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基于GEE的长江经济带城市群热岛特征及影响因素 被引量:5

Heat island characteristics and influencing factors of urban agglomerations in the Yangtze River Economic Zone based on GEE
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摘要 遥感技术能够客观、定量地评价地表城市热岛强度的时空变化,分析城市热岛的影响因素,为城市生态建设提供有效的科学参考。本研究基于GEE(Google Earth Engine)平台,以长时间序列的MODIS卫星资料为基础数据源,使用城乡二分法估算长江经济带2003—2019年的城市地表热岛强度,再利用城市热场变异指数评价生态环境,并利用地理探测器进行城市热岛成因分析。结果表明:长江经济带5个城市群2003—2019年全年平均气温为22.78℃,白天为23.91℃,夜间为7.59℃,平均温度整体上均呈上升趋势,分别为0.02、0.02和0.006℃·a^(-1)。长江经济带5个城市群17年无热岛占比最高,弱热岛和弱冷岛占比次之,强热岛占比最少,且城市热岛全年、白天和夜间都呈现下降趋势。长江经济带整体的生态评价为优。地理探测器因子探测表明,DEM、土地覆盖类型、O3是长三角城市群热岛效应的主控因子;蒸散发量、紫外线气溶胶吸收指数、人口密度是长江中游城市群热岛效应的主控因子;归一化植被指数、夜间灯光指数、土地覆盖类型是成渝城市群热岛效应的主控因子;归一化植被指数、DEM、CO是黔中城市群热岛效应的主控因子;蒸散发量、O3、NDVI是滇中城市群热岛效应的主控因子。 Remote sensing technology can objectively and quantitatively evaluate the spatial and temporal variations of surface urban heat island intensity.Analyzing the influencing factors of urban heat islands could provide effective scientific references for urban ecological construction.Based on the GEE(Google Earth Engine)platform,we estimated the surface urban heat island intensity in the Yangtze River Economic Zone from 2003 to 2019 using long time series of MODIS satellite data.We evaluated the ecological environment using urban thermal field variance index,and analyzed the causes of urban heat islands using geographical detectors.The results showed that mean annual temperature of the five urban agglomerations in the Yangtze River Economic Zone during 2003-2019 was 22.78℃,with 23.91℃on daytime,7.59℃at nighttime,and an overall increasing trend of 0.02,0.02 and 0.006℃·a^(-1),respectively.The five urban agglomerations in the Yangtze River Economic Belt had the highest proportion of heat island free during 2003-2019,followed by weak heat islands and weak cold islands,and the lowest proportion of strong heat islands.The urban heat island effect showed a decreasing trend throughout the year,during the day,and at night.The overall environmental quality of the Yangtze River Economic Zone was excellent.Geographic detector for factor detection showed that DEM,land-cover type,and O3were the main drivers for surface urban heat island effect in the Yangtze River Delta urban agglomeration.Evapotranspiration,ultraviolet aerosol index,and population density were the main controlling factors of surface urban heat island effect in the middle reaches of the Yangtze River urban agglomeration.Normalized difference vegetation index,nighttime light index,and land-cover type were the main controlling factors for surface urban heat island effect in the Chengdu-Chongqing urban agglomeration.Normalized difference vegetation index,DEM,and CO were the main controlling factors of surface urban heat island effect in the central Guizhou urban agglomeration.Evapotranspiration,O3and normalized difference vegetation index were the main controlling factors of surface urban heat island effect in the central Yunnan urban agglomeration.
作者 阴瑜鑫 张华 安慧敏 雷金萍 李明 宋金岳 韩武宏 YIN Yu-xin;ZHANG Hua;AN Hui-min;LEI Jin-ping;LI Ming;SONG Jin-yue;HAN Wu-hong(Northwest Normal University,School of Geography and Environmental Sciences,Lanzhou 730070,China;Key Laboratory of Resource Environment and Sustainable Development of Oasis,Gansu Province,Lanzhou 730070,China)
出处 《生态学杂志》 CAS CSCD 北大核心 2023年第1期160-169,共10页 Chinese Journal of Ecology
基金 国家自然科学基金项目(41461011) 兰州市人才创新创业项目(2019-RC-105)资助。
关键词 Google Earth Engine 地表城市热岛强度 城市热场变异指数 地理探测器 Google Earth Engine surface urban heat island intensity urban thermal field variance index geographic detector
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