基于遥感监测的城市热岛研究进展

doi:10.18306/dlkxjz.2016.09.002

Abstract

Abstract:

Rapid and high intensity urbanization is currently occurring in the world, resulting in increasingly more serious urban heat island phenomenon. Urban heat islands have direct and indirect impacts on various eco-environment factors of cities, regions, and the world, which are closely related to the human well-being. Remote sensing method has been widely used for Surface Urban Heat Island (SUHI) monitoring for its obvious advantages, such as wide range, huge amount of information, short observation cycle, among others. Considering the issue that existing studies have not systematically summarized the thermal infrared data sources, monitoring indicators, and the spatiotemporal variation patterns of monitoring results, and the related information needs to be updated, this study conducted a review of progress of surface urban heat island monitoring by remote sensing. First, we presented and classified the thermal infrared remote sensing data sources for the SUHI monitoring by remote sensing in previous studies. Second, we divided the monitoring indicators into three types, including land cover types-driven kind, Land Surface Temperature (LST) pattern-driven kind, and complex kind driven by both land cover types and LST pattern. We introduced the main indicator calculation methods and application cases in detail and analyzed their advantages and disadvantages. We then reviewed the intraannual spatiotemporal change regulation of the SUHI from three aspects, including diurnal variation, nocturnal variation, and comparative variations between day and night. We also considered the patterns of interannual changes. Finally, we proposed several key issues and potential research directions based on the research areas in which conflicting conclusions are found or research needs to be deepened in the existing studies.

Key words: land surface temperature, monitoring indicator, spatiotemporal variation, land use and land cover, surface biophysical parameter, research progress

Yuanzheng LI, Ke YIN, Hongxuan ZHOU, Xiaolin WANG, Dan HU. Progress in urban heat island monitoring by remote sensing[J].PROGRESS IN GEOGRAPHY, 2016, 35(9): 1062-1074.

Figures/Tables 2

Tab.1

Tab.2

Typical monitoring indicators of SUHI"

指标类型	指标	量化方法	传感器、时间范围、文献
