Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively ...Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.展开更多
The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature(LST).Currently,most studies mainly examine the effects of two-dimensional(2D...The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature(LST).Currently,most studies mainly examine the effects of two-dimensional(2D)landscape patterns on LST variations,and research investigating the relationship between three-dimensional(3D)urban landscape patterns and LST remains relatively scarce.Therefore,this study utilizes partial correlation analysis and piecewise linear regression to systematically investigate the impacts of gray landscape indicators on LST variations under both 2D and 3D urban patterns,aiming to elucidate the complex relationship between 3D urban landscape patterns and LST dynamics.The results demonstrate that specific 3D building characteristics,particularly the area of low-rise buildings,building aggregation degree,shape complexity,and patch density of mid-rise buildings,serve as effective indicators of urban thermal environment risk.The analysis reveals that increased area-related indicators for low-rise buildings significantly exacerbate the LST rise,whereas modifications to the landscape shape of middle and high-rise buildings contribute to thermal mitigation.Additionally,when gray landscape aggregation exceeds 80%,the spatial concentration of mid-rise buildings exhibits a pronounced positive effect on moderating urban LST.These findings elucidate the mechanisms through which 3D landscape patterns influence urban thermal risks in Beijing,advancing the understanding of urban landscape-ecological processes interactions and providing crucial scientific support for landscape optimization and urban thermal environment risk mitigation strategies.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Shanxi Province Graduate Research Practice Innovation Project,No.2023KY465Project on the Reform of Graduate Education and Teaching in Shanxi Province,No.2021YJJG146+1 种基金Research Project of Shanxi Provincial Cultural Relics Bureau,No.22-8-14-1400-119National Key R&D Program of China,No.2021YFB3901300。
文摘Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.
基金supported by the National Key Research and Development Program of China[grant number 2024YFF1306200]the National Natural Science Foundation of China[grant number 42171318].
文摘The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature(LST).Currently,most studies mainly examine the effects of two-dimensional(2D)landscape patterns on LST variations,and research investigating the relationship between three-dimensional(3D)urban landscape patterns and LST remains relatively scarce.Therefore,this study utilizes partial correlation analysis and piecewise linear regression to systematically investigate the impacts of gray landscape indicators on LST variations under both 2D and 3D urban patterns,aiming to elucidate the complex relationship between 3D urban landscape patterns and LST dynamics.The results demonstrate that specific 3D building characteristics,particularly the area of low-rise buildings,building aggregation degree,shape complexity,and patch density of mid-rise buildings,serve as effective indicators of urban thermal environment risk.The analysis reveals that increased area-related indicators for low-rise buildings significantly exacerbate the LST rise,whereas modifications to the landscape shape of middle and high-rise buildings contribute to thermal mitigation.Additionally,when gray landscape aggregation exceeds 80%,the spatial concentration of mid-rise buildings exhibits a pronounced positive effect on moderating urban LST.These findings elucidate the mechanisms through which 3D landscape patterns influence urban thermal risks in Beijing,advancing the understanding of urban landscape-ecological processes interactions and providing crucial scientific support for landscape optimization and urban thermal environment risk mitigation strategies.
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。
