Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems
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...
Gespeichert in:
Veröffentlicht in: | Sustainability 2023-08, Vol.15 (16), p.12247 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 16 |
container_start_page | 12247 |
container_title | Sustainability |
container_volume | 15 |
creator | He, Hongbo Liao, Xiaohan Ye, Huping Xu, Chenchen Yue, Huanyin |
description | 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 × 108 h and 1.22 × 108 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. |
doi_str_mv | 10.3390/su151612247 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2857445967</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A762548463</galeid><sourcerecordid>A762548463</sourcerecordid><originalsourceid>FETCH-LOGICAL-c329t-71d07218ec060949cf6b26e97de1dad63d2a90baac4c7caf3d80aed62ec65c2a3</originalsourceid><addsrcrecordid>eNpVkU1v1DAQhqMKpFalJ_6AJU4IpfgjsTfcVm2hK1Vq1e2eo4k9WVyydvA40O0f4G8TtBzamcN86HnfOUxRvBf8XKmGf6ZJ1EILKStzVJxIbkQpeM3fvOiPizOiRz6HUqIR-qT4cwkZysvkf2Fgq0B--z0T8yFHdhfHaYDsY2BXT2OkKSG79_SDvrCH-BuSI7aeKIMP0A3IIDi2hh7ZJnUQ2NInGsHOY_aDfz74dHu2CTsIAR1bYvIwsPWeMu7oXfG2h4Hw7H89LTZfrx4ursub22-ri-VNaZVscmmE40aKBVqueVM1tted1NgYh8KB08pJaHgHYCtrLPTKLTig0xKtrq0EdVp8OPiOKf6ckHL7GKcU5pOtXNSmqupGm5k6P1BbGLD1oY85gZ3T4c7bGLD3835ptKyrRaXVLPj4SjAzGZ_yFiaidrW-f81-OrA2RaKEfTsmv4O0bwVv_32yffFJ9RfKBJG6</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2857445967</pqid></control><display><type>article</type><title>Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>He, Hongbo ; Liao, Xiaohan ; Ye, Huping ; Xu, Chenchen ; Yue, Huanyin</creator><creatorcontrib>He, Hongbo ; Liao, Xiaohan ; Ye, Huping ; Xu, Chenchen ; Yue, Huanyin</creatorcontrib><description>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 × 108 h and 1.22 × 108 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.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su151612247</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aircraft ; Aviation ; Datasets ; Geographic information systems ; Geography ; Geospatial data ; Population density ; Risk assessment ; Spatial data ; Sustainability ; Unmanned aerial vehicles ; Urban areas ; Urban land use</subject><ispartof>Sustainability, 2023-08, Vol.15 (16), p.12247</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c329t-71d07218ec060949cf6b26e97de1dad63d2a90baac4c7caf3d80aed62ec65c2a3</cites><orcidid>0000-0002-7900-2564 ; 0000-0003-3348-5174 ; 0000-0002-9114-205X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>He, Hongbo</creatorcontrib><creatorcontrib>Liao, Xiaohan</creatorcontrib><creatorcontrib>Ye, Huping</creatorcontrib><creatorcontrib>Xu, Chenchen</creatorcontrib><creatorcontrib>Yue, Huanyin</creatorcontrib><title>Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems</title><title>Sustainability</title><description>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 × 108 h and 1.22 × 108 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.</description><subject>Aircraft</subject><subject>Aviation</subject><subject>Datasets</subject><subject>Geographic information systems</subject><subject>Geography</subject><subject>Geospatial data</subject><subject>Population density</subject><subject>Risk assessment</subject><subject>Spatial data</subject><subject>Sustainability</subject><subject>Unmanned aerial vehicles</subject><subject>Urban areas</subject><subject>Urban land