长江三角洲城市群热环境安全格局及土地利用变化影响研究

doi:10.3724/SP.J.1047.2017.00039

地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (1): 39-49.doi: 10.3724/SP.J.1047.2017.00039

• 新时期中国土地利用/覆被变化时空特征与生态环境效应专栏 • 上一篇下一篇

长江三角洲城市群热环境安全格局及土地利用变化影响研究

韩冬锐¹(), 徐新良^2,*^*(), 李静³, 孙希华¹, 乔治⁴

1. 山东师范大学地理与环境学院,济南 250014
2. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101
3. 环境保护部卫星环境应用中心,北京 100094
4. 天津大学环境科学与工程学院室内空气环境质量控制天津市重点实验室,天津 300072

收稿日期:2016-06-30 修回日期:2016-08-20 出版日期:2017-01-20 发布日期:2017-01-13
作者简介:
作者简介：韩冬锐（1991-）,男,山东烟台人,硕士生,研究方向为土地利用土地覆被变化。E-mail: 1018327881@qq.com
基金资助:
中国科学院重点部署项目（KJZD-EW-TZ-G10）;中国科学院特色研究所培育建设服务项目（TSYJS03）

Study on the Security Pattern of the Heat Environment and the Influence of Land Use Change in the Yangtze River Delta Urban Agglomeration

HAN Dongrui¹(), XU Xinliang^2,^*(), LI Jing³, SUN Xihua¹, QIAO Zhi⁴

1. College of Geography and Environment, Shandong Normal University, Jinan 250014,China
2. State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
3. Satellite Environment Center, Ministry of Environmental Protection,Beijing 100094, China
4. Key Laboratory of Indoor Air Environment Quality Control, School ofEnvironmental Science and Engineering, Tianjin University, Tianjin 300072,China

Received:2016-06-30 Revised:2016-08-20 Online:2017-01-20 Published:2017-01-13
Contact: XU Xinliang

摘要/Abstract

摘要：

城市化进程的加快对区域热环境具有重要影响,热环境的改变会引发一系列生态环境问题,科学地评价城市群热环境安全对于城市发展的规划布局和建设舒适的人居环境具有重要意义。本文利用多期MODIS地表温度数据产品,在构建热环境安全等级分级标准的基础上,对长江三角洲城市群热环境安全格局时空变化特征和土地利用变化的影响进行了探讨。结果表明：① 2015年长江三角洲城市群热环境不安全区域多分布于城市建成区及建成区周围,以南京、上海、杭州和宁波等城市形成的“Z”型区域最明显,临界安全区域多分布于郊区,较安全区域集中分布于长江以北平原区域,安全区域则主要分布于杭州及杭州以南山地、丘陵区,太湖大部分区域以及长江三角洲城市群北部区域;② 2005-2015年长江三角洲城市群热环境不安全区域、临界安全区域、较安全区域和安全区域分别呈现扩张、小幅增长、缩减和先缩减后扩张趋势;③ 土地利用结构中建设用地比例过高和林地比例过低是导致热环境安全等级下降的主要原因,其次,建设用地侵占大量耕地也是导致热环境不安全区域扩张的主要原因。

关键词: 城市化, 城市群, 热环境, 安全格局

Abstract:

The acceleration of urbanization plays an important role in regional heat environment, whose changes may lead to a series of ecological problems. A scientific evaluation on the heat environment of urban agglomeration is essential to urban planning and construction. Based on the construction of a standard of heat environment security levels, we analyzed the spatio-temporal variation of the heat environment security pattern and its causes from land use changes in the Yangtze River Delta urban agglomeration using the MODIS land surface temperature products. The conclusions are as follows: (1) in 2015, the dangerous zones of the heat environment in the Yangtze River Delta urban agglomeration were mostly located in or closed to the urban built-up regions. For example, the “Z” region of Nanjing, Shanghai, Hangzhou, Ningbo and other cities were most obvious. The critical security zones were mostly located in suburbs while the relative security zones were mainly distributed in the northern plains of the Yangtze River. The security zones were mainly located in Hangzhou and its southern mountain and hilly region, most of the region of Tai Lake and the north of the Yangtze River Delta urban agglomerations; (2) the dangerous zone, the critical security zone, the relative security zone and the security zone showed an upward trend, a slight upward trend, a downward trend and a first downward then upward trend, respectively; (3) the primary reason of the decline in security levels of the heat environment was the high ratio of the build-up areas and the low ratio of woodlands. Additionally, the large quantity of croplands occupied by build-up areas was also the reason of the expansion of dangerous zones.

