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喀斯特城市地表水热通量的时空变化研究
引用本文:王修信,汤谷云,罗涟玲,孙涛,朱启疆.喀斯特城市地表水热通量的时空变化研究[J].生态学报,2020,40(11):3579-3589.
作者姓名:王修信  汤谷云  罗涟玲  孙涛  朱启疆
作者单位:广西师范大学计算机科学与信息工程学院, 桂林 541004;广西师范大学广西多源信息挖掘与安全重点实验室, 桂林 541004;北京师范大学遥感科学国家重点实验室, 北京 100875;广西师范大学生命科学学院, 桂林 541004
基金项目:国家自然科学基金项目(41561008);广西自然科学基金项目(2014GXNSFAA118289)
摘    要:针对我国西南地区桂林喀斯特城市近20多年来快速扩展所引发的热环境问题,改进METRIC模型使其适用于喀斯特城市实际状况,利用模型和1994—2015年5景Landsat遥感图像反演地表水热通量,分析通量时空变化规律。结果表明,潜热通量从高到低依次为水体、喀斯特山峰阳坡植被、地面植被、喀斯特山峰阴坡植被、建筑/道路和裸土、喀斯特山峰裸岩,显热通量从高到低依次为喀斯特山峰裸岩和建筑/道路、裸土、喀斯特山峰阳坡植被、地面植被、喀斯特山峰阴坡植被、水体。水热通量随时间的变化受地表覆盖变化的影响,研究区波文比(显热通量与潜热通量比值)在1994年最高,达到1.62,2000年下降到1.24,之后逐渐升高至2015年的1.51。城市扩展过程出现的显热高值区和潜热低值区比例低于10%,其变化引发显热中低值区和潜热中高值区比例的变化,显热高值区最高比例在1994年(10.0%),2000年下降到5.4%,之后至2010年逐渐上升到9.4%,但2015年下降到7.1%,潜热低值区比例的变化趋势与显热高值区比例基本相同。植被覆盖度(Vegetation fraction,Pv)在0.1—0.8范围时对水热通量的影响相对更显著,Pv增加0.1,显热通量降低8—27 W/m~2,而潜热通量升高8—24 W/m~2。喀斯特山峰植被保护和城区地面绿化建设对喀斯特城市热环境的改善至关重要。

关 键 词:喀斯特城市  水热通量  METRIC模型  时空变化  植被覆盖变化
收稿时间:2019/2/19 0:00:00
修稿时间:2020/1/18 0:00:00

Spatio-temporal variation of land surface water and heat fluxes over karst city
WANG Xiuxin,TANG Guyun,LUO Lianling,SUN Tao,ZHU Qijiang.Spatio-temporal variation of land surface water and heat fluxes over karst city[J].Acta Ecologica Sinica,2020,40(11):3579-3589.
Authors:WANG Xiuxin  TANG Guyun  LUO Lianling  SUN Tao  ZHU Qijiang
Institution:College of Computer Science and Information Technology, Guangxi Normal University, Guilin 541004, China;Guangxi Key Laboratory of Multi-source Information Mining & Security, Guangxi Normal University, Guilin 541004, China;State key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China;College of life Science, Guangxi Normal University, Guilin 541004, China
Abstract:In order to study thermally environmental problems caused by rapid expansion of Guilin city in Southwest China karst area in the last 20 years, the METRIC model was improved for suitability of the actual situation in karst cities. Then land surface water and heat fluxes were retrieved with the improved METRIC model from five Landsat images from1994 to 2015. Finally, the spatio-temporal variations of the fluxes were analyzed. The results showed that the land cover types with the values of latent heat flux from the highest to the lowest were water body, vegetation on the sunny slopes of karst hills, ground vegetation, vegetation on the shady slopes of karst hills, buildings and roads, bare soil, and bare rock on karst hills. In contrast, the land cover types with the values of sensible heat flux from the highest to the lowest were bare rock on karst hills, buildings and roads, bare soil, vegetation on the sunny slopes of karst hills, ground vegetation, vegetation on the shady slopes of karst hills, and water body. The temporal variations of land surface water and heat fluxes were influenced by the changes of land covers. The ratio of sensible heat flux to latent heat flux, defined as Bowen ratio, was 1.62 in 1994 as the highest, down to 1.24 in 2000, and gradually rising to 1.51 in 2015. The area proportions of the high sensible heat flux and the low latent heat flux resulted from urban expansion were less than 10.0%. The above area proportion changes resulted in the changes of the area proportions of the middle, low sensible heat flux and middle, and high latent heat flux. The area proportion of the high sensible heat flux was with the highest 10.0% in 1994, went down to 5.4% in 2000, and gradually rised to 9.4% in 2010. But it dropped to 7.1% in 2015. The variation trend of the area proportions of the low latent heat flux is essentially the same with that of the high sensible heat flux. While vegetation fraction ranges between 0.1 and 0.8, it affected the fluxes very obviously. The value of sensible heat flux decreased 8-27 W/m2 and the value of latent heat flux increased 8-24 W/m2 with the 0.1 rise of vegetation fraction. Vegetation protection on karst hills and ground greening construction are crucial in improving urban heat environment in karst cities.
Keywords:karst city  water and heat fluxes  METRIC model  spatio-temporal variation  vegetation cover change
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