用户名: 密码: 验证码:
城市热岛效应演变与成因遥感研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
持续快速的城市化对城市局地气候、生态环境和生态安全产生了持久而深远的影响,随着地表覆被类型的急剧变化、地表物化性质的改变使得地表与大气间的水分与能量物质交换过程发生变化,进而影响到城市“热”环境系统。并由城市“热”引发的一系列环境、生态安全等问题已经成为制约城市可持续发展的瓶颈。为此,2005年国务院发布的《国家中长期科学和技术发展规划纲要(2006-2020)》中明确要求,为提升城市功能与空间节约利用,要把城市“热岛”效应的形成机制与入工调控技术作为重点研究内容。其强调了城市热环境研究对构建新型现代化都市的重要性,并将此作为构建城市可持续发展的必经之路。
     本文以西安都市圈为例,以1988~2009年21年间的陆地卫星(Landsat) TM/ETM+数据为主要信息源,以气象站点资料和土地利用图件为辅助,以遥感定量反演和GIS空间分析为技术支撑,对不同年份的西安都市圈地表温度和不同时相的西安市地表温度状况进行分析与评价;并引入景观生态学理论,利用景观格局指数对西安都市圈典型城镇(西安市、咸阳市和兴平市)热环境格局动态变化进行分析与评价;同时,采用分形理论,探讨了西安市地表温度的时空分形特征与尺度效应特征;基于研究区下垫面类型的变化与地表温度间的定量关系,以西安市主要公园为例探讨了公园下垫面类型对周边地区温度的定量影响,在此基础上,运用元胞自动机理论和马尔可夫模型,构建了可用于城市热环境模拟的UHI-CA-Markov模拟与预测模型;在定性分析城市热岛效应影响因素的基础上,基于多元目标的主成分分析的方法,定量探讨了各影响因子对城市热岛效应的贡献率大小,并从调整城市规划思路、控制工业热源、调控民用热源等三个方面构建了应对西安都市圈典型城镇热岛效应的调控体系和措施。
     研究过程中,主要得出以下重要结论:
     (1)西安都市圈典型城镇均存在不同程度的热岛效应
     ①基于等距的热岛类型划分体系适用于大中城镇构建热环境指标与评价体系;而基于中误差的划分体系更适合于构建市、县、镇、乡四级热环境指标及评价体系;②西安市、咸阳市和兴平市热环境结构中常温区均占主导地位。西安市和咸阳市不同热岛类型面积大小依次为:常温区>绿岛区>热岛区>强热岛区>强绿岛区;而兴平市不同热岛类型面积大小依次为:常温区>热岛区>绿岛区>强热岛区>强绿岛区;③西安市不同年份不同时间城郊地表温度差异较大。
     (2)西安都市圈典型城镇热景观格局时空差异较大
     ①类型景观水平指数显示,1988~2006年18年间常温区始终是西安市、咸阳市和兴平市域内的优势斑块;②蔓延度指数表明:西安市、咸阳市和兴平市整个景观要素先趋于密集化,破碎度增加,呈现无序化趋势;之后,破碎度降低,斑块分布趋于稳定;③多样性指数和均匀度指数的变化趋势表明:西安市、咸阳市和兴平市土地利用方式随着时间推移均趋于稳定,破碎度降低,热景观格局亦趋于稳定;④不同粒度下,地表温度剖面线表现为相似的结构特征,但当尺度达到150m的时候,会发生跳跃现象。
     (3)西安市地表温度与下垫面覆盖(利用)类型的定量关系表达
     ①夏季西安市不同地表覆盖(利用)类型中,其平均地表温度由高到低的次序为:裸露地>建设用地>耕地>草地>林地>水体;冬季西安市不同地表覆盖(利用)类型的平均地表温度由高到低依次为:林地>耕地>裸露地>建设用地>草地>水体;②夏季西安市地表温度(LST)与归一化植被指数(NDVI)呈现显著的负相关关系;LST与归一化裸露指数(NDBI)呈现正相关关系;LST与水体指数(NDWI)呈现典型的负相关关系,表明夏季水体具有很好的降温作用;③不同形态参数(面积、长宽比、形状指数等)的公园对其周边区域的热环境影响不同。公园面积是其平均温度高低的决定性因素;公园平均降温范围与公园长宽比和形状指数呈现较强的正相关关系,降温幅度与水域面积、长宽比和形状指数呈较低程度的正相关;水体面积比例较高(≥30%)的兴庆公园、大唐鞭蓉园,其平均降温影响范围Lmax以及△Tmax整体略高于其它公园。因此,城市公园建设中建议水体面积占公园面积30%以上为佳。
     (4)西安市热环境模拟结果显示未来城市热趋于好转
     ①基于UHI-CA-Markov模型的空间模拟结果显示,预计到2012年西安市热环境相比2006年表现为:强热岛区和热岛区均呈现小幅减少的趋势,常温区、绿岛区呈现略微增加的趋势,强绿岛区呈现稳定的趋势;②到2018年,西安市热环境类型与2012年相比,预计强热岛区呈现小幅增加的趋势,热岛区呈现持平的趋势,常温区出现较大幅度的增加,绿岛区和强绿岛区均呈现不同程度的减少;③2006~2018年12年间模拟结果表明:未来西安市热环境状况整体趋于良好,常温区占绝对优势,但局部地区热环境有进一步恶化的趋势。因此,建议城市规划建设中居民热环境规划作为一项重要内容予以考虑。
     (5)西安都市圈热岛成因与对策分析
     ①从有利于增加城市热岛(Urban Heat Island, UHI)的因素被加强、有利于缓解UHI的因素被减弱、临时性和持久性影响因素共4个方面构建了“热岛”影响因素体系,并将4个方面内容进一步细分为11个一级类型,20个二级类型;②PCA分析结果表明:主成分1集中反映了城市发展水平及规模对城市热环境的影响;主成分2集中反映了气象因素对城市热环境的影响;主成分3集中反映了天气状况对城市热环境的影响;主成分4集中反映了城市人口及人口密度对城市热环境的贡献;③构建了应对西安都市圈城镇热岛效应的宏观调控体系,体系由3个一级指标和15个二级指标构成;④针对城市规划提出了城市热环境调控的总体规划,包括城市规模规划、人口和人口密度规划、城市绿化和水域的总体规划;针对工业热源提出了控制高热企的比例、有效降低企业能耗和控制三废排放的绝对量;针对民用热源提出了倡导低碳生活理念和营造低碳生态环保氛围的对策和建议。
     本文在以下几个方面有所创新:
     ①将景观生态学理论引入城市热环境研究中,利用景观格局、过程机制探讨城市热环境演变,结果表明这种方法能够很好的阐释城市热环境时空格局动态演变特征;②定量剖析了不同遥感指数(NDVI、NDBI和NDWI)与城市地表温度间的定量关系。并引入分形理论,能够较好的闸释LST与不同土地利用类型间的相关系;③将元胞自动机理论与马尔可夫模型相结合,提出了用于城市热环境模拟与预测的UHI-CA-Markov模型,并取得了较好的模拟与预测结果;④针对城市热环境,在定性分析影响因素的基础上,应用基于多元目标分析的PCA方法,计算了不同影响因子对城市热环境的贡献率大小,并提出了城市热岛效应的评价指标和应对与缓解城市热岛效应的宏观调控建议。
The rapid development of urbanization has brought far-reaching implications to the environment and the ecological security in the city zone. With the rapid changes of the land use and cover, the physical and chemical features changes of land surface have made a great impact on the transformation between atmospheric water and the energy substance, which have an effect on the urban heat environment. A series of environmental problem and ecological security arised from the urban heat island have made a negative effect on the urban continual development. Therefore. State release《National Plan for Med-to-long-term Scientific and Technological Development》. in which it is requested to study the form mechanism of Urban Heat Island and the man-made technology in order to advance the city function and the city space managing use. Also it emphasizes the essentiality to the Urban Heat environment for constructing the modern urbanization.
