfortability. Implementing such strategies requires urban climate models, which simulate the effects of built and vegetated structures. To be accurate, urban climate models need high-resolution data detailing the urban structures. Current data collection methods are limited by technical constraints, time, and cost, motivating new methods to collect multiple characteristics simultaneously. This study evaluates the feasibility of three light detection and ranging (LiDAR) systems: backpack, vehicle-based and fused ground-and-aerial. To assess the accuracy and precision of LiDAR, height and width measurements were obtained from buildings and trees (including tree trunks and canopy) across four streets in London, Ontario, Canada and compared to proven legacy methods. Each LiDAR method showed various performance levels for each characteristic; generally, the fused data product performed the best, followed by the backpack. The vehicle-based and backpack approaches were limited in measuring building heights above 50 meters but excelled when measuring characteristics underneath street tree canopies, such as trunk height and diameter. Both approaches performed data collection ten times faster than the legacy methods, but the significant data processing with LiDAR resulted in a similar time to obtain measurements. Overall, the thesis demonstrates the potential of ground-based and fused LiDAR data to obtain measurements of urban morphology. The accuracy of the LiDAR methods is not currently adequate for the highest-resolution urban climate models (e.g. CFD) without further improvements, but it may be sufficient for lower-resolution microscale models. Further work is required to streamline processing to qualify feasibility as a complete replacement for legacy methods.

Recommended Citation

Shaigec, Steffen F. Mr., "Resolving Street Canyon Elements for Microscale Urban Climate Models with Ground-Based Lidar" (2024). Electronic Thesis and Dissertation Repository. 10269.
https://ir.lib.uwo.ca/etd/10269

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.