Key words: urbanization, urban agglomeration, the heat environment, security pattern

韩冬锐, 徐新良, 李静, 孙希华, 乔治. 长江三角洲城市群热环境安全格局及土地利用变化影响研究[J]. 地球信息科学学报, 2017, 19(1): 39-49.DOI:10.3724/SP.J.1047.2017.00039

HAN Dongrui,XU Xinliang,LI Jing,SUN Xihua,QIAO Zhi. Study on the Security Pattern of the Heat Environment and the Influence of Land Use Change in the Yangtze River Delta Urban Agglomeration[J]. Journal of Geo-information Science, 2017, 19(1): 39-49.DOI:10.3724/SP.J.1047.2017.00039

图/表 11

图1

图2

表1

地表温度热力等级划分标准

地表温度等级	温度范围
低温	$T normal$ < $T mean$ –1.5 $T std$
次低温	$T mean$ –1.5 $T std$ ≤ $T normal$ < $T mean$ –0.5 $T std$
中温	$T mean$ –0.5 $T std$ ≤ $T normal$ < $T mean$ +0.5 $T std$
次高温	$T mean$ +0.5 $T std$ ≤ $T normal$ < $T mean$ +1.5 $T std$
高温	$T normal$ ≥ $T mean$ +1.5 $T std$