土地覆盖类型驱动型	地表温差城市核心区-乡村/K	城市核心区与乡村LST均值的差值。前者指不透水面比例(ISA)大于75%的城区;后者指距离ISA为25%的等值线的45和50 km或15和20 km之间的ISA小于5%的区域。	MODIS;白天和夜间,多年;美国大陆上的超大城市;Imhoff等(2010)MODIS;白天和夜间,多年;全球3000多个城市;Zhang等(2010)
	地表温差城市-乡村/K	行政建成区与乡村LST均值的差值。分别计算城乡地区最高与最低LST的幅度;然后计算城乡幅度的差值。	Landsat-TM和ETM;白天,1天;南充和广安;Dan等(2010)
		4个及其以上多层建筑结构城市像元与其5 km和10 km缓冲区内去除城区和水体像元的LST均值的差值。	MODIS;昼夜,1年;全球;Clinton等(2013)
		对ISA比例大于50%区域进行聚合操作得到的城区与邻近12个一半城区面积缓冲区中最远的3个内去除水体像元后区域LST均值的差值。	MODIS;昼夜,多年;中国32个大城市;Zhou et al (2015)
		全区与乡村气象站处LST的差值。	MODIS;昼夜,多年夏季;伯明翰;Tomlinson等(2012)
		五环路内城区与指定代表乡村区域LST均值的差值。	MODIS;昼夜,多年;北京;王建凯等(2007)
	地表温差城市-郊区/℃	基于城区聚类算法得到的城区与邻近相同面积缓冲区内去除城区及水体像元后区域LST均值的差值。	MODIS;昼夜,多年;全球;Peng等(2011)
		对ISA比例大于50%区域进行聚合操作得到的城区与邻近相同面积缓冲区内去除水体像元后区域LST均值的差值。	MODIS;昼夜,多年;中国32个大城市;Zhou D C等(2014)
	地表温差城市-农田/K	城区与农田LST均值的差值。	MODIS;白天和夜间,同一年中的1月和7月;全球;Jin等(2005) MODIS;白天和夜间,2年;德黑兰;Haashemi等(2016)
	地表温差城市-林地/K	城区与林地LST均值的差值。	MODIS;白天和夜间,同一年中的1月和7月;全球;Jin等(2005)
	地表温差城市-水体/K	城区与水体LST均值的差值。	Landsat-TM;白天,多年中的代表天;珠江三角洲;Chen等(2006) MODIS;白天和夜间,2年;德黑兰;Haashemi等(2016)
地表温度格局驱动型	高斯面积/km²	乡村LST背景值去掉以后基于LST场数据拟合的高斯曲面下的面积。	NOAA-AVHRR;夜间,4月;休斯顿;Streutker(2002) MODIS;白天和夜间,多年;东亚和东南亚的超大城市;Tran等(2006)
	高斯幅度/K	乡村LST背景值去掉以后基于LST场数据拟合的高斯曲面的高度。	NOAA-AVHRR;夜间,4年;休斯顿;Streutker(2003) MODIS;白天和夜间,多年;东亚和东南亚的超大城市;Tran等(2006)
	高斯幅度经验值/K	城区与拟合后的乡村LST的最大差值。	MODIS;白天和夜间,某一年7月及另一年的1月和7月;263个欧洲城市;Schwarz等(2011)
	标准差/K	研究区内LST的标准差。	MODIS;白天和夜间,某一年7月及另一年的1月和7月;263个欧洲城市;Schwarz等(2011)
	幅度/K	基于卷积核技术处理后影像LST场的最大值和最小值的差值。	MODIS;白天和夜间,1年;印第安纳波利斯;Rajasekar等(2009)
	基于地温数理统计的热岛面积/km²	LST高于区域LST均值和一倍标准差之和的区域的面积。	Landsat-ETM+;白天,1天;广东的10个城市;Zhang等(2008)
	地温差值高温区-低温区/℃	高温区(地温大于区域均值和一倍标准差之和的区域)与低温区(地温低于区域均值和一倍标准差之差的区域)LST均值的差值。	Landsat TM和ETM;白天,3年中的3天;珠江三角洲;张金区(2006)
	热岛变异指数	各像元LST与研究区LST均值的差值与研究区LST均值的比值。	CBERS02-IRMSS;白天,1天;北京、无锡;张勇等(2006)
	基于地温空间统计的热岛面积/km²	基于莫兰指数计算的空间相关性及热点分析的统计量来识别高温和低温聚集区。	Landsat Landsat/TM、ETM+;白天,5年中的5天;杭州;张伟等(2015)
	基于剖线突检测的热岛面积/km²和强度/℃	对多条从市中心发射出的地表温度剖线利用诺夫法检测突变点即热岛边界并结合缓冲区分析法计算热岛强度。	MODIS;白天和夜间,多年7月;布加勒斯特;Cheval等(2009)
	亮温级别变化指数	对两期影像的LST单独进行分级;综合考虑各像元两期级别的变化类型和比例;旨在分析SUHI强度的变化趋势。	Landsat-TM和ETM;白天,2年中的2天;庐州;Xu等(2011)
两者复合驱动型	热岛比例指数	综合考虑了LST高于郊区区域中各等级所占的比例及强度;最后给出一个0~1范围内的数值。	Landsat-TM和ETM;白天,2年中的2天;厦门;徐涵秋等(2003)。FY-3A/MERSI和MODIS;白天和夜间,2年;北京;Ye等(2011) Landsat-TM和ETM;白天,3年中的3天;兰州;Pan(2016)
两者复合驱动型	加权平均热岛强度/℃	综合考虑城区内各级别LST所占的比例及其均值与郊区LST均值的差值。	Landsat-TM和ETM;白天,2年中的2天;庐州;Xu等(2011)