     This study choose the Xi'an metropolitan as the research area, based on the Landsat TM and ETM+from 1988 to 2009, by using the climate data and land use/cover data as an assistant with the quantificational simulation and the GIS technology for evaluation the Land surface temperature in different years and different seasons. This paper also used the theory of Landscape Ecology for assessment of the Heat Island Landscape and the scale effects of Xi'an, Xianyang and Xingping. The paper also discussed the characteristics of spatial-temporal fractal and scale effect on surface temperature of Xi'an. The relationship between changes of land cover and various factors were studied quantitatively; and this paper also discussed the Quantitative influence of land cover of parks to surrounding areas. A UHI-CA-Markov model for urban thermal environment simulation has been developed based on Cellular automata and Markov model. We also analyzed the contribution of the factors to Urban Heat Island effect by using the method of Principal Component Analysis with multiple purposes. The system of control and countermeasures for Urban Heat Island effect were constructed from the adjustment of urban planning, control of industrial heat sources and control of civilian heat sources. In this research, some important results have been concluded:
     (1) There are different levels of Urban Heat Island effect in Xi'an metropolitan.
     ①The classification system of Urban Heat Island based on the isometric way were suitable for medium and large scale building area to set up the thermal environment of urban indicators and evaluation system, and the Mean Error-based classification system were more suitable for construction four heat environmental indicators and evaluation system of city, county, town, township.②The normal temperature area were dominant at the structure of the thermal environment in Xi'an, Xian yang and Xingping. In the Xi'an and Xianyang, the area size of different UHI types were normal temperature zone>Green island zone>Heat island zone>Strong heat island zone>Strong green zone, and the Xiping city, the area size of different UHI types were normal temperature zone>Heat island zone>Green island zone>Strong heat island zone>Strong green zone.③The land surface temperature in different seasons were changed obviously.
     (2) The spatial-temporal differentiation of the UHI landscape pattern is very large.
     ①It is indicated by the index of landscape level that:the normal temperature zones was always the dominant patch in Xi'an. Xianyang and Xingping from 1988 to 2006.②The Contagion index showed a higher intensive trend, which suggested that the entire landscape elements of Xi'an. Xianyang and Xingping become a intensive and an disorder trend, with the increasing fragmentation index. Shannon's diversity index and Shannon's evenness index showed a slight reduction at first, followed by slightly decreased trend, which indicated land use in Xi'an were stable over time, with the broken degree decreasing, the pattern of thermal landscape tend to be stabilization.③The surface temperature profile showed similar structural characteristics in different scales. As the research-scale increasing, the profile began to become more smooth and continuous, and the detailed features began to disappear, but the overall trend have been maintained, and when the scale reached 150m, the jump phenomenon were happened, therefore, the 150 m was the maximum scale to study the Urban Heat Island.
     (3) The expression of quantitative relationships between the land surface temperature and land use and land cover were set up.
     ①The surface temperature of land use and land cover in Xi'an in summer from high to low were as follows:bare land> construction land> woodland> forest land>grass land>water. But in winter were that:forest land> cultivated land>bare land>the construction land>grass land>water.②LST and NDVI showed a significant negative correlation in summer. LST and NDBI presented positive correlation. LST and NDWI showed a typical negative correlation, which showed the water has a good cooling effect in summer.③With the morphological parameters (size, aspect, shape index,etc) of parks to its neighboring region of the thermal environment were different, The park area was a decisive factor to the average temperature. The park average temperature reducer range has a strong positive correlation between the aspect ratio and shape index of park. the extent of reducer average temperature showed a lower level of positive correlation between the water area, length-width and shape index. The Lmax and Tmax of Xing' qing and Datang Park are higher than other parks which have the water less than 30%. Therefore, the park construction, not only should consider its shape, but also should consider the water area. Generally speaking, water area accounts for park area more than 30% is preferred.
     (4) The results of Xi'an thermal environment simulation indicated that the future heat island effect tend to be better.
     ①The results of the thermal environment simulation of Xi'an in 2012 based on the UHI-CA-Markov model showed that, the strong heat island and heat island area minor reductions, normal temperature area, the green zone present slightly increasing, strong green zone showed a stable trend by contrasting with thermal environment in 2006.②The results of the thermal environment simulation of Xi'an in 2018 respectively compared with the 2012, the strong heat island area showed a few increasing, the heat island area showed a trend of stabilization, the normal temperature was a substantial increasing, green island and strong green island area showed a strong decreasing.③The results of simulation from 2006 to 2018 showed that the future thermal environment of Xi'an tends to be better, normal temperature area is dominated in the research area, but local thermal environment have further deterioration trend. Therefore, the proposal in urban planning and construction of the thermal environment planning for the resident should be considered as an important component.
     (5) The cause of Urban Heat Island was analyzed and countermeasures systerm was established.
     ①The paper put forward the four aspects to construct the Urban Heat Island system including the factors to increase the UHI were strengthened, to alleviate the factors were reduced, the temporary and permanence factors. And four aspects were further broken down 11 categories and 20 secondary indicators.②The results of PCA analysis showed that the principal component 1 reflected the level and scale of city development, mainly including the urban population, building area information; principal component 2 concentrated reflection of urban heat meteorological factors, including the precipitation, relative humidity and other information; principal component 3 concentrated reflection the weather conditions on the urban thermal environment, including wind speed; principal component 4 concentrated reflection of the urban population, population density and the contribution of the urban thermal environment.③Construction the system of urban heat island effect of Xi'an metropolitan, the system consist of three first-order index and 15 sub-indicators.④Urban planning are presented in the overall planning of urban thermal environment, including the size of city planning, population and the population density planning, urban greening and water master plan. According to industrial heat proposed control the proportion of high fever; effectively reduce the enterprise energy consumption and emissions control "three wastes" absolute. According to civil heat proposed initiative low carbon life concept and build low-carbon ecological and environment protection countermeasures and suggestions.