表1

表2

图3

表3

表4

图4

表5

图5

表6

参考文献 37

[1]	Li B C.Problems of Municipal Ecological Environment and the Sustainable Development in China[J].Journal of Arid Land Resources and Environment, 2006,20(2):1-6. doi: 10.1016/S1872-2040(06)60041-8
[2]	Liu J Y, Kuang W H, Zhang Z X, et al.Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s[J].Journal of Geographical Sciences, 2014,69(1):3-14. doi: 10.1007/s11442-014-1082-6
[3]	Rizwan A M, Dennis Y.C. L, Liu C H. A Review on the gerneration, dertermination and mitigation of Urban Heat Island[J].Journal of Environmental Sciences, 2008,20(1):120-128. doi: 10.1016/S1001-0742(08)60019-4
[4]	Oke T R.City size and urban heat island[J].Atmospheric Environment, 1973,7(8):769-779. doi: 10.1016/0004-6981(73)90140-6
[5]	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):715-726. doi: 10.3321/j.issn:0001-5733.2008.03.012
	[ Zhou R W, Jiang W M, He X F.Numerical simulation of the impacts of the thermal effects of urban canopy structure on the formation and the intensity of the urban heat island[J]. Chinese Journal of Geophysics, 2008,51(3):715-726. ] doi: 10.3321/j.issn:0001-5733.2008.03.012
[6]	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):3995-4004. doi: 10.3321/j.issn:1000-0933.2009.07.064
	[ Dai X Y, Zhang L Q, Guo Z Y, et al.Mechanism of formation of urban heat island effect and its spatial pattern in Shanghai[J]. Acta Ecologica Sinica, 2009,29(7):3995-4004. ] doi: 10.3321/j.issn:1000-0933.2009.07.064
[7]	Oke T R.Boundary layer climate[M]. Cambridge: Great Britain at the University Press, 1987:471-508.
[8]	Zhang Y, Bao W J, Yu Q, et al.Study on seasonal variations of the urban heat island and its inte-annual changes in a typical Chinese megacity[J]. Chinese Journal of Geophysics, 2012,55(4):1121-1128. doi: 10.6038/j.issn.0001-5733.2012.04.007
[9]	岳文泽,徐丽华,徐建华.20世纪90年代上海市热环境变化及其社会经济驱动力[J].生态学报,2010,30(1):155-164.
	[ Yue W Z, Xu L H, Xu J H.Thermal environment change and its socio-economic drivers in Shanghai City during the 1990s[J]. Acta Ecologica Sinica, 2010,30(1):155-164. ]
[10]	蒙伟光,张艳霞,李江南,等.WRF/UCM在广州高温天气及城市热岛模拟研究中的应用[J].热带气象学报,2010,26(3):273-282. doi: 10.3969/j.issn.1004-4965.2010.03.003
	[ Meng W G, Zhang Y X, Li J N, et al.Application of WRF/UCM in the simulation of a heat wave event and urban heat island around Guangzhou City[J].Journal of Tropical Meteorology, 2010,26(3):273-282. ] doi: 10.3969/j.issn.1004-4965.2010.03.003
[11]	陈燕,蒋维楣,吴涧,等.利用区域边界层模式对杭州市热岛的模拟研究[J].高原气象,2004,23(4):519-528. doi: 10.3321/j.issn:1000-0534.2004.04.016
	[ Chen Y, Jiang W M, Wu J, et al.A numerical simulation on Hangzhou City heat island using region boundary model[J].Plateau Meteorology, 2004,23(4):519-528. ] doi: 10.3321/j.issn:1000-0534.2004.04.016
[12]	Kuang W H, Chi W F, Shi W J.Spatio-temporal characteristics of intra-urban land cover in the cities of China and USA from 1978 to 2010[J]. Journal of Geographical Sciences, 2014,69(7):883-895. doi: 10.1007/s11442-015-1149-z
[13]	郑祚芳,郑艳,李青春.近30年来城市化进程对北京区域气温的影响[J].中国生态农业学报, 2007,15(4):26-29.
	[ Zheng Z F, Zheng Y, Li Q C. Effect of urbanization on the temperature of Beijing metropolis in recent 30 years[J]. Chinese Journal of Eco-Agriculture, 2007,15(4):26-29. ]
[14]	林学椿,于淑秋,唐国利.北京京城市化进程与热岛强度关系的研究[J].自然科学进展,2005,15(7):882-886. doi: 10.3321/j.issn:1002-008X.2005.07.018
	[ Lin X C, Yu S Q, Tang G L.Study on the relation between urbanization and UHI intensity in Beijing[J]. Journal of Natural Sciences, 2005,15(7):882-886. ] doi: 10.3321/j.issn:1002-008X.2005.07.018
[15]	陈云浩,史培军,李晓兵.不同热力背景对城市降雨(暴雨)的影响(I)——降雨分布的空间差异[J].自然灾害学报,2001,10(2):37-42. doi: 10.3969/j.issn.1004-4574.2001.02.007
	[ Chen Y H, Shi P J, Li X B.Effect of different thermal background on urban rainfall (rainstorm) (I): spatial difference of rainfall distribution[J]. Journal of Natural Disasters, 2001,10(2):37-42. ] doi: 10.3969/j.issn.1004-4574.2001.02.007
[16]	陈燕,蒋维楣,郭文利,等.珠江三角洲地区城市群发展对局地大气污染物扩散的影响[J].环境科学学报,2005,25(5):700-710. doi: 10.3321/j.issn:0253-2468.2005.05.023
	[ Chen Y, Jiang W M, Guo W L, et al.Study on the effect of the city group development in Pearl River Delta on local air pollutant dispersion by numerical modeling[J]. Acta Scientiae Circumstantiae, 2005,25(5):700-710. ] doi: 10.3321/j.issn:0253-2468.2005.05.023
[17]	宫阿都,陈云浩,李京,等.北京市城市热岛与土地利用/覆盖变化的关系研究[J].中国图象图形学报,2007,12(8):1476-1481. doi: 10.3969/j.issn.1006-8961.2007.08.028
	[ Gong A D, Chen Y H, Li J, et al.Study on relationship between urban heat island and urban land use and cover change in Beijing[J]. Journal of Image and Graphics, 2007,12(8):1476-1481. ] doi: 10.3969/j.issn.1006-8961.2007.08.028
[18]	岳文泽,徐丽华.城市土地利用类型及格局的热环境效应研究——以上海市中心城区为例[J].地理科学,2007,27(2):243-248. doi: 10.3969/j.issn.1000-0690.2007.02.020
