景观格局影响下的南京市热舒适度动态变化
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摘要
城市热舒适度的评价是判断热环境优劣的主要方式,其结果可为城市规划、改善城市热环境提供科学依据,而温湿指数(THI)综合反映了温度和湿度两个因子对人体热感的影响,是衡量城市热舒适度的一项重要指标。选取江苏省南京市作为研究区,以1994、2000、2010和2013年夏季Landsat遥感影像数据和土地利用现状数据为数据源,反演地表温度,并结合归一化水汽指数(NDMI)对传统温湿指数进行改进,在此基础上分别从宏观和微观两个层面分析了南京市热舒适度的动态变化,通过计算景观格局指数,分析不同热舒适度分级下景观格局指数的变化,统计了2.5 km尺度上单元格网温湿指数平均值及变异系数并对其与景观组成和结构特征的相关性进行了研究,从微观尺度上探讨城市景观格局与城市热舒适度之间的关系。结果表明:宏观上,从1994年到2013年景观格局对南京市热舒适度的影响不断加深,影响面积和强度都不断增大,城市热环境逐渐恶化;微观上,景观类型组成和结构对城市热舒适度有不同程度的影响,水体、耕地、林地能显著改善热舒适度,其中水体对热舒适度的改善效果最好,其景观优势度越大、分布越集中,效果越明显;反之,建设用地优势度越大、聚集度越高,热舒适度越差。
Evaluation of urban thermal comfort is the important means of assessing the quality of thermal environment for cities,as well as provides the scientific basis for improving urban thermal environment. The temperature-humidity index( THI) is an important indicator of thermal comfort indexes. In this paper,taking Nanjing City,capital of Jiangsu Province as the study area,we analyzed the impacts of landscape patterns on the dynamics change of thermal comfort. Four Landsat images of 1994,2000,2010 and 2013 were used to retrieve the land surface temperature( LST) and normalized moisture Index( NDMI). And the modified THI( MTHI) of Nanjing was calculated through LST and NDMI. The paper investigated the dynamic changes of thermal comfort in Nanjing City from the macro and micro scales during 1994 to 2013. Landscape metrics were calculated to explore the changes of various landscape patterns based on the different thermal comfort levels. The correlation between MTHI in virtue of 2. 5 km fishnet and the composition and structure of the urban landscape was quantified,which can clarify the relationship between urban thermal comfort and urban landscape patterns on microscale. The results showed that the impacts of landscape patterns on thermal comfort in Nanjing has been increasing from 1994 to 2013 from the macro perspective,which was getting worse. The compositions and structures of different landscapes exert different impacts on urban thermal comfort from the micro perspective,among which cropland,forest,especially water can relieve the urban thermal comfort. The more proportion and greater concentration of cropland,forest and water body,the better they can improve the urban thermal comfort. Conversely the thermal comfort got worse when there were more aggregative built-up areas.
Evaluation of urban thermal comfort is the important means of assessing the quality of thermal environment for cities,as well as provides the scientific basis for improving urban thermal environment. The temperature-humidity index( THI) is an important indicator of thermal comfort indexes. In this paper,taking Nanjing City,capital of Jiangsu Province as the study area,we analyzed the impacts of landscape patterns on the dynamics change of thermal comfort. Four Landsat images of 1994,2000,2010 and 2013 were used to retrieve the land surface temperature( LST) and normalized moisture Index( NDMI). And the modified THI( MTHI) of Nanjing was calculated through LST and NDMI. The paper investigated the dynamic changes of thermal comfort in Nanjing City from the macro and micro scales during 1994 to 2013. Landscape metrics were calculated to explore the changes of various landscape patterns based on the different thermal comfort levels. The correlation between MTHI in virtue of 2. 5 km fishnet and the composition and structure of the urban landscape was quantified,which can clarify the relationship between urban thermal comfort and urban landscape patterns on microscale. The results showed that the impacts of landscape patterns on thermal comfort in Nanjing has been increasing from 1994 to 2013 from the macro perspective,which was getting worse. The compositions and structures of different landscapes exert different impacts on urban thermal comfort from the micro perspective,among which cropland,forest,especially water can relieve the urban thermal comfort. The more proportion and greater concentration of cropland,forest and water body,the better they can improve the urban thermal comfort. Conversely the thermal comfort got worse when there were more aggregative built-up areas.
引文
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[2]吴志丰,陈利顶.热舒适度评价与城市热环境研究:现状、特点与展望[J].生态学杂志,2016,35(5):1364-1371.WU Z F,CHEN L D.Thermal comfort assessment and urban thermal environment research:review and prospective[J].Chinese Journal of Ecology,2016,35(5):1364-1371.