Tab.2

References 104

1	白杨, 孟浩, 王敏, 等. 2013. 上海市城市热岛景观格局演变特征研究[J]. 环境科学与技术, 36(3): 196-201.
	[Bai Y, Meng H, Wang M, et al.2013. Spatial and temporal changes of urban thermal landscape pattern in Shanghai[J]. Environmental Science & Technology, 36(3): 196-201.]
2	陈爱莲, 孙然好, 陈利顶. 2012. 基于景观格局的城市热岛研究进展[J]. 生态学报, 32(14): 4553-4565. doi: 10.5846/stxb201106280965
	[Chen A L, Sun R H, Chen L D.2012. Studies on urban heat island from a landscape pattern view: A review[J]. Acta Ecologica Sinica, 32(14): 4553-4565.] doi: 10.5846/stxb201106280965
3	但尚铭, 但玻, 许辉熙, 等. 2011. 环形热岛格局演变过程的遥感分析[J]. 长江流域资源与环境, 20(9): 1125-1130.
	[Dan S M, Dan B, Xu H X, et al.2011. Analysis about evolution of annular urban heat island based on remote sensing[J]. Resources and Environment in the Yangtze Basin, 20(9): 1125-1130.]
4	高建成, 尹泽凯, 张睿. 2015. 快速城镇化地区热岛景观动态变化研究: 以唐山市建成区为例[J]. 干旱区资源与环境, 29(9): 165-170. doi: 10.13448/j.cnki.jalre.2015.311
	[Gao J C, Yin Z K, Zhang R.2015. Spatial and temporal changes of urban thermal landscape pattern in rapid urbanization area: Taking Tangshan urban built-up area as examples[J]. Journal of Arid Land Resources and Environment, 29(9): 165-170.] doi: 10.13448/j.cnki.jalre.2015.311
5	葛荣凤, 王京丽, 张力小, 等. 2016. 北京市城市化进程中热环境响应[J]. 生态学报, 36(19): doi: 10.5846/stxb201409301935.
	[Ge R F, Wang J L, Zhang L X, et al.2016. Impacts of urbanization on the urban thermal environment in Being[J]. Acta Ecologica Sinica, 36(19): doi: 10.5846/stxb201409301935]
6	胡华浪, 陈云浩, 宫阿都. 2005. 城市热岛的遥感研究进展[J]. 国土资源遥感,(3): 5-9, 13. doi: 10.3969/j.issn.1001-070X.2005.03.002
	[Hu H L, Chen Y H, Gong A D.2005. Advances in the application of remotely sensed data to the study of urban heat island[J]. Remote Sensing for Land & Resources,(3): 5-9, 13.] doi: 10.3969/j.issn.1001-070X.2005.03.002
7	李乐, 徐涵秋. 2014. 杭州市城市空间扩展及其热环境变化[J]. 遥感技术与应用, 29(2): 264-272. doi: 10.11873/j.issn.1004-0323.2014.2.0264
	[Li L, Xu H Q.2014. Urban expansion and thermal environment changes in Hangzhou City of East China[J]. Remote Sensing Technology and Application, 29(2): 264-272.] doi: 10.11873/j.issn.1004-0323.2014.2.0264
8	李丽光, 许申来, 王宏博, 等. 2013. 基于源汇指数的沈阳热岛效应[J]. 应用生态学报, 24(12): 3446-3452.
	[Li L G, Xu S L, Wang H B, et al.2013. Urban heat island effect based on urban heat island source and sink indices in Shenyang, Northeast China[J]. Chinese Journal of Applied Ecology, 24(12): 3446-3452.]
9	林奕桐, 叶骏菲, 林开平, 等. 2014. 南宁市热岛效应的遥感研究[J]. 灾害学, 29(4): 192-197. doi: 10.3969/j.issn.1000-811X.2014.04.035
	[Lin Y T, Ye J F, Lin K P, et al.2014. Remote sensing research of heat island effect in Nanning[J]. Journal of Catastrophology, 29(4): 192-197.] doi: 10.3969/j.issn.1000-811X.2014.04.035
10	刘勇洪, 徐永明, 马京津, 等. 2014. 北京城市热岛的定量监测及规划模拟研究[J]. 生态环境学报, 23(7): 1156-1163. doi: 10.3969/j.issn.1674-5906.2014.07.010
	[Liu Y H, Xu Y M, Ma J J, et al.2014. Quantitative assessment and planning simulation of Beijing urban heat island[J]. Ecology and Environmental Sciences, 23(7): 1156-1163.] doi: 10.3969/j.issn.1674-5906.2014.07.010
11	石涛, 杨元建, 马菊, 等. 2013. 基于MODIS的安徽省代表城市热岛效应时空特征[J]. 应用气象学报, 24(4): 484-494. doi: 10.3969/j.issn.1001-7313.2013.04.011
	[Shi T, Yang Y J, Ma J, et al.2013. Spatial temporal characteristics of urban heat island in typical cities of Anhui Province based on MODIS[J]. Journal of Applied Meteorological Science, 24(4): 484-494.] doi: 10.3969/j.issn.1001-7313.2013.04.011
12	孙飒梅, 卢昌义. 2002. 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, 41(1): 66-70. doi: 10.3321/j.issn:0438-0479.2002.01.015
	[Sun S M, Lu C Y.2002. Study on monitoring intensity of urban heat island and taking it as an indicator for urban ecosystem by remote sensing[J]. Journal of Xiamen University: Natural Science, 41(1): 66-70.] doi: 10.3321/j.issn:0438-0479.2002.01.015
13	王建凯, 王开存, 王普才. 2007. 基于MODIS地表温度产品的北京城市热岛(冷岛)强度分析[J]. 遥感学报, 11(3): 330-339. doi: 10.3321/j.issn:1007-4619.2007.03.007
	[Wang J K, Wang K C, Wang P C.2007. Urban heat (or cool) island over Beijing from MODIS land surface temperature[J]. Journal of Remote Sensing, 11(3): 330-339.] doi: 10.3321/j.issn:1007-4619.2007.03.007
14	王天星, 陈松林, 阎广建. 2009. 地表参数反演及城市热岛时空演变分析[J]. 地理科学, 29(5): 697-702.