	[ Yue W Z, Xu L H.Thermal environment effect of urban land use type and pattern: A case study of central area of Shanghai City[J]. Scientia Geographica Sinica, 2007,27(2):243-248. ] doi: 10.3969/j.issn.1000-0690.2007.02.020
[19]	牟雪洁,赵昕奕.珠江三角洲地区地表温度与土地利用类型关系[J].地理研究,2012,31(9):1589-1597. doi: 10.11821/yj2012090005
	[ Mou X J, Zhao X Y.Study on the relationship between surface temperature and land use in Pearl River Delta[J]. Geographical Research, 2012,31(9):1589-1597. ] doi: 10.11821/yj2012090005
[20]	乔治,田光进.北京市热环境时空分异与区划[J].遥感学报,2014,18(3):715-734. doi: 10.11834/jrs.20143030
	[ Qiao Z, Tian G J.Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing[J]. Journal of Remote Sensing, 2014,18(3):725-734. ] doi: 10.11834/jrs.20143030
[21]	王建凯,王开存,王普才.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,2007,11(3):330-339. doi: 10.3321/j.issn:1007-4619.2007.03.007
	[ Wang J K, Wang K C, Wang P C.Urban heat (or Cool) island over Beijing from MODIS land surface temperature[J]. Journal of Remote Sensing, 2007,11(3):330-339. ] doi: 10.3321/j.issn:1007-4619.2007.03.007
[22]	Wan Z M, Dozier J.A generalized Split-window algorithm for retrieving Land-surface temperature from space[J]. IEEE Transactions on Geoscience and Remote Sensing, 1996,34(4):892-905 doi: 10.1109/36.508406
[23]	Wan Z, Zhang Y, Zhang Q, et al.Quality assessment and validation of the MODIS global land surface temperature[J]. International Journal of Remote Sensing, 2004,25(1):261-274 doi: 10.1080/0143116031000116417
[24]	Wang K, Wan Z, Wang P, et al.Evaluation and improvement of the MODIS land surface temperature /emissivity products using ground-based measurements at a semi-desert site on the western Tibetan Plateau[J]. International Journal of Remote Sensing, 2007,28(11):2549-2565 doi: 10.1080/01431160600702665
[25]	Liu J Y, Liu M L, Tian H Q, et al.Spatial and temporal patterns of China's cropland during 1990-2000: Analysis based on Landsat TM data[J]. Remote Sensing of Environment, 2005,98(4):442-456. doi: 10.1016/j.rse.2005.08.012
[26]	Liu J Y, Zhang Z X, Zhuang D F, et al.A study on the spatial-temporal dynamic changes of land-use and driving forces analyses of China in the 1990s[J]. Geographical Research, 2003,22(1):1-12.
[27]	Liu J Y, Buhe A.Study on spatial-temporal feature or modern land-use change in China: Using remote sensing techniques[J]. Quaternary Sciences, 2000,20(3):229-239. doi: 10.3321/j.issn:1001-7410.2000.03.003
[28]	Liu J Y, Zhang Z X, Xu X L, et al.Spatial patterns and driving forces of land use change in China during the early 21st century[J]. Journal of Geographical Sciences, 2010,20(4):483-494. doi: 10.1007/s11442-010-0483-4
[29]	Liu J Y, Liu M L, Zhuang D F, et al.Study on spatial pattern of land-use change in China during 1995-2000[J]. Science in China Series D: Earth Sciences, 2003,46(4):373-384. doi: 10.1360/03yd9033
[30]	肖汉,李志鹏.基于分形理论的北京城市形态结构遥感分析[J].科技导报,2010,28(16):57-62.
	[ Xiao H, Li Z P.Remote sensing analyses of the urban morphology of Beijing based on Fractal Theory[J]. Science and Technology Review, 2010,28(16):57-62. ]
[31]	查良松,王莹莹.一种城市热岛强度的计算方法——以合肥市为例[J].科技导报,2009,27(20):76-79. doi: 10.3321/j.issn:1000-7857.2009.20.018
	[ Zha L S, Wang Y Y.A calculation method for urban heat island intensity: A case study on Hefei city[J]. Science and Technology Review, 2009,27(20):76-79. ] doi: 10.3321/j.issn:1000-7857.2009.20.018
[32]	乔治,田光进.基于MODIS的2001-2012年北京热岛足迹及容量动态监测[J].遥感学报,2015,19(3):476-484. doi: 10.11834/jrs.20154165
	[ Qiao Z, Tian G J.Dynamic monitoring of the footprint and capacity for urban heat island in Beijing between 2001 and 2012 based on MODIS[J]. Journal of Remote Sensing, 2015,19(3):476-484. ] doi: 10.11834/jrs.20154165
[33]	蒋晶,乔治.北京市土地利用变化对地表温度的影响分析[J].遥感信息,2012,27(3):105-111. doi: 10.3969/j.issn.1000-3177.2012.03.018
	[ Jiang J, Qiao Z.Impact analysis of Land Surface Temperature(LST)Land Use Change on Beijing[J]. Remote Sensing Information, 2012,27(3):105-111. ] doi: 10.3969/j.issn.1000-3177.2012.03.018
[34]	康文星,吴耀兴,何介南,等.城市热岛效应的研究进展[J].中南林业科技大学学报, 2011,31(1):70-76. doi: 10.3969/j.issn.1673-923X.2011.01.011
	[ Kang W X, Wu Y X, He J N, et al. Research progress of urban heat island effect[J]. Journal of Central South University of Forestry&Technology, 2011,31(1):70-76. ] doi: 10.3969/j.issn.1673-923X.2011.01.011
[35]	程好好,曾辉,汪自书,等.城市绿地类型及格局特征与地表温度的关系——以深圳特区为例[J].北京大学学报(自然科学版),2009,45(3):495-501. doi: 10.3321/j.issn:0479-8023.2009.03.019
	[ Cheng H H, Zeng H, Wang Z S, et al.Green Space and Land Surface Temperature: A Case Study in Shenzhen Special Economic Zone[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2009,45(3):495-501. ] doi: 10.3321/j.issn:0479-8023.2009.03.019
[36]	高吉喜,张惠远.构建城市生态安全格局从源头防控区域大气污染[J].环境保护,2014,42(6):20-22. doi: 10.3969/j.issn.0253-9705.2014.06.004
	[ Gao J X, Zhang H Y.Constructing urban ecological security