With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for p...With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making.In this study,Shenyang was selected to comprehensively analyse multiple factors,including topography,human activity,vegetation and landscape.Moreover,we used the random forest algorithm to explore nonlinear factors influencing land surface temperature(LST)over four years in the study area.The results revealed that from 2005 to 2020,the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased.The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020.Additionally,significant and strong correlations were observed between LST and variables such as the enhanced vegetation index(EVI),normalised difference vegetation index(NDVI),population density,proportion of cropland and proportion of impervious land.In 2010,proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale,reaching 0.852(p<0.01).The 4 km grid scale was identified as the optimal grid size for this study,while the 2 km grid performed the worst.In 2020,NDVI emerged as the most significant factor influencing LST.These findings provide valuable guidance for improving urban planning and developing sustainable strategies.展开更多
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
本文通过对南京地区1984—2003年20 a 110个降水结冰样本当日温度的统计分析,讨论了南京地区结冰时间变化和各影响温度的变化规律,总结了对结冰预报具有指示意义的关键因子;同时利用支持向量机方法探讨了南京地区结冰预报方法,该方法具...本文通过对南京地区1984—2003年20 a 110个降水结冰样本当日温度的统计分析,讨论了南京地区结冰时间变化和各影响温度的变化规律,总结了对结冰预报具有指示意义的关键因子;同时利用支持向量机方法探讨了南京地区结冰预报方法,该方法具有显著的预报价值。在此基础上根据Norrman提出的路面打滑分类,结合南京地区具体情况得出了南京雨雪天气路面结冰的类别、标准和预测预报方法。展开更多
基金National Natural Science Foundation of China,No.42204031。
文摘With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making.In this study,Shenyang was selected to comprehensively analyse multiple factors,including topography,human activity,vegetation and landscape.Moreover,we used the random forest algorithm to explore nonlinear factors influencing land surface temperature(LST)over four years in the study area.The results revealed that from 2005 to 2020,the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased.The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020.Additionally,significant and strong correlations were observed between LST and variables such as the enhanced vegetation index(EVI),normalised difference vegetation index(NDVI),population density,proportion of cropland and proportion of impervious land.In 2010,proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale,reaching 0.852(p<0.01).The 4 km grid scale was identified as the optimal grid size for this study,while the 2 km grid performed the worst.In 2020,NDVI emerged as the most significant factor influencing LST.These findings provide valuable guidance for improving urban planning and developing sustainable strategies.
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.
文摘本文通过对南京地区1984—2003年20 a 110个降水结冰样本当日温度的统计分析,讨论了南京地区结冰时间变化和各影响温度的变化规律,总结了对结冰预报具有指示意义的关键因子;同时利用支持向量机方法探讨了南京地区结冰预报方法,该方法具有显著的预报价值。在此基础上根据Norrman提出的路面打滑分类,结合南京地区具体情况得出了南京雨雪天气路面结冰的类别、标准和预测预报方法。