	[Wang T X, Chen S L, Yan G J.2009. Estimation of land surface parameters and spatio-temporal characteristics of urban heat island[J]. Scientia Geographica Sinica, 29(5): 697-702.]
15	徐涵秋, 陈本清. 2003. 不同时相的遥感热红外图像在研究城市热岛变化中的处理方法[J]. 遥感技术与应用, 18(3): 129-133. doi: 10.3969/j.issn.1004-0323.2003.03.002
	[Xu H Q, Chen B Q.2003. An image processing technique for the study of urban heat island changes using different seasonal remote sensing data[J]. Remote Sensing Technology and Application, 18(3): 129-133.] doi: 10.3969/j.issn.1004-0323.2003.03.002
16	杨何群, 周红妹, 尹球, 等. 2013. FY-3A/MERSI数据在典型大城市热环境监测预报中的应用: 以上海市为例[J]. 测绘通报,(11): 25-28, 32.
	[Yang H Q, Zhou H M, Yin Q, et al.2013. Application of FY-3A/MERSI satellite data for thermal environment monitoring and forecast of typical cities: A case study of Shanghai[J]. Bulletin of Surveying and Mapping,(11): 25-28, 32.]
17	杨丽萍, 孔金玲, 郭玉芳, 等. 2015. 西安城区地表温度的遥感反演与时空演变分析[J]. 兰州大学学报: 自然科学版, 51(3): 388-396. doi: 10.13885/j.issn.0455-2059.2015.03.013
	[Yang L P, Kong J L, Guo Y F, et al.2015. Inversion and temperal-spatial evolution analysis of land surface temperature in urban Xi'an based on remote sensing data[J]. Journal of Lanzhou University: Natural Sciences, 51(3): 388-396.] doi: 10.13885/j.issn.0455-2059.2015.03.013
18	曾胜兰. 2014. 道路建设对成都市热岛效应的影响[J]. 生态环境学报, 23(10): 1622-1627. doi: 10.3969/j.issn.1674-5906.2014.10.009
	[Zeng S L.2014. The effect of road construction on urban heat island effect in Chengdu[J]. Ecology and Environmental Sciences, 23(10): 1622-1627.] doi: 10.3969/j.issn.1674-5906.2014.10.009
19	张好, 徐涵秋, 李乐, 等. 2014. 成都市热岛效应与城市空间发展关系分析[J]. 地球信息科学学报, 16(1): 70-78. doi: 10.3724/SP.J.1047.2014.00070
	[Zhang H, Xu H Q, Li L, et al.2014. Analysis of the relationship between urban heat island effect and urban expansion in Chengdu, China[J]. Journal of Geo-Information Science, 16(1): 70-78.] doi: 10.3724/SP.J.1047.2014.00070
20	张佳华, 侯英雨, 李贵才, 等. 2005. 北京城市及周边热岛日变化及季节特征的卫星遥感研究与影响因子分析[J]. 中国科学: 地球科学, 35(S1): 187-194.
	[Zhang J H, Hou Y Y, Li G C, et al.2005. The diurnal and seasonal characteristics of urban heat island variation in Beijing City and surrounding areas and impact factors based on remote sensing satellite data[J]. Science China: Earth China, 48(S2): 220-229.]
21	张建明, 王鹏龙, 马宁, 等. 2012. 河谷地形下兰州市城市热岛效应的时空演变研究[J]. 地理科学, 32(12): 1530-1537.
	[Zhang J M, Wang P L, Ma N, et al.2012. Spatial-temporal evolution of urban heat island effect in basin valley: A case study of Lanzhou City[J]. Scientia Geographica Sinica, 32(12): 1530-1537.]
22	张金区. 2006. 珠江三角洲地区地表热环境的遥感探测及时空演化研究[D]. 广州: 中国科学院研究生院: 广州地球化学研究所.
	Zhang J Q. 2006. Thermal environment detection in the Pearl River Delta area by remote sensing and analysis of its spatial and temporal evolutions[D]. Guangzhou, China: Graduate Schoolof the Chinese Academy of Sciences: Guangzhou Institute of Geochemistry, CAS.
23	张伟, 蒋锦刚, 朱玉碧. 2015. 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, 26(6): 1840-1846.
	[Zhang W, Jiang J G, Zhu Y B.2015. Spatial-temporal evolution of urban thermal environment based on spatial statistical features[J]. Chinese Journal of Applied Ecology, 26(6): 1840-1846.]
24	张勇, 余涛, 顾行发, 等. 2006. CBERS-02 IRMSS热红外数据地表温度反演及其在城市热岛效应定量化分析中的应用[J]. 遥感学报, 10(5): 789-797. doi: 10.3321/j.issn:1007-4619.2006.05.028
	[Zhang Y, Yu T, Gu X F, et al.2006. Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect[J]. Journal of Remote Sensing, 10(5): 789-797.] doi: 10.3321/j.issn:1007-4619.2006.05.028
25	赵小锋, 叶红. 2009. 热岛效应季节动态随城市化进程演变的遥感监测[J]. 生态环境学报, 18(5): 1817-1821. doi: 10.3969/j.issn.1674-5906.2009.05.042
	[Zhao X F, Ye H.2009. Monitoring the changes of urban heat island seasonal dynamics in the process of urbanization by remote sensing[J]. Ecology and Environmental Sciences, 18(5): 1817-1821.] doi: 10.3969/j.issn.1674-5906.2009.05.042
26	赵颜创, 赵小锋, 旷达. 2014. 宁波城市热岛随城市化演变的多指标综合分析[J]. 生态环境学报, 23(10): 1628-1635. doi: 10.3969/j.issn.1674-5906.2014.10.010
	[Zhao Y C, Zhao X F, Kuang D.2014. Multi-index analysis of heat island dynamics with the process of urbanisation in Ningbo City[J]. Ecology and Environmental Sciences, 23(10): 1628-1635.] doi: 10.3969/j.issn.1674-5906.2014.10.010
