Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems

Hongbo He, Xiaohan Liao, Huping Ye (), Chenchen Xu and Huanyin Yue
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Hongbo He: State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaohan Liao: State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Huping Ye: State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Chenchen Xu: State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Huanyin Yue: State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Sustainability, 2023, vol. 15, issue 16, 1-20

Abstract: With the rapid increase in unmanned aerial vehicles (UAVs), ensuring the safety of airspace operations and promoting sustainable development of airspace systems have become paramount concerns. However, research dedicated to investigating the population exposure risks of UAV operations in urban areas and their spatial pattern is still missing. To address this gap, this study evenly divides the urban space into uniform grids and calculates critical areas for two UAV types within each grid. By integrating geospatial data, including buildings, land use, and population, data-driven risk maps are constructed to assess the spatial distribution patterns and potential population exposure risks of two UAV types and compare them with commonly used census units. The results indicate that the mean time between failures (MTBF) for the selected generic and rotary-type UAVs can be up to 9.04 × 10 8 h and 1.22 × 10 8 h, respectively, at acceptable risk levels, considering uncertainties. The spatial pattern of population exposure risk exhibits spatial heterogeneity and multi-scale effects in urban areas, aligning with population distribution. High-risk areas concentrate in regions characterized by high population mobility, such as transport hubs, commercial service areas, residential zones, and business districts. Additionally, the comparation emphasizes the potential bias introduced by using census units in risk assessment, especially in regions with significant urban build-up. This framework enables the evaluation of safety and acceptability across diverse urban land use areas and offers guidance for airspace management in megacities, ensuring the safe integration of UAVs in urban environments.

Keywords: unmanned aerial vehicle; risk assessment; risk map; population exposure risk; airspace management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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