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- Publisher Website: 10.1080/01431161.2024.2391582
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Article: Small unmanned aerial vehicle (UAV)-based detection of seasonal micro-urban heat islands for diverse land uses
Title | Small unmanned aerial vehicle (UAV)-based detection of seasonal micro-urban heat islands for diverse land uses |
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Authors | |
Keywords | drones extreme temperature remote sensing urban heat island Urbanization |
Issue Date | 2024 |
Citation | International Journal of Remote Sensing, 2024 How to Cite? |
Abstract | Metropolitan areas have diverse land uses (LUs), which can also cause significant differences in land surface temperature (LST), leading to the formation of micro-urban heat islands (MUHIs). Measuring the MUHIs is significant for heat mitiga-tion and adaptation measures and requires high spatial-temporal resolution, which is not feasible through coarser satellite observations (CSOs). Thermal cameras onboard unmanned aerial vehicles (UAVs) can detect such MUHIs because of their high spatial and desired temporal resolution. This study used the Zenmuse H20T onboard a UAV providing LST at ∼8 cm resolution to evaluate MUHIs in an area with diverse and contiguous LUs including three urban built-up LUs: 1) residential high cost (RHC), 2) residential low cost (RLC), 3) industrial area (IA) and one natural area (i.e. park area (PA)). The LST and MUHI were estimated in two seasons: fall (October 2022) and summer (June-July 2023). In each season, six flights were conducted at similar times of day. The findings were compared with Landsat in each season to examine the loss of information between coarser and finer spatial resolution. Using UAV, a maximum MUHI of 25.54◦C and 15.85◦C was identified in the summer and fall seasons, respectively, between 15:30 and 16:20. The maximum LST was observed in RHC, and PA showed the minimum LST in both seasons. Notably, dark-coloured roofs with asphalt shingle coating reported up to 25.78◦C and 27.37◦C higher LST (UAV-estimated) than light-coloured roofs in the fall and summer, respectively. Landsat significantly underestimated MUHI hotspots in the summer and fall seasons. The on-ground validation of the UAV showed better results in the summer season. The study shows the pragmatic use of UAVs to detect localized MUHIs. The findings are useful to devise strategies to mitigate MUHIs utilizing UAVs in the face of climatic and environmental changes. |
Persistent Identifier | http://hdl.handle.net/10722/349217 |
ISSN | 2023 Impact Factor: 3.0 2023 SCImago Journal Rankings: 0.776 |
DC Field | Value | Language |
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dc.contributor.author | Ahmad, Junaid | - |
dc.contributor.author | Sajjad, Muhammad | - |
dc.contributor.author | Eisma, Jessica | - |
dc.date.accessioned | 2024-10-17T06:57:03Z | - |
dc.date.available | 2024-10-17T06:57:03Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | International Journal of Remote Sensing, 2024 | - |
dc.identifier.issn | 0143-1161 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349217 | - |
dc.description.abstract | Metropolitan areas have diverse land uses (LUs), which can also cause significant differences in land surface temperature (LST), leading to the formation of micro-urban heat islands (MUHIs). Measuring the MUHIs is significant for heat mitiga-tion and adaptation measures and requires high spatial-temporal resolution, which is not feasible through coarser satellite observations (CSOs). Thermal cameras onboard unmanned aerial vehicles (UAVs) can detect such MUHIs because of their high spatial and desired temporal resolution. This study used the Zenmuse H20T onboard a UAV providing LST at ∼8 cm resolution to evaluate MUHIs in an area with diverse and contiguous LUs including three urban built-up LUs: 1) residential high cost (RHC), 2) residential low cost (RLC), 3) industrial area (IA) and one natural area (i.e. park area (PA)). The LST and MUHI were estimated in two seasons: fall (October 2022) and summer (June-July 2023). In each season, six flights were conducted at similar times of day. The findings were compared with Landsat in each season to examine the loss of information between coarser and finer spatial resolution. Using UAV, a maximum MUHI of 25.54◦C and 15.85◦C was identified in the summer and fall seasons, respectively, between 15:30 and 16:20. The maximum LST was observed in RHC, and PA showed the minimum LST in both seasons. Notably, dark-coloured roofs with asphalt shingle coating reported up to 25.78◦C and 27.37◦C higher LST (UAV-estimated) than light-coloured roofs in the fall and summer, respectively. Landsat significantly underestimated MUHI hotspots in the summer and fall seasons. The on-ground validation of the UAV showed better results in the summer season. The study shows the pragmatic use of UAVs to detect localized MUHIs. The findings are useful to devise strategies to mitigate MUHIs utilizing UAVs in the face of climatic and environmental changes. | - |
dc.language | eng | - |
dc.relation.ispartof | International Journal of Remote Sensing | - |
dc.subject | drones | - |
dc.subject | extreme temperature | - |
dc.subject | remote sensing | - |
dc.subject | urban heat island | - |
dc.subject | Urbanization | - |
dc.title | Small unmanned aerial vehicle (UAV)-based detection of seasonal micro-urban heat islands for diverse land uses | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/01431161.2024.2391582 | - |
dc.identifier.scopus | eid_2-s2.0-85202540101 | - |
dc.identifier.eissn | 1366-5901 | - |