27	朱焱, 朱莲芳, 徐永明, 等. 2010. 基于Landsat卫星资料的苏州城市热岛效应遥感分析[J]. 高原气象, 29(1): 244-250.
	[Zhu Y, Zhu L F, Xu Y M, et al.2010. Study on the urban heat island of Suzhou City based on landsat remote sensing data[J]. Plateau Meteorology, 29(1): 244-250.]
28	Adams M P, Smith P L.2014. A systematic approach to model the influence of the type and density of vegetation cover on urban heat using remote sensing[J]. Landscape and Urban Planning, 132: 47-54. doi: 10.1016/j.landurbplan.2014.08.008
29	Chen L, Jiang R, Xiang W N.2016. Surface heat island in Shanghai and its relationship with urban development from 1989 to 2013[J]. Advances in Meteorology, 22: 1-15. doi: 10.1155/2016/9782686
30	Chen X L, Zhao H M, Li P X, et al.2006. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes[J]. Remote Sensing of Environment, 104(2): 133-146. doi: 10.1016/j.rse.2005.11.016
31	Cheval S, Dumitrescu A.2009. The July urban heat island of Bucharest as derived from modis images[J]. Theoretical and Applied Climatology, 96(1-2): 145-153. doi: 10.1007/s00704-008-0019-3
32	Chudnovsky A, Ben-Dor E, Saaroni H.2004. Diurnal thermal behavior of selected urban objects using remote sensing measurements[J]. Energy and Buildings, 36(11): 1063-1074. doi: 10.1016/j.enbuild.2004.01.052
33	Clinton N, Gong P.2013. MODIS detected surface urban heat islands and sinks: Global locations and controls[J]. Remote Sensing of Environment, 134: 294-304. doi: 10.1016/j.rse.2013.03.008
34	Connors J P, Galletti C S, Chow W T L.2013. Landscape configuration and urban heat island effects: Assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona[J]. Landscape Ecology, 28(2): 271-283. doi: 10.1007/s10980-012-9833-1
35	Dan S M, Xu H R, Dan B, et al.2010. Comparison and analysis of research methods for urban heat island effect based on Landsat TM6[C]//Proceedings of the 2010 second IITA international conference on geoscience and remote sensing. Qingdao, China: IEEE: 161-164.
36	de Lucena A J, Filho O C R, França J R D A, et al.2013. Urban climate and clues of heat island events in the metropolitan area of Rio de Janeiro[J]. Theoretical and Applied Climatology, 111(3-4): 497-511. doi: 10.1007/s00704-012-0668-0
37	Dousset B, Gourmelon F.2003. Satellite multi-sensor data analysis of urban surface temperatures and landcover[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 58(1-2): 43-54. doi: 10.1016/S0924-2716(03)00016-9
38	Goldreich Y.1985. The structure of the ground-level heat island in a central business district[J]. Journal of Climate and Applied Meteorology, 24(11): 1237-1244. doi: 10.1175/1520-0450(1985)0242.0.CO;2
39	Grimm N B, Faeth S H, Golubiewski N E, et al.2008. Global change and the ecology of cities[J]. Science, 319: 756-760. doi: 10.1126/science.1150195 pmid: 18258902
40	Haashemi S, Weng Q H, Darvishi A, et al.2016. Seasonal variations of the surface urban heat island in a semi-arid city[J]. Remote Sensing, 8(4): 352. doi: 10.3390/rs8040352
41	Hengl T, Heuvelink G B M, Tadić M P, et al.2012. Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images[J]. Theoretical and Applied Climatology, 107(1-2): 265-277. doi: 10.1007/s00704-011-0464-2
42	Howard L.1833. Climate of London deduced from metrological observations (Vol. 1)[M]. 3rd ed. London, UK: Harvey and Dolton Press.
43	Huang L M, Zhao D H, Wang J Z, et al.2008. Scale impacts of land cover and vegetation corridors on urban thermal behavior in Nanjing, China[J]. Theoretical and Applied Climatology, 94(3-4): 241-257. doi: 10.1007/s00704-007-0359-4
44	Imhoff M L, Zhang P, Wolfe R E, et al.2010. Remote sensing of the urban heat island effect across biomes in the continental USA[J]. Remote Sensing of Environment, 114(3): 504-513. doi: 10.1109/IGARSS.2010.5653907
45	Jin M L, Dickinson R E, Zhang D L.2005. The footprint of urban areas on global climate as characterized by MODIS[J]. Journal of Climate, 18(10): 1551-1565. doi: 10.1175/JCLI3334.1
46	Kanda M.2007. Progress in urban meteorology: A review[J]. Journal of the Meteorological Society of Japan, 85B(S1): 363-383. doi: 10.2151/jmsj.85B.363