[3]HOUGHTON F C,YAGLOU C P.Determining equal comfort lines[J].Journal of the American Society of Heating and Ventilating Engineers,1923,29:165-176.
[4]YAGLOU C P,MINARD D.Control of heat casualties at military training centers[J].American Medical Association Archives of Industrial Health,1957,16:302-316.
[5]THOM E C.The discomfort index[J].Weatherwise,1959,12(12):57-61.
[6]FANGER P O.Thermal comfort.analysis and applications in environmental engineering.copenhagen[J].Danish Technical Press,1970.
[7]HPPE P.The physiological equivalent temperature-a universal index for the biometeorological assessment of the thermal environment[J].International Journal of Biometeorology,1999,43,71-75.
[8]王远飞,沈愈.上海市夏季温湿效应与人体舒适度[J].华东师范大学学报(自然科学版),1998(3):60-66.WANG Y F,SHEN Y.The temperature-humidity effect and human comfort in Shanghai summer[J].Journal of East China Normal University(Nature Science),1998(3):60-66.
[9]曹伟华,扈海波.北京城市高温舒适度的空间变化分析[C]//中国环境科学学会学术年会论文集(第七卷).北京:中国环境科学学会,2013:6283-6288.
[10]刘贝.基于GIS的中部六省旅游气候舒适度研究[D].华中师范大学硕士学位论文,2016.LIU B.The research of tourism climate comfort degree of six provinces in central China based on Geographic Information System[D].Master Thesis of Central China Normal University,2016.
[11]覃志豪,ZHANG MINGHUA,ARNON KARNIELI,等.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.QIN Z H,ZHANG M H,ARNON K,et al.Mono-window Algorithm for retrieving land surface temperature from Landsat TM6 data[J].Acta Geographica Sinica,2001,56(4):456-466.
[12]覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004,16(3):28-32.QIN Z H,LI W J,XU B,et al.The estimation of land surface emissivity for Landsat TM6[J].Remote Sensing for Land&Resources,2004,16(3):28-32.
[13]江樟焰,陈云浩,李京.基于Landsat TM数据的北京城市热岛研究[J].武汉大学学报(信息科学版),2006,31(2):120-123.JIANG Z Y,CHEN Y H,LI J.Heat island effect of Beijing based on Landsat TM data[J].Geomatics and Information Science of Wuhan University,2006,31(2):120-123.
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[15]张伟,蒋锦刚,朱玉碧.基于空间统计特征的城市热环境时空演化[J].应用生态学报,2015,26(6):1840-1846.ZHANG W,JIANG J G,ZHU Y B.Spatial-temporal evolution of urban thermal environment based on spatial statistical features[J].Chinese Journal of Applied Ecology,2015,26(6):1840-1846.
[16]向梅.空气湿度对人体热舒适影响的实验研究[D].重庆大学硕士学位论文,2013.XIANG M.Effect of air humidity on human thermal comfort[D].Master Thesis of Chongqing University,2013.
[17]薛俊杰.徽州传统聚落夏季户外热舒适度的实测分析[D].安徽建筑大学硕士学位论文,2015.XUE J J.Measurement and analysis on summer outdoor thermal comfort degree of Huizhou traditional settlements[D].Master Thesis of Anhui Jianzhu University,2015.
[18]HUNT JR E R,ROCK B N,NOBEL P S.Measurement of leaf relative water content by infrared reflectance[J].Remote Sensing of Environment,1987,22(3):429-435.
[19]HARDISKY M A,KLEMAS V,SMART R M.The influence of soil salinity,growth form,and leaf moisture on the spectral radiance of spartina alterniflora canopies[J].Photogrammetric Engineering&Remote Sensing,1983,49(1):77-84.
[20]李仕峰,钱乐祥,王瑾.基于陆地卫星TM/ETM+改进的温湿指数及其对不透水表面的响应[J].地理与地理信息科学,2013,29(2):112-115.LI S F,QIAN L X,WANG J.Improved Temperature-humidity index based on landsat TM/ETM+and its response to impervious surface[J].Geography and Geo-Information Science,2013,29(2):112-115.
[21]钱乐祥,崔海山.归一化水汽指数与地表温度的关系[J].地理研究,2008,27(6):1358-1366.QIAN L X,CUI H S.Relationship between normalized difference moisture index and land surface temperature[J].Geographical Research,2008,27(6):1358-1366.
[22]TURNER M G.landscape ecology:what is the state of the science?[J].Annual Review of Ecology Evolution&Systematics,2005,36(36):319-344.
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