     There are some progression and innovation in the article as follows:
     ①The paper introduced the landscape ecology into the thermal environment study, by using the landscape index and the process mechanism of evolution of urban thermal environment. The results showed the approach could very well explanation of spatial-temporal urban thermal environment characteristics of dynamic evolution.②The paper also get the relationship between the different remote sensing index and the surface temperature by the way of the quantitative analysis. We can be better expalining the correlation changes between the different land use and the LST by the fractal theory.③A model named UHI-CA-Markov were set up by combining the cellular automata and markov model, which have achieved a good results for the UHI simulation.④For the thermal environment, A qualitative analysis were presented based on multiple objective analysis of the PCA method, and calculated the various factors on the constribution to the Urban Heat Island, then put forward a evaluation index system of the Urban Heat Island, a Relieving system of Urban Heat Island effect were also established.
引文
[1]联合国.联合国气候变化框架公约[N].1992.
    [2]联合国.京都议定书[N].日本.1997.12.
    [3]米金套.澳门城市景观格局变化与热岛效应研究[D].北京:北京林业大学[博士学位论文].2009.
    [4]冯晓刚,李锐,莫宏伟.基于RS和GIS的城市扩展及驱动力研究[J].遥感技术与应用.2010.25(2):202-208.
    [5]中华人民共和国国务院.国家中长期科学和技术发展规划纲要(2006-2020)[N].人民日报报.2006-02-10(1).
    [6]陈云浩,史培军.李晓兵.基于遥感和GIS的上海城市空间热环境研究[J].测绘学报.2002.31(2):139-144.
    [7]陈云浩,王洁.李晓兵.夏季城市热场的卫星遥感分析[J].国土资源遥感.2002.54(1):55-59.
    [8]赵红旭.昆明市热岛效应卫星监测研究[J].国土资源遥感.1999.4:29-32.
    [9]陈云浩.李晓兵.史培军等.上海城市热环境的空间格局分析[J].地理科学.2002,22(3):318-322.
    [10]Stathopoulou M, Cartalis C. Daytime urban heat islands from Landsat ETM+ and Corine land cover data An application to major cities in Greece[J]. Solar Energy, 2007,81(3):358-368.
    [11]胡华浪,陈云浩,宫阿都.城市热岛的遥感研究进展[J].国土资源遥感,2005,6(9):5-9.
    [12]Howard L. Climate of London deduced from meteorological observation[J]. Harvey and Darton,1833,1(3):1-24.
    [13]周淑贞,束炯.城市气候学[M].北京:气象出版社,1994.
    [14]Camahan W H, Larson R C. An Analysis of an Urban Heat Sink. Remote Sensing of Environment,1990,33:65-71.
    [15]邱新法,顾丽华,曾燕等.南京城市热岛效应研究[J].气候与环境研究,2008,13(6):807-814.
    [16]David J, Sailor Lu. A top-down methodology for developing diurnal and seasonal Anthropogenic heating profiles for urban areas[J]. Atmospheric Environment, 2004,39(3):2737-2748.
    [17]盛辉,万红,崔健勇.基于TM影像的城市热岛效应监测与预测分析[J].遥感技术与应用,2010,25(1):8-14.
    [18]戴晓燕,张利权,过仲阳,等.上海城市热岛效应形成机制及空间格局[J].生态学报.2009,29(7):3995-4003.
    [19]骆杨,周锁铨,孙善磊等.杭州城市热岛空间分布及时域-频域多尺度变化特征[J].生态环境学报,2009,18(6):2200-2205.
    [20]张旭阳,宁海文,杜继稳等.西安城市热岛效应对夏季高温的影响[.J].干旱区资源与环境,2010,24(1):95-100.
    [21]贡璐,吕光辉.基于景观的干早区城市热岛效应变化研究[J].中国沙漠,2009.29(5):982-988.
    [22]岳文泽.基于遥感影像的城市景观格局及其热环境效应研究[M].上海:华东师范大学[博士学位论文],2005,
    [23]Juan juan Li, Xiang rang Wang, Xin-jun Wang. Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area,China. Ecological Complexity,2009,6:413-420.
    [24]周荣卫.蒋维楣,何晓凤.城市冠层结构热力效应对城市热岛形成及强度影响的模拟研究[J].地球物理学报,2008.51(3):716-726.
    [25]王翠云.基于遥感和CFD技术的城市热环境分析与模拟—以兰州市为例[D].兰州:兰州大学[博士学位论文],2008.
    [26]Umamaheshwaran Rajasekar, Qinhao Weng. Urban heat island monitoring and analysis using a non-parametric model:A case study of Indianapolis[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2009,64:86-96.
    [27]陈志,俞炳丰,胡汪洋等.城市热岛效应的灰色评价与预测[J].西安交通大学学报,2004,38(9):985-988.
    [28]何萍,陈辉,李宏波等.云南高原楚雄市热岛效应因子的灰色分析[J].地理科学进展,2009,28(1):25-32.
    [29]冯薇薇,刘慧平,朱涛等.城市扩张对东莞市陆表温度的影响分析[J].地理与地理信息科学,2010,26(3):87-90.
    [30]徐涵秋,陈本清.城市热岛与城市空间发展的关系探讨—以厦门市为例[J].城市生态与环境,2004,11(2):65-70.
    [31]张小飞,王仰麟,吴健生等.城市地域地表温度—植被覆盖定量关系分析—以深圳市为例[J].地理研究,2006,25(3):369-376.
    [32]季青,贺伶俐,余明等.基于Landsat ETM+数据的福州市土地利用/覆被与城 市热岛的关系研究[J].福建师范大学学报(自然科学版).2009.25(6):106-113.
    [33]Chen Xiaoling, Zhao Hongmei, Li Pingxiang. et al. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes[J]. Remote Sensing of Environment,2006,104:133-146.
    [34]张宏利.陈豫,张纳伟锐等.西安市热岛效应变化特征与城市人口发展研究[J].水土保持研究,2009,16(4):131-136.
    [35]郑柞芳,王迎春,刘伟东.地形及城市下垫面对北京夏季高温影响的数值研究[J].热带气象学报.2006,22(6):672-676.
    [36]景元书.张惠君.南京城市化进程及温室效应研究[J].安徽农业科学,2009.37(18):8614-8615.8690.
    [37]王伟武.李国梁,薛瑾.杭州城市热岛空间分布及减缓对策[J].自然灾害学报,2009.18(6):14-20.
    [38]Voogt, J.A. Oke. T.R. Thermal remote sensing of urban climates[J]. Remote Sensing of Environment,2003,86:370-384.
    [39]张健,章新平.王晓云 等.北京地区气温多尺度分析和热岛效应[J].干旱区地理,2010,33(1):51-58.
    [40]林学椿,于淑秋.北京地区气温的年代际变化和热岛效应[J].地理物理学报,2005,48(1):42-44.