47	Klok L, Zwart S, Verhagen H, et al.2012. The surface heat island of Rotterdam and its relationship with urban surface characteristics[J]. Resources, Conservation and Recycling, 64: 23-29. doi: 10.1016/j.resconrec.2012.01.009
48	Knapp S, Kühn I, Stolle J, et al.2010. Changes in the functional composition of a central European urban flora over three centuries[J]. Perspectives in Plant Ecology, Evolution and Systematics, 12(3): 235-244. doi: 10.1007/978-3-8348-9626-1_5
49	Lazzarini M, Marpu P R, Ghedira H.2013. Temperature-land cover interactions: The inversion of urban heat island phenomenon in desert city areas[J]. Remote Sensing of Environment, 130: 136-152. doi: 10.1016/j.rse.2012.11.007
50	Liu H, Weng Q H.2008. Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA[J]. Environmental Monitoring and Assessment, 144(1-3): 199-219. doi: 10.1007/s10661-007-9979-5
51	Liu K, Su H B, Zhang L F, et al.2015. Analysis of the urban heat island effect in Shijiazhuang, China using satellite and airborne data[J]. Remote Sensing, 7(4): 4804-4833. doi: 10.3390/rs70404804
52	Liu K, Zhang X H, Li X K, et al.2014. Multiscale analysis of urban thermal characteristics: Case study of Shijiazhuang, China[J]. Journal of Applied Remote Sensing, 8(1): 083649. doi: 10.1117/1.JRS.8.083649
53	Lowry W P.1977. Empirical estimation of urban effects on climate: A problem analysis[J]. Journal of Applied Meteorology, 16(2): 129-135. doi: 10.1175/1520-0450(1977)0162.0.CO;2
54	Ma Q, Wu J G, He C Y.2016. A hierarchical analysis of the relationship between urban impervious surfaces and land surface temperatures: Spatial scale dependence, temporal variations, and bioclimatic modulation[J]. Landscape Ecology, 31(5): 1139-1153. doi: 10.1007/s10980-016-0356-z
55	Manley G.1958. On the frequency of snowfall in metropolitan England[J]. Quarterly Journal of the Royal Meteorological Society, 84: 70-72. doi: 10.1002/qj.49708435910
56	Memon R A, Leung D Y C, Liu C H.2009. An investigation of urban heat island intensity (UHII) as an indicator of urban heating[J]. Atmospheric Research, 94(3): 491-500. doi: 10.1016/j.atmosres.2009.07.006
57	Meng F, Liu M.2013. Remote-sensing image-based analysis of the patterns of urban heat islands in rapidly urbanizing Jinan, China[J]. International Journal of Remote Sensing, 34(24): 8838-8853. doi: 10.1080/01431161.2013.853895
58	Mostovoy G V, King R L, Reddy K R, et al.2006. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi[J]. GIScience & Remote Sensing, 43(1): 78-110. doi: 10.2747/1548-1603.43.1.78
59	Pan J H.2016. Area delineation and spatial-temporal dynamics of urban heat island in Lanzhou City, China using remote sensing imagery[J]. Journal of the Indian Society of Remote Sensing, 44(1): 111-127.
60	Peng S S, Piao S L, Ciais P, et al.2011. Surface urban heat island across 419 global big cities[J]. Environmental Science & Technology, 46(2): 696-703.
61	Prado D.2010. Characterizing urban heat island phenomenon of four Texas cities using MODIS LST products[D]. San Antonio, TX: The University of Texas.
62	Quan J L, Chen Y H, Zhan W F, et al.2014. Multi-temporal trajectory of the urban heat island centroid in Beijing, China based on a Gaussian volume model[J]. Remote Sensing of Environment, 149: 33-46. doi: 10.1016/j.rse.2014.03.037
63	Quan J L, Zhan W F, Chen Y H, et al.2016. Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands[J]. Journal of Geophysical Research: Atmospheres, 121(6): 2638-2657. doi: 10.1002/2015JD024354
64	Rajasekar U, Weng Q H.2009. Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 64(1): 86-96. doi: 10.1016/j.isprsjprs.2008.05.002
65	Ramdani F, Setiani P.2014. Spatio-temporal analysis of urban temperature in Bandung City, Indonesia[J]. Urban Ecosystems, 17(2): 473-487. doi: 10.1007/s11252-013-0332-1
66	Rao P K.1972. Remote sensing of urban heat islands from an environmental satellite[J]. Bulletin of the American Meteorological Society, 53(7): 647-648.
67	Retalis A, Paronis D, Michaelides S, et al.2013. Study of the August 2010 heat event in Cyprus[M]//Helmis C G, Nastos P T. Advances in meteorology, climatology and atmospheric physics. Berlin & Heidelberg, Germany: Springer, 265-270.