use</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpVkU1v1DAQhqMKpFalJ_6AJU4IpfgjsTfcVm2hK1Vq1e2eo4k9WVyydvA40O0f4G8TtBzamcN86HnfOUxRvBf8XKmGf6ZJ1EILKStzVJxIbkQpeM3fvOiPizOiRz6HUqIR-qT4cwkZysvkf2Fgq0B--z0T8yFHdhfHaYDsY2BXT2OkKSG79_SDvrCH-BuSI7aeKIMP0A3IIDi2hh7ZJnUQ2NInGsHOY_aDfz74dHu2CTsIAR1bYvIwsPWeMu7oXfG2h4Hw7H89LTZfrx4ursub22-ri-VNaZVscmmE40aKBVqueVM1tted1NgYh8KB08pJaHgHYCtrLPTKLTig0xKtrq0EdVp8OPiOKf6ckHL7GKcU5pOtXNSmqupGm5k6P1BbGLD1oY85gZ3T4c7bGLD3835ptKyrRaXVLPj4SjAzGZ_yFiaidrW-f81-OrA2RaKEfTsmv4O0bwVv_32yffFJ9RfKBJG6</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>He, Hongbo</creator><creator>Liao, Xiaohan</creator><creator>Ye, Huping</creator><creator>Xu, Chenchen</creator><creator>Yue, Huanyin</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-7900-2564</orcidid><orcidid>https://orcid.org/0000-0003-3348-5174</orcidid><orcidid>https://orcid.org/0000-0002-9114-205X</orcidid></search><sort><creationdate>20230801</creationdate><title>Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems</title><author>He, Hongbo ; Liao, Xiaohan ; Ye, Huping ; Xu, Chenchen ; Yue, Huanyin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c329t-71d07218ec060949cf6b26e97de1dad63d2a90baac4c7caf3d80aed62ec65c2a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aircraft</topic><topic>Aviation</topic><topic>Datasets</topic><topic>Geographic information systems</topic><topic>Geography</topic><topic>Geospatial data</topic><topic>Population density</topic><topic>Risk assessment</topic><topic>Spatial data</topic><topic>Sustainability</topic><topic>Unmanned aerial vehicles</topic><topic>Urban areas</topic><topic>Urban land use</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>He, Hongbo</creatorcontrib><creatorcontrib>Liao, Xiaohan</creatorcontrib><creatorcontrib>Ye, Huping</creatorcontrib><creatorcontrib>Xu, Chenchen</creatorcontrib><creatorcontrib>Yue, Huanyin</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>He, Hongbo</au><au>Liao, Xiaohan</au><au>Ye, Huping</au><au>Xu, Chenchen</au><au>Yue, Huanyin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems</atitle><jtitle>Sustainability</jtitle><date>2023-08-01</date><risdate>2023</risdate><volume>15</volume><issue>16</issue><spage>12247</spage><pages>12247-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><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 × 108 h and 1.22 × 108 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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su151612247</doi><orcidid>https://orcid.org/0000-0002-7900-2564</orcidid><orcidid>https://orcid.org/0000-0003-3348-5174</orcidid><orcidid>https://orcid.org/0000-0002-9114-205X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2071-1050 |
ispartof | Sustainability, 2023-08, Vol.15 (16), p.12247 |
issn | 2071-1050 2071-1050 |
language | eng |
recordid | cdi_proquest_journals_2857445967 |
source | MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals |
subjects | Aircraft Aviation Datasets Geographic information systems Geography Geospatial data Population density Risk assessment Spatial data Sustainability Unmanned aerial vehicles Urban areas Urban land use |
title | Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T16%3A16%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Data-Driven%20Insights%20into%20Population%20Exposure%20Risks:%20Towards%20Sustainable%20and%20Safe%20Urban%20Airspace%20Utilization%20by%20Unmanned%20Aerial%20Systems&rft.jtitle=Sustainability&rft.au=He,%20Hongbo&rft.date=2023-08-01&rft.volume=15&rft.issue=16&rft.spage=12247&rft.pages=12247-&rft.issn=2071-1050&rft.eissn=2071-1050&rft_id=info:doi/10.3390/su151612247&rft_dat=%3Cgale_proqu%3EA762548463%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2857445967&rft_id=info:pmid/&rft_galeid=A762548463&rfr_iscdi=true |