    [41]Brian Stone, John M.Norman. Land use planning and surface heat island formation:A parcel-based radiation flux approach[J]. Atmospheric Environment, 2006,40(19):3561-3573.
    [42]David J, Sailor Lu. A top-down methodology for developing diurnal and seasonal Anthropogenic heating profiles for urban areas[J]. Atmospheric Environment, 2004,39(3):2737-2748.
    [43]Hongli Fan, David J Sailor. Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia:a comparison of implementations in two PBL schemes[J]. Atmospheric Environment,2005,39(1):73-84.
    [44]何萍,李宏波.云贵高原中小城市热岛效应分析[J].气象科技,2002,30(5):288-291.
    [45]江田汉,束炯,邓莲堂.上海城市热岛的小波特征[J].热带气象学报,2004,20(5):515-521.
    [46]刘熙明.胡非,李磊等.北京地区夏季城市气候趋势和环境效应得分析研究[J].地球物理学报,2006,49(3):689-697.
    [47]刘学锋,阮新,谷永利.石家庄地区气温变化和热岛效应分析[J].环境科学研究,2005,18(5):11-14.
    [48]石春娥,王兴荣,吴必文等.合肥市夏季热岛特征研究[J].南京气象学院学报,2005,28(5):672-677.
    [49]王郁,胡非.北京地区夏季城市热岛的气候趋势和环境效应的分析研究.地球物理学报,2006,49(1):61-68.
    [50]邱新法,顾丽华,曾燕等.南京城市热岛效应研究[J].气候与环境研究,2008,13(6):807-814.
    [51]陈正洪,王海军,仟国玉.武汉市城市热岛强度非对称性变化[J].气候变化研究进展,2007,5(3):282-286.
    [52]韩素芹,郭军,黄遂樑等.天津城市热岛效应演变特征研究[J].生态环境.2007,16(2):280-284.
    [53]李卓仑,王乃昂,轧靖等.近40年兰州城市气候季节性变化与城市发展[J].高原气象,2007,26(3):581-591.
    [54]张恩洁,张晶晶,赵听奕等.深圳城市热岛研究[J].自然灾害学报,2008,17(2):19-24.
    [55]高红燕,蔡新玲.贺皓等.西安城市化对气温变化趋势的影响[J].2009,64(9):1093-1101.
    [56]王珊珊,艾里西尔库尔班,郭宇宏等.乌鲁木齐地区气温变化和城市热岛效应分析[J].干旱区研究,2009,26(3):433-440.
    [57]彭文甫,张东辉,何政伟等.成都市地表温度对不透水面的响应研究[J].遥感应用,2010,2:98-102.
    [58]宫阿都,徐捷,赵静等.城市热岛研究方法概述[J].自然灾害学报,2008,17(6):96-99.
    [59]胡嘉骢,朱启疆.城市热岛研究进展[J].北京师范大学学报(自然科学版),2010,46(2):186-193.
    [60]Rao P.K. Remote sensing of Urban Heat Island from an environmental satellite[J]. Bulletin of the American Meteorological Society,1972,53:647-648.
    [61]Jimenez-Munoz J C,Sobrino J A. A Generalized Single-channel Method ofr Retrieving Land Surface Temperature from Remote Sensing Data[J]. Journal of Geophysical Research,2003,108(D22):4688-4695.
    [62]Sobrino J A. Jimenez-Munoz J C, Paolini L. Land surface temperature retrieval from Landsat TM 5[J]. Remote Sensing of Environment,2004,90:434-440.
    [63]丁凤,徐涵秋.TM热波段图像的地表温度反演算法与实验分析[J].地球信息科学.2006,8(3):125-130.
    [64]李福建,马安青,丁原东 等.基于Landsat数据的城市热岛效应研究[J].遥感技术与应用,2009,24(4):553-558.
    [65]郑伟,曾志远.遥感图像大气校正方法综述[J].遥感信息,2004.4:66-70.
    [66]覃志豪,Zhang Minghua, Arono 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.
    [67]覃志豪,Li Wenjuan, Zhang Minghua等.单窗算法的大气参数估计方法[J].国土资源遥感,2003,2:37-43.
    [68]Jimenez-Munoz J C.Sobrino J A. A Generalized Single-channel Method ofr Retrieving Land Surface Temperature from Remote Sensing Data[J]. Journal of Geophysical Research.2003,108(D22):4688-4695.
    [69]Qin Z. Karnieli A. A Mono-window Alorithm for Retrieving Land Surface Temperature from Landsat TM Data and Its Application to the Lsrael-Egypt Border Region[J]. International Journal of Remote Sensing,2001,22(18):3739-3756.
    [70]黄妙芬.刑旭峰.王培娟 等.利用Landsat/TM热红外通道反演地表温度的三种方法比较[J].干旱区地理,2006,29(1):132-137.
    [71]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,2004,61(3):8-32.
    [72]McMillin L M. Estimation of sea surface temperature from two infrared window measurements with different absorption[J]. Journal of Geophysical Research,1975, 20:5113-5117.
    [73]PRICE J C. Land surface temperature measurements from the Split-window channels of the NOAA/AVHRR[J]. J.Geophys.Res,1984,79:5039-5044.
    [74]Becker F. The impact of spectral emissivity on the measurement of land surface temperature from a satellite[J]. Int J Remote Sens,1987,10:1509-1522.
    [75]PRATA A J. Land surface temperature derived from the advanced very high resolution radiometer and the along-track scanning radiometer. Experimental results and validation of AVHRR algorithms[J]. J. Geophys.Res,1994,99:13025-13058.
    [76]Qin Z, Ohn G D, Karnieli A, etal. Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperatere form NOAA-AVHRR data[J]. Journal of Geophysical Research,2001,106(D19):22655-22670.
    [77]王君华,黄永磷.我国利用MODIS数据反演陆面温度的研究进展[J].广西气象,2005,26(4):18-20.
    [78]Wan Z. Dozier J. A generalized Split-window Algorithm for Retrieving Land-Surface Temperature from Space[J]. IEEE Transaction on Geoscience and Remote Sensing,1996,34(4):892-905.
    [79]覃志豪,高懋芳,秦效敏.农业旱灾监测中的地表温度遥感反演方法—以MODIS数据为例[J].自然灾害学报,2005,14(3):64-70.
    [80]夏俊土,杜培军,张海荣等.基于遥感数据的城市地表温度与土地覆盖定量研究[J].遥感技术与应用,2010,25(1):15-22.
    [81]张佳华.李欣,姚凤梅 等.基于热红外光谱和微波反射地表温度的研究进展[J].光谱学与光谱分析.2009,29(8):2103-2107.
    [82]王今殊.李贵才.刘玉洁等.北京地区陆表温度空间分布特征[J].测绘科学.2009,34(6):218-220.
    [83]田振坤,黄妙芬.刘良云等.使用单窗算法研究北京城区热岛效应[J].遥感信息,2006,1:21-24.