68	Schwarz N, Lautenbach S, Seppelt R.2011. Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures[J]. Remote Sensing of Environment, 115(12): 3175-3186. doi: 10.1016/j.rse.2011.07.003
69	Schwarz N, Schlink U, Franck U, et al.2012. Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators: An application for the city of Leipzig (Germany)[J]. Ecological Indicators, 18: 693-704. doi: 10.1016/j.ecolind.2012.01.001
70	Shen G R, Ibrahim A N, Wang Z J, et al.2015. Spatial-temporal land-use/land-cover dynamics and their impacts on surface temperature in Chongming Island of Shanghai, China[J]. International Journal of Remote Sensing, 36(15): 4037-4053. doi: 10.1080/01431161.2015.1043404
71	Shen H F, Huang L W, Zhang L P, et al.2016. Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China[J]. Remote Sensing of Environment, 172: 109-125. doi: 10.1016/j.rse.2015.11.005
72	Shi B, Tang C S, Gao L, et al.2012. Observation and analysis of the urban heat island effect on soil in Nanjing, China[J]. Environmental Earth Sciences, 67(1): 215-229. doi: 10.1007/s12665-011-1501-2
73	Simon D, Sanchez-Rodriguez R, Seto, K, et al.2005. Science plan: Urbanization and global environmental change[R]. Bonn, Germany: International Human Dimensions Programme: 18-25.
74	Sobrino J A, Oltra-Carrió R, Sòria G, et al.2013. Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing[J]. International Journal of Remote Sensing, 34(9-10): 3177-3192. doi: 10.1080/01431161.2012.716548
75	Streutker D R.2002. A remote sensing study of the urban heat island of Houston, Texas[J]. International Journal of Remote Sensing, 23(13): 2595-2608. doi: 10.1080/01431160110115023
76	Streutker D R.2003. Satellite-measured growth of the urban heat island of Houston, Texas[J]. Remote Sensing of Environment, 85(3): 282-289. doi: 10.1016/S0034-4257(03)00007-5
77	Tomlinson C J, Chapman L, Thornes J E, et al.2011. Remote sensing land surface temperature for meteorology and climatology: A review[J]. Meteorological Applications, 18(3): 296-306. doi: 10.1002/met.287
78	Tomlinson C J, Chapman L, Thornes J E, et al.2012. Derivation of Birmingham's summer surface urban heat island from MODIS satellite images[J]. International Journal of Climatology, 32(2): 214-224. doi: 10.1002/joc.2261
79	Tran H, Uchihama D, Ochi S, et al.2006. Assessment with satellite data of the urban heat island effects in Asian mega cities[J]. International Journal of Applied Earth Observation and Geoinformation, 8(1): 34-48. doi: 10.1016/j.jag.2005.05.003
80	Unger J.2004. Intra-urban relationship between surface geometry and urban heat island: Review and new approach[J]. Climate Research, 27(3): 253-264. doi: 10.3354/cr027253
81	United Nations, Department of Economic and Social Affairs(UN DESA). 2014. World urbanization prospects: The 2014 revision, highlights[R]. New York: United Nations, Department of Economic and Social Affairs: 20.
82	Voogt J A, Oke T R.1997. Complete urban surface temperatures[J]. Journal of Applied Meteorology, 36(9): 1117-1132. doi: 10.1175/1520-0450(1997)0362.0.CO;2
83	Voogt J A, Oke T R.2003. Thermal remote sensing of urban climates[J]. Remote Sensing of Environment, 2003, 86(3): 370-384. doi: 10.1016/S0034-4257(03)00079-8
84	Weng Q H.2009. Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 64(4): 335-344. doi: 10.1016/j.isprsjprs.2009.03.007
85	Weng Q H, Fu P.2014. Modeling diurnal land temperature cycles over Los Angeles using downscaled GOES imagery[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 97: 78-88. doi: 10.1016/j.isprsjprs.2014.08.009
86	Weng Q H, Liu H, Liang B Q, et al.2008. The spatial variations of urban land surface temperatures: Pertinent factors, zoning effect, and seasonal variability[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1(2): 154-166. doi: 10.1109/JSTARS.2008.917869
87	Weng Q H, Yang S H.2004. Managing the adverse thermal effects of urban development in a densely populated Chinese city[J]. Journal of Environmental Management, 70(2): 145-156. doi: 10.1016/j.jenvman.2003.11.006 pmid: 15160740
