The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for co...The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for comprehending the intricate interactions among urbanization,climate dynamics,and human well-being.However,many aspects of these topics remain understudied.In this study,we conducted a comprehensive analysis of LST and TAIR,covering day and night and spanning all four seasons of a full year.We used global datasets and applied non-spatial and spatial analysis techniques in the Amman-Zarqa urban region,a typical arid to semiarid environment.The study had three primary objectives:(1)Assess how different human settlement types influence the variations in LST and TAIR across space and time.(2)Examine the spatial and temporal attributes of the relationships between TAIR and LST.(3)Synthesize insights regarding the spatial and temporal characteristics of urban heat islands in arid to semiarid environments.The findings unveiled that urban centers consistently exhibit the lowest daytime LST and maximum and minimum TAIR,across all seasons when compared to other human settlement types.Nighttime LST displayed more variable patterns.Urban centers act as surface urban cool islands during the day and canopy layer urban cool islands both day and night throughout the seasons.The presence of surface urban heat or cool islands at night is barely noticeable.Daytime and nighttime LST play a significant role in explaining the variability in maximum and minimum TAIR across all seasons,with the relationships exhibiting variations ranging from positive to non-significant to negative,influenced by location and seasonal changes.During the daytime,LST consistently exceeds TAIR across all seasons,whereas this relationship displays greater variability at night.The findings of this study hold significant implications for sustainable urban planning and efforts to combat the effects of urban heat islands.展开更多
Change detection of land-cover to recommend the future directions of land-use is indispensable for sustainable development and the proper utilization of land resources. In this research, unsupervised classification ma...Change detection of land-cover to recommend the future directions of land-use is indispensable for sustainable development and the proper utilization of land resources. In this research, unsupervised classification maps produced using images of Landsat 8 OLI from 2013 until 2021 (with a 4-year interval) reveal important land-cover changes, along with their drivers, in Kapasia, Bangladesh. Overall, a substantial increase in paddy (24.7% to 27.2%) and urban (3.5% to 10.1%) and a decrease in homestead (67.5% to 59.3%) and forest (4.2% to 3.4%) were observed within the time interval. To direct the land-use towards long-term biodiversity and sustainability of the region, it is important to implement types of agroforestry systems as the observed decrease in homestead and forest areas are alarming. Agroforestry practices will not only have a positive environmental impact but can help diversify food systems, increase economic return and optimize natural resource use.展开更多
Catastrophic natural disasters like earthquakes can cause infrastructure damage.Emer-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and t...Catastrophic natural disasters like earthquakes can cause infrastructure damage.Emer-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and types.The authors aim for an autonomous Unmanned Aerial Vehicle(UAV)platform equipped with a 3D LiDAR sensor to comprehensively and accurately scan the infrastructure and map it with a predefined resolution r.During the inspection,the UAV needs to decide on the Next Best View(NBV)position to maximize the gathered information while avoiding collision at high speed.The authors propose solving this problem by implementing a hierarchical closed‐loop control system consisting of a global planner and a local planner.The global NBV planner decides the general UAV direction based on a history of measurements from the LiDAR sensor,and the local planner considers the UAV dynamics and enables the UAV to fly at high speed with the latest LiDAR measurements.The proposed system is vali-dated through the Regional Scale Autonomous Swarm Damage Assessment simulator,which is built by the authors.Through extensive testing in three unique and highly constrained infrastructure environments,the autonomous UAV inspection system suc-cessfully explored and mapped the infrastructures,demonstrating its versatility and applicability across various shapes of infrastructure.展开更多
基金funded by Natural Sciences and Engineering Research Council of Canada(NSERC)[RGPIN-2022-04342].
文摘The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for comprehending the intricate interactions among urbanization,climate dynamics,and human well-being.However,many aspects of these topics remain understudied.In this study,we conducted a comprehensive analysis of LST and TAIR,covering day and night and spanning all four seasons of a full year.We used global datasets and applied non-spatial and spatial analysis techniques in the Amman-Zarqa urban region,a typical arid to semiarid environment.The study had three primary objectives:(1)Assess how different human settlement types influence the variations in LST and TAIR across space and time.(2)Examine the spatial and temporal attributes of the relationships between TAIR and LST.(3)Synthesize insights regarding the spatial and temporal characteristics of urban heat islands in arid to semiarid environments.The findings unveiled that urban centers consistently exhibit the lowest daytime LST and maximum and minimum TAIR,across all seasons when compared to other human settlement types.Nighttime LST displayed more variable patterns.Urban centers act as surface urban cool islands during the day and canopy layer urban cool islands both day and night throughout the seasons.The presence of surface urban heat or cool islands at night is barely noticeable.Daytime and nighttime LST play a significant role in explaining the variability in maximum and minimum TAIR across all seasons,with the relationships exhibiting variations ranging from positive to non-significant to negative,influenced by location and seasonal changes.During the daytime,LST consistently exceeds TAIR across all seasons,whereas this relationship displays greater variability at night.The findings of this study hold significant implications for sustainable urban planning and efforts to combat the effects of urban heat islands.
文摘Change detection of land-cover to recommend the future directions of land-use is indispensable for sustainable development and the proper utilization of land resources. In this research, unsupervised classification maps produced using images of Landsat 8 OLI from 2013 until 2021 (with a 4-year interval) reveal important land-cover changes, along with their drivers, in Kapasia, Bangladesh. Overall, a substantial increase in paddy (24.7% to 27.2%) and urban (3.5% to 10.1%) and a decrease in homestead (67.5% to 59.3%) and forest (4.2% to 3.4%) were observed within the time interval. To direct the land-use towards long-term biodiversity and sustainability of the region, it is important to implement types of agroforestry systems as the observed decrease in homestead and forest areas are alarming. Agroforestry practices will not only have a positive environmental impact but can help diversify food systems, increase economic return and optimize natural resource use.
文摘Catastrophic natural disasters like earthquakes can cause infrastructure damage.Emer-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and types.The authors aim for an autonomous Unmanned Aerial Vehicle(UAV)platform equipped with a 3D LiDAR sensor to comprehensively and accurately scan the infrastructure and map it with a predefined resolution r.During the inspection,the UAV needs to decide on the Next Best View(NBV)position to maximize the gathered information while avoiding collision at high speed.The authors propose solving this problem by implementing a hierarchical closed‐loop control system consisting of a global planner and a local planner.The global NBV planner decides the general UAV direction based on a history of measurements from the LiDAR sensor,and the local planner considers the UAV dynamics and enables the UAV to fly at high speed with the latest LiDAR measurements.The proposed system is vali-dated through the Regional Scale Autonomous Swarm Damage Assessment simulator,which is built by the authors.Through extensive testing in three unique and highly constrained infrastructure environments,the autonomous UAV inspection system suc-cessfully explored and mapped the infrastructures,demonstrating its versatility and applicability across various shapes of infrastructure.
