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Abstract
In this paper, we demonstrate three unique use cases of LiDAR data and processing, which can be implemented in an urban metropolis to determine the challenges that are associated with climate change. LiDAR data for the City of Toronto were collected in April 2015 with a density of 10 points/m2. We utilized both a digital terrain model and a bare earth digital elevation model in this work. The first case study estimated storm water, in which we compared flow accumulation values and catchment areas generated with a 20-m DEM and a 1-m LiDAR DEM. The finer resolution DEM demonstrated that the urban street features play a significant role in flow accumulation by directing flows. Urban catchment areas were found to occur on spatial scales that were smaller than the 20-m DEM cell size. For the second case study, the solar potential in the City of Toronto was calculated based on the slope and aspect of each land parcel. According to area, 56% of the city was found to have high solar potential, with 33% and 11% having medium and low solar potential. For the third case study, we calculated the building heights for 16,715 high-rise buildings in Toronto, which were combined with ambulance and fire emergency response times required to reach the base of the building. All buildings that had more than 17 stories were within a 5-min response time for both fire and ambulance services. Only 79% and 88% of these buildings were within a 3-min response time for ambulance and fire emergencies, respectively. LiDAR data provides a highly detailed record of the built urban environment and can provide support in the planning and assessment of climate change resilience activities.
Highlights
Over one-half of the world’s population resides in urban areas and urbanization is expected to increase throughout the remainder of the 21st century [1,2,3]
We demonstrated the ability of Light detecting and ranging (LiDAR) data to include urban features in the assessment, we mapped out the solar potential for all city-owned building roofs and we calculated response times based on 3D data for emergency responders
We demonstrated the increased level of detail that is available when a LiDAR-derived digital elevation model (DEM) is utilized for flood modelling, which has 1-m resolution compared to a workflow that utilizes the commonly available 20-m DEM
Summary
Over one-half of the world’s population resides in urban areas and urbanization is expected to increase throughout the remainder of the 21st century [1,2,3]. These climate change challenges can include improving water drainage on the transportation networks (local roads), the development of green roofs and creating modern hazard-event evacuation plans [6] The implementation of these actions requires the creation of a significant data collection program and subsequent data processing activities due to the high density and large scale of modern cities. The case studies include urban flood modelling, solar energy generation potential and emergency response planning. We demonstrated the ability of LiDAR data to include urban features (e.g., curbs that direct water) in the assessment, we mapped out the solar potential for all city-owned building roofs and we calculated response times based on 3D data for emergency responders.
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