88	Wong K V, Paddon A, Jimenez A.2013. Review of world urban heat islands: Many linked to increased mortality[J]. Journal of Energy Resources Technology, 135(2): 022101. doi: 10.1115/1.4023176
89	Wong N H, Jusuf S K, Syafii N I, et al.2011. Evaluation of the impact of the surrounding urban morphology on building energy consumption[J]. Solar Energy, 85(1): 57-71. doi: 10.1016/j.solener.2010.11.002
90	Wu C D, Lung S C C, Jan J F.2013. Development of a 3-D urbanization index using digital terrain models for surface urban heat island effects[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 817: 1-11. doi: 10.1016/j.isprsjprs.2013.03.009
91	Wu H, Ye L P, Shi W Z, et al.2014. Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China[J]. International Journal of Applied Earth Observation and Geoinformation, 32: 67-78. doi: 10.1016/j.jag.2014.03.019
92	Xu H X, Chen Y H, Dan S M, et al.2011. Dynamical monitoring and evaluation methods to urban heat island effects based on RS & GIS[J]. Procedia Environmental Sciences, 10: 1228-1237. doi: 10.1016/j.proenv.2011.09.197
93	Xu Y M, Qin Z H, Wan H X.2010. Spatial and temporal dynamics of urban heat island and their relationship with land cover changes in urbanization process: A case study in Suzhou, China[J]. Journal of the Indian Society of Remote Sensing, 38(4): 654-663. doi: 10.1007/s12524-011-0073-7
94	Yang J, Peng G, Zhou J X, et al.2010. Detection of the urban heat island in Beijing using HJ-1B satellite imagery[J]. Science China Earth Science, 53(S1): 67-73. doi: 10.1007/s11430-010-4131-8
95	Ye C H, Liu Y H, Quan W J, et al.2011. Application of urban thermal environment monitoring based on remote sensing in Beijing[J]. Procedia Environmental Sciences, 11: 1424-1433. doi: 10.1016/j.proenv.2011.12.214
96	Yuan F, Bauer M E.2007. Comparison of impervious surface area and Normalized Difference Vegetation Index as indicators of surface urban heat island effects in Landsat imagery[J]. Remote Sensing of Environment, 106(3): 375-386. doi: 10.1016/j.rse.2006.09.003
97	Zakšek K, Oštir K.2012. Downscaling land surface temperature for urban heat island diurnal cycle analysis[J]. Remote Sensing of Environment, 117: 114-124. doi: 10.1016/j.rse.2011.05.027
98	Zehnder J A.2002. 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, 41(9): 971-979. doi: 10.1175/1520-0450(2002)041<0971:SMTIFG>2.0.CO;2
99	Zhan W F, Ju W M, Hai S P, et al.2014. Satellite-derived subsurface urban heat island[J]. Environmental Science & Technology, 48(20): 12134-12140. doi: 10.1021/es50211851 pmid: 25222374
100	Zhang J Q, Wang Y P.2008. Study of the relationships between the spatial extent of surface urban heat islands and urban characteristic factors based on Landsat ETM+ data[J]. Sensors, 8(11): 7453-7468. doi: 10.3390/s8117453 pmid: 3787455
101	Zhang P, Imhoff M L, Wolfe R E, et al.2010. Characterizing urban heat islands of global settlements using MODIS and nighttime lights products[J]. Canadian Journal of Remote Sensing: Journal Canadien de Télédétection, 36(3): 185-196. doi: 10.5589/m10-039
102	Zhou D C, Zhao S Q, Liu S G, et al.2014. Surface urban heat island in China's 32 major cities: Spatial patterns and drivers[J]. Remote Sensing of Environment, 152: 51-61. doi: 10.1016/j.rse.2014.05.017
103	Zhou D H, Zhao S Q, Zhang L X, et al.2015. The footprint of urban heat island effect in China[J]. Scientific Reports, 5: 11160. doi: 10.1038/srep11160
104	Zhou W Q, Qian Y G, Li X M, et al.2014. Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures[J]. Landscape Ecology, 29(1): 153-167. doi: 10.1007/s10980-013-9950-5

平台/传感器	空间分辨率	覆盖周期	过境时间	起始年份	可用热红外波段数
GOES系列/GOES成像器	4 km	~0 d	多个,间隔30 min	1974	双
FY-2/SVISSR	5 km	~0 d	多个,2006年后间隔为15 min	2004	双
MSG系列/SEVIRI	3 km	~0 d	多个,间隔15 min	2005	双
NOAA系列/AVHRR	1.1 km	≤0.25 d	具体见官网^①	1979	双
Terra/MODIS	1 km	0.5 d	~10:30、~22:30	2000	双
Aqua/MODIS	1 km	0.5 d	~01:30、~13:30	2002	双
HJ-1B/IRS	300 m	4 d	~10:00	2008	单
FY-3/MERSI	250 m	5.5 d	~10:45	2008	单
Landsat/TM、ETM+、TIRS^②	60~120 m	16 d	~10:30	1982	单或双
Terra/ASTER	90 m	15 d	按要求	1999	多
CBERS/IRMSS、IRS^③	80~156 m	26 d	~10:30	1999	单
机载	~1 m	按要求	按要求	1985	多
热视频辐射仪	~1.8 mrad	按要求	按要求	1997	多

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