    [84]张兆明,何国金,肖荣波等.基于RS与GlS的北京市热岛研究[J].地球科学与环境学报.2007.29(1):107-110.
    [85]彭静,刘伟东,龙步菊等.北京城市热岛的时空变化特征[J].地球物理学进展,2007,22(6):1942-1947.
    [86]陈云浩,宫阿都,李京.基于地表辐射亮温标准化的城市热环境遥感研究[J].中国矿业大学学报,2006,35(4):462-467.
    [87]葛伟强,周红妹,杨引明等.基于遥感和GIS的城市绿地缓解热岛效应作用研究[J].遥感技术与应用,2006,21(5):432-435.
    [88]陈锋,何报寅,龙占勇等.利用Landsat ETM+分析城市热岛与下垫面的空间分布关系[J].国土资源与遥感,2008,76(2):56-61.
    [89]赵小艳,杨沈斌,申双和等.基于遥感的南京市城市热岛效应时空演变分析[J].安徽农业科学,2009,,37(22):10776-10778.
    [90]樊辉.基于NOAA/AVHRR热红外数据的城市热岛强度年内变化特征[J].遥感技术与应用,2008,23(4):414-418.
    [91]毛克彪,覃志豪,刘伟.用MODIS影像和单窗算法反演环渤海地区的地表温度[J].测绘与空间地理信息,2004,27(6):23-25.
    [92]徐金鸿.基于遥感技术的广州市热岛效应分析[J].云南地理环境研究,2008,20(6):41-44.
    [93]徐永明,覃志豪,朱炎.基于遥感数据的苏州市热岛效应时空变化特征分析[J].地理科学.2009.29(4):529-534.
    [94]Weng Qihao. A remote sensing GIS evaluation of urban expansion and its impact on surface temperature in Zhujiang dela Chia[J]. International Journal of Remote Sensing,2001,22(10):1999-2014.
    [95]Weng Qihao, Lu Dengsheng, Jacquelyn Schubring. Estimation of land surface temperature-vegation abundance relationship for urban heat island studies[J]. Remote Sensing of Environment,2004,89:467-483.
    [96]Xiao-Ling Chen, Hong-Mei Zhao, et al. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes[J]. Remote Sensing of Environment,2006.104:133-146.
    [97]Martha K..R. Josefino C.C. et al. Relationship between satellite-derived land surface temperatures arctic vegatation types.and NDVI[J]. Remote Sensing of Environment.2008.112:1884-1894.
    [98]潘竟虎,刘春雨,李晓雪.基于混合光谱分解兰州城市热岛与下垫面空间关系分析[是J].遥感技术与应用.2009.24(4):642-648.
    [99]陈声海.魏信,王修信等.小区地表温度与下垫而结构关系研究[J].国土资源遥感,2009,81(3):49-53.
    [100]温兴平,胡光道,杨晓峰.基于Landsat影像下广州市植被覆盖变化对城市热岛的影响[J].生态环境,2008,17(3):985-988.
    [101]王艳娇,闫峰,张培群等.基于植被指数和地表反照率影响的北京城市热岛变化[J].环境科学研究,2009,22(2):215-220.
    [102]Youshui Zhang, Inakwu O.A.Odeh. etal. Bi-teporal characterization of land surface temperature in relaiton to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis[J]. International Journal of Applied Earth Observation and Geoinformation,2009,11:256-264.
    [103]王宇.全球地表温度100年内将上升1.4至5.8摄氏度[J].生态经济,2004,6:27.
    [104]毛克彪,覃志豪,施建成.用MODIS影像和劈窗算法反演山东半岛的地表温度[J].中国矿业大学学报,2005,34(1):46-50.
    [105]秦晓敏,覃志豪,毛克彪.基于MODIS数据的陕西省地表温度的空间分布研究[J].干旱区地理,2005,28(4):548-553.
    [106]Honglin Xiao, Qihao Weng. The impact of land use and land cover changes on land surface temperature in a karst area of China[J]. Journal of Environmental Management,2007,85:245-257.
    [107]江学顶,夏北成.珠江三角洲城市群热环境空间格局动态[J].生态学报.2007,27(4):1461-1469.
    [108]叶智威,覃志豪,宫辉力.洪泽湖区的Landsat TM6地表温度遥感反演和空间差异分析[J].首都师范大学学报(自然科学版),2009,30(1):88-94.
    [109]张金区.珠江三角洲地区地表热环境的遥感探测及时空演化研究[M].广州:中国科学院[博士学位论文],2006.
    [110]于艳梅,甘甫平,周萍等.热红外遥感火星矿物填图方法初步研究及应用[J].国土资源遥感.2009,82(4):45-39.
    [111]季灵运,许建东,临旭东等.利用卫星热红外遥感技术监测长白山天池火山活动性[J].地震地质,2009.31(4):617-625.
    [112]史培军,潘耀忠.陈晋等.深圳市土地利用/覆盖变化与生态环境安全分析[J].自然资源学报,1999.14(4):293-299.
    [113]孙飒梅,卢昌义.遥感监测城市热岛强度及其作为生态监测指标的探讨[J].厦门大学学报(自然科学版).2002,41(1):66-70.
    [114]贡璐.干旱区城市热岛效应定量研究[M].新疆大学博士学位论文,2007.
    [115]Carlson T.N,Augustin J.A, Boland F.E. Potential application of satellite temperatures measurements in the analysis of land use over urban areas[J]. Bull Amer Meteor Soc,1977,58:1301-1303.
    [116]Balling R C, Brazell S W. High resolution surface temprature patterns in a comples urban terrain[J]. Photogrammetric Engineering and Remote Sensing, 1988,54:1289-1293.
    [117]Jan Hafner and Stanley Q.Kidder. Urban Heat Island Modeling in Conjunction with Satellite-Derived Surface/Soil Parameters[J]. Journal of Applied Meteorology, 1999,38:448-465.
    [118]Qihao Weng, Dengsheng Lu, et al. Estimatioin of land surface temperature-vegetation abundance relationship for urban heat island studies[J]. Remote Sensing of Environment 2004,89:467-483.
    [119]Soushi K, Yasushi Y. Analysis of urban heat-island effect using ASTER and ETM+ Data:Separation of anthropogenic heat discharge and natural heat radiation from sensible heat flux[J]. Remote Sensing of Environment,2005,99:44-54.
    [120]Tran H, Daisuke U, Shiro O, etal. Assessment with satellite Data of the Urban Heat Island Effects in Asian Mega Cities[J]. International Journal of Applied Earth Observation and Geoinformation,2006,8(1):34-48.
    [121]Reza Amiri, Qihao Weng, etal. Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use cover in the Tabriz urban area,Iran[J]. Remote Sensing of Environment.2009,113:2606-2617.
    [122]毛克彪,唐华俊,陈仲新等.一个从ASTER数据中反演地表温度的劈窗算法[J].遥感信息,2006,5:7-11.
    [123]姜立鹏,覃志豪.谢雯.针对MODIS数据的地表温度非线性迭代反演方法[J].遥感技术与应用,2006,21(6):483-487.
    [124]高懋芳.覃志豪.徐斌.用MODIS数据反演地表温度的基本参数估计方法[J].干旱区研究,2007,24(1):113-119.
    [125]段四波,阎广建,钱水刚等.利用HJ-1B模拟数据反演地表温度的两种单通道算法[J].自然科学进展,2008,18(9):1001-1008.
    [126]范心圻.刘继伟.钱彬等.我国主要城市热岛现象动态监测研究[C].环境监测与作物估产遥感研究论文集,北京:北京大学出版社,1991.171-189.
    [127]王芝生.郭淑麟.钱彬.上海城区航卫片过地表层的热力景观分析研究[C].环境监测与作物估产遥感研究论文集,北京:北京大学出版社,1991,210-220.
    [128]杨星卫,周红妹.卫星资料在上海浦东新区热力场分析中的应用[J].应用气象学报,1994,8:370-373.
    [129]周红妹NOAA卫星在上海市热力场动态监测中的应用[J],大气科学与应用,1998,1:23-28.
    [130]赵红旭.昆明市热岛效应卫星监测研究[J].国土资源遥感,1999,42(4):29-32.
    [131]纪瑞鹏,张喜民,李刚.沈阳等6城市热岛效应卫星监测[J].辽宁气象,2000,(4):22-23.
    [132]周红妹,高阳,葛伟强.城市扩张与热岛空间分布变化关系研究[J].生态环境,2008,17(1):163-168.
    [133]刘三超,张万昌.张掖绿洲城市热岛效应的遥感研究[J].国土资源遥感,2003,58(4):17-21.
    [134]李延明,郭佳,冯久莹.城市绿色空间及对城市热岛效应的影响[J].城市环境和城市生态,2004,17(1):1-4.
    [135]宫阿都,李京,王晓娣等.北京城市热岛环境时空变化规律研究[J].地理与地理信息科学,2005,21(6):15-18.
    [136]苏伟忠,杨英宝,杨桂山.南京市热场分布特征及其与土地利用/覆被关系研 究[J].地理科学,2005,25(6):697-703.
    [137]叶柯,覃志豪.基于MODIS数据的南京市夏季城市热岛分析[J].遥感技术与应用,2006,21(5):426-431.
    [138]Jinqu Zhang, Yunpeng Wang, Yan Li. A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6[J]. Computers & Geosciences,2006,32:1796-1805.
    [139]Xiaoling Chen, Hongmei Zhao, etal. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes[J]. Remote Sensing Environment,2006,104:133-146.
    [140]Rongbo Xiao, Zhiyun OUYANG. etal. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China[J]. Journal of Environmental Sciences,2007,19:250-256.
    [141]周纪.陈云浩,李京等.基于遥感影像的城市热岛容量模型及其应用[J].遥感学报,2008.]2(5):734-741.
    [142]杜灵通.基于Landsat ETM+数据的银川城市热岛研究[J].测绘科学,2008,33(4):169-171.
    [143]孙华,林辉,熊育久.基于Landsat TM图像的长株潭城市群地表温度遥感反演[J].中南林业科技大学学报,2008,28(2):85-90.
    [144]武鹏飞,王茂军,张学霞.基于归一化建筑指数的北京市城市热岛效应分布特征[J].生态环境学报,2009,18(4):1325-1331.
    [145]陈辉,古琳,黎燕琼等.成都市城市森林格局与热岛效应的关系[J].生态学报,2009,29(9):4865-4873.
    [146]季青,余明.基于CBERS-02 IRMSS和MODIS数据的地表温度反演与热坏境评价[J].地理与地理信息科学,2009,25(6):78-81.
    [147]IGBP SCIENCE NO.1. The terrestrial bioshere and global change:implications for natural and managed ecosystems. Synthesis of GCTE and Related Research.
    [148]IGBP SCIENCE NO.3. Environmental Variability and Climate Change.
    [149]IGBP SCIENCE NO.4. Global Change and the Earth System:A Planet Under Pressure.
    [150]徐兴奎.互补相关理论在卫星遥感领域的应用研究[J].遥感学报,1999:3(1):133-145.
    [151]王翠云.基于遥感和CFD技术的城市热环境分析与模拟—以兰州市为例[D].兰州:兰州大学[博士学位论文].2004.
    [152]田国良等.热红外遥感[M].北京:电子工业出版社,2006.
    [153]Taha H. Modifying a mesoscale meteorological model to better incorporate urban heat storage:a bulk-parameterization approach[J]. Journal of Applied Meteorology. 1999,38:466-473.
    [154]陈亮,张弘,孟伟.城市热岛效应与热效应模型研究[J].环境科学研究,2004.17(2):65-67.
    [155]陈志,俞炳丰.胡汪洋 等.城市热岛效应的灰色评价与预测[J].西安交通大学学报,2004,38(9):985-988.
    [156]卢军,冯源,沈薇.计算机模拟辅助云阳县热环境规划[J].重庆建筑大学学报,2006,28(1):84-87.
    [157]缪爱国,李宁.缓解夏季城市热岛效应的数值模拟研究[J].徐州工程学院学报,2007.22(6):53-56.
    [158]曹丽琴,张良培,李平湘等.城市下垫面覆盖类型变化对热岛效应影响的模拟研究[J].武汉大学学报(信息科学版).2008,33(12):1229-1232.
    [159]周荣卫,将维楣,何晓凤.城市冠层结构热力效应对城市热岛形成及强度影响的模拟研究[J].地球物理学报.2008.5 1(3):715-726.
    [160]李立华,傅爱民.论城市热岛效应的地貌成因[J].华中师范大学学报(自然科学版),1992,26(4):506-510.
    [161]Kim H H. Urban heat island[J]. International Journal of Remote Sensing,1992, 13(12):2319-2336.
    [162]杨德保,王式功,王玉玺.兰州城市气候变化及热岛效应分析[J].兰州大学学报(自然科学版),1994,30(4):161-167.
    [163]郦桂芬,马鸿良.酒泉市城市热岛成因分析[J].干旱环境监测,1996,10(4):220-221.
    [164]黄嘉佑,刘小宁,李庆祥.中国南方沿海城市热岛效应与人口的关系研究[J].热带气象学报,2004,20(6):713-722.
    [165]Kato S. Yamaguchi Y. Analysis of urban heat-island effect using ASTER and ETM+Data:Separation of anthropogenic heat discharge and nature heat radiation from sensible heat flux[J]. Remote Sensing of Environment,2005,99:44-54.
    [166]田喆,朱能,刘俊杰.城市气温与人为影响因素的关系[J].天津大学学报,2005,38(9):830-833.
    [167]郑艳,潘家华,吴向阳.影响北京城市增温的主要社会经济因子分析[J].气候变化研究进展,2006,4(2):188-192.
    [168]陈云浩,李晓兵,宫阿都.基于遥感的城市空间热环境寻因分析[J].同济大学学报,2006,34(6):782-785.
    [169]张新,孔永健,关彦斌.沥青路面对城市大气受热的影响分析[J].金陵科技学院学报,2006,22(2):16-18.
    [170]肖荣波,欧阳志云,李伟峰等.城市热岛时空特征及其影响因素[J].气象科学,2007,27(2):230-236.
    [171]鹏少麟,叶有华.城市热岛效应对城市规划的影响[J].中山大学学报(自然科学版).2007,46(5):59-63.
    [172]马东升.朝阳市城市热岛效应浅析[J].辽宁师专学报.2008.20(3):77-80.
    [173]张科平.改善上海城市热岛效应的对策研究[J].上海铁道大学学报,1998.19(8):49-52.
    [174]刘文杰.李红梅.景洪市城市热岛效应对城市高温的影响及其防御对策[J].热带地理,1998,18(2):143-146.
    [175]延昊.利用遥感地表参数分析上海市的热岛效应及治理对策[J].热带气象学报,2004.20(5):579-585.
    [176]周志翔,邵天一,唐万鹏等.城市绿地空间格局及其环境效应—以宜昌市中心城区为例[J].生态学报,2004,24(2):186-192.
    [177]王艳霞,董建文等.城市绿地与城市热岛效应关系探讨[J].亚热带植物科学,2005,34(4):55-59.
    [178]颜玲.长沙市热岛效应遥感分析及其防治措施[J].工程于环境地质,2006,3(3):155-157.
    [179]唐鸣放,王东,郑开郦.山地城市绿化与热环境[J].重庆建筑大学学报,2006,28(2):1-3.
    [180]王朝春.城市气候高温化的成因与对策—以福州市城区为例[J].城市问题,2006,137(9):98-102.
    [181]陕西省人民政府. 陕西省城镇体系规划(2006-2020年)[N].陕西省人民政府,2006,2.
    [182]陕西师范大学地理系编.西安市地理志[M],陕西:陕西省人民出版社,1988.
    [183]陕西师范大学地理系编.咸阳市地理志[M],陕西:陕西省人民出版社,1991.
    [184]Manley G. On the freguency of snowfall in metropolitan England. Quart. J. Roy. Meteor. Soc,1958,84:70-72.
    [185]愈宏,石汉青.利用分裂窗算法反演陆地表面温度的研究进展[J].气象科学,2002,22(4):494-499.
    [186]Christopher small. Comparative analysis of urban reflectance and surface temperature[J]. Remote Sensing of Environment.2006.104:168-189.
    [187]王伟武.地表演变对城市热环境影响的定量研究[D].杭州:浙江大学[博士学位论文].2004.
    [188]蒋卫国.武建军,顾磊 等.基于夜间热红外光谱的地下煤火监测方法研究[J].光谱学与光谱分析,2011,32(2):357-361.
    [189]王旻燕,吕达仁.GMS5资料反演地表温度的一个修正算法[J].地球物理学报.2005,48(5):1034-1044.
    [190]Jimenez-Munoz J C, Sobrino J A. A Generalized Single-charrnel Method for Retrieving Land Surface Temperature from Remote Sensing Data[J]. Journal of Geophysical Research.2003.108(D22):4688-4695.
    [191]JENNIFER F. KAYA A.R. Spatial relationships between snow contaminant content, grain size, and surface temperature from multispectral images of Mt. Rainier. Washington(USA)[J]. Remote Sensing of Environment,2003,86:216-231.
    [192]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社.2003.
    [193]Enric Valor, Vicente Caselles. Mapping Land Surface Emissivity from NDVI:Application to European, African, and South American Areas[J]. Remote Sensing of Environment,1996,57(3):167-184.
    [194]Cesar Coll, Vicente Caselles, Joan M, et al. Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data[J]. Remote Sensing of Enviroenment,2005,97:288-300.
    [195]邬建国.景观生态学:格局、过程、尺度及等级[M].北京:高等教育出版社,2000.
    [196]周华峰,马克明,傅伯杰.人类活动对北京东灵山地区景观格局影响分析[J].自然资源学报,1999,14(2):117-122.
    [197]Luck M, Wu J. A gradient analysis of urban landscape pattern:A case study from the Phoenix metropolitan region, Arizona, USA[J]. Landscape Ecology,2002, 17:327-339.
    [198]李月臣,宫鹏,陈晋等.中国北方13省土地利用景观格局变化分析(1989-1999)[J].水上保持学报,2004,19(4):143-146.
    [199]程维明.马纳斯河流域景观格局及其演化研究[D].北京:中国科学院研究生院[博士学位论文],2003.
    [200]Mandelbrot B B. How long is the coast of Britain? Statistical self-similarity and fractional dimension[J]. Science,1967.156(3775):636-638.
    [201]梁长秀.基于RS和GIS的北京市土地利用/覆被变化研究[D].北京:北京林业大学[博士学位论文].2009.
    [202]孟彩红.基于GIS的兰州城市景观研究[D].兰州:兰州大学[博士学位论文],2008.
    [203]叶红梅.面向流域生态安全的景观格局演变研究—以疏勒河流域为例[D].武汉:华中科技大学[博士学位论文],2009.
    [204]Mandelbrot B B. the fractal geometry of nature[M]. New York:W H Freeman. 1982,45-66.
    [205]陈彦光,刘继生.城市形态分维测算和分析的若干问题[J].人文地理,2007.3:98-103.
    [206]葛方龙,李伟峰,陈求稳.景观格局演变及其生态效应研究进展[J].生态环境.2008,17(6):2511-25]9.
    [207]中华人民共和国建设部.城市用地分类与规划建设用地标准GBJ137-90[N].1990.7.2.
    [208]Jauregui. E. Influence of a large urban park on temperature and convective precipitation in a tropical city[J]. Energy Build.1990.15-16.457-463.
    [209]Chang, C.R., Li, M.H., Chang, S.D. A preliminary study on the local cool-island intensity of Taipei city parks[J]. Urban Plan.2007,80:386-395.
    [210]Upmanis,H.,Eliasson,I.,Lindqvist,S. The influence of green areasonnocturnal temperatures in a high latitude city (Goteborg, Sweden)[J]. Int. J. Climatol. 1998.18:681-700.
    [211]Shashua-Bar,L.,Hoffman, M.E., Vegetationas climatic component in the design of an urban street-anempirical model for predicting the cooling effect of urban green areas with trees[J]. Energy Build.2000,31:221-235.
    [212]武鹏飞,王茂军,张学霞.北京市植被绿度与城市热岛效应关系研究[J].北京林业大学学报,2009,31(5):54-60.
    [213]王娟,蔺银鼎,刘清丽.城市绿地在减弱热岛效应中的作用[J],草原与草坪,2006,6(119):56-59.
    [214]唐罗忠,李职奇,严春风等.不同类型绿地对南京热岛效应的缓解作用[J],生态环境学报,2009,18(1):23-28.
    [215]苏泳娴,黄光庆,陈修治等.广州市城区公园对周边环境的降温效应[J],生态学报,2010,30(18):4905-4910.
    [216]Spronken-Smith. R.A.. Oke, T.R..The thermal regime of urban parks in two cities with different summer climates[J]. Int. J. Remote Sens.1998,19(11):2085-2104.
    [217]Mcgarigal, K., Marks. B.J., FRAGSTATS:Spatial Pattern Analysis Program for Quantifying Landscape Structure. Gen. Tech. Rep. PNW-GTR-351. U.S.D.A[J], ForestService,Pacific. Northwest Research Station,Portland, portland,1995.
    [218]陈志,俞炳丰,胡汪洋等.城市热岛效应的灰色评价与预测[J].西安交通大学学报.2004,38(9):985-988.
    [219]韦海东,赵有益,陈英.兰州市城市热岛效应评价与灰色预测[J].中国沙漠.2009,29(3):571-576.
    [220]何萍.陈辉.李宏波等.云南高原楚雄市热岛效应因子的灰色分析[J].2009.地理科学进展.2009.28(1):25-32.
    [221]Tapper N J, Tyson P D, Owens I F. et al. Modeling the winter urban heat island over Christchurch, New Zealand[J]. Journal of Applied Meteorology,1981,20,365.
    [222]Vukovich F M. A study of the atmospheric response due to a diurnal heating function haracteristic of an urban complex[J]. Monthly Weather Review,1973, 101:467.
    [223]杨梅学,陈长和.复杂地形上城市热岛的数值模拟[J].兰州大学学报(自然科学版),1998,34(3):117.
    [224]Zehnder, Joseph A. Simple Modifications to Improve Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model Performance for the Phoenix, Arizona, Metropolitan Area [J]. Journal of Applied Meteorology,2002,41:971.
    [225]杨玉华,徐祥德,翁永辉.北京城市边界层热岛的日变化周期模拟[J].应用气象学报,2003,14(1):61-68.
    [226]Tong Hua, Andrew W, Sang jianguo, et al. Numerical simulation of the urban boundary-layer over the complex terrain of Hong Kong[J]. Atmospheric Environment,2005,39:3549.
    [227]李鹍.基于遥感与CFD仿真的城市热环境研究—以武汉市夏季为例[D].武汉:华中科技大学[博士学位论文],2008.
    [228]王翠云.基于遥感和CFD技术的城市热环境分析与模拟—以兰州市为例[D].兰州:兰州大学[硕士学位论文],2008.
    [229]周成虎,孙战利,谢一春.地理元胞自动机研究[M].北京:科学出版社,1999.
    [230]熊利亚,常斌,周相广.基于地理元胞自动机的土地利用变化研究[J].资源 科学,2005.27(4):38-43.
    [231]Batty M. Xie Y. Modelling inside GIS:Part1.Model Structures, Exploratory Spatial Data Analysis and Aggregation[J]. International Journal of Geographical Information Systems,1994.8:291-307.
    [232]Clarke K C, Hoppen S, Gaydos L J. A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area[J]. Environment and Planning B,1997,24:247-261.
    [233]Waddell P, Urbansim:Modeling Urban Development for Land Use, Transportation, and Environment Planning[J].Journal of American Planning Association,2002,68(3):297-313.
    [234]张显峰,崔伟宏.继承GIS和细胞自动机模型进行地进时空过程模拟与预测的新方法[J].测绘学报,2001.30(2):148-155.
    [235]吴大千,王仁卿,高甡等.黄河三角洲农业用地动态变化模拟与情景分析[J].农业工程学报,2010,,26(4):285-289.
    [236]柯新利,邓祥征,刘成武.基于分区异步元胞自动机模型的耕地利用布局优化[J].地理科学进展,2010,29(11):1442-1450.
    [237]景楠.基于多智能体与GIS的城市人口分布预测研究[D].北京:中国科学院[博士学位论文],2007.
    [238]郑燕凤.基于GIS和CA-Markov模型的土地利用变化研究—以招远市为例[D].山东泰安:山东农业大学[硕士学位论文],2009.
    [239]傅立.灰色系统理论及其应用[M].北京:科学技术出版社,1992.
    [240]王国栋,邱镇,任燕峰等.基于PSO优化的直接灰色模型在年用电量预测中的应用[J].水电能源科学,2010,,28(10):148-150.
    [241]刘思峰,党耀国,方志耕.灰色系统理论及应用(第三版)[M].北京:科学出版社,2004.
    [242]Streutker.D.R. A remote sensing study of the urban heat island of Houston[J].Int J Remote Sens,2002,23:2595-2608.
    [243]杨士弘等.城市生态环境学(第二版)[M].北京:科学出版社,2003.
    [244]于志熙.城市生态学[M].北京:中国林业出版社,1991.
    [245]Ahmed Memon Rizwan, Leung Y.C. DENNIS, et al. A review on the generation, determination and mitigation of Urban Heat Island[J].Journal of Environmental Sciences,2008,20(1):120-128.
    [246]Hung,T,U.chihamaD,OchiS,YasuokaY Assessment with satellite data of the urban heat island effects in Asian megacities. International Journal of Applied Earth Observation and Geo-Information,2005,8(1):34-48.
    [247]Kim Y. Baik J. Maximum urban heat island intensity in Seoul[J]. Journalof Applied Meteorology,2002,41:651-659.
    [248]景元书,谢济善.城市热岛效心影响因素分析[J].中国科技信息,2006(21):215-216.
    [249]王喜全,王自发,郭虎.北京“城市热岛”效应现状及特征[J].气候与环境研究,2006,11(5):627-636.
    [250]周明煜,曲绍厚.李玉英等.北京地区热岛和热岛环流特征[J].环境科学.1980.1(5):12-18.
    [251]戊春波,刘红年.朱炎.苏州夏季城市热岛现状及影响因子分析研究[J].气象科学.2009.29(1):84-87.
    [252]刘传年,阴秀菊.西安城市热岛效应及气象因索分析[J].干旱区资源与环境,2008,22(2):87-90.
    [253]余永江,林长城,王宏等.福建省福州市热岛效应与气象条件的关系研究[J].安徽农业科学,2009,37(3):1165-1166.
    [254]佟华,刘辉志,桑建国 等.城市人为热对北京热环境的影响[J].气候与环境研究,2004,9(3):409-420.
    [255]何晓凤,蒋维楣,陈燕等.人为热源对城市边界层结构影响的数值模拟研究[J].地球物理学报,2007,50(1):74-82.
    [256]王喜全,王自发,郭虎.北京“城市热岛”效应现状及特征[J].气候与环境研究,2006,11(5):627-636.
    [257]朱正伟.王猛.城市热岛效应的危害及对策[J].污染防治技术,2009,22(2):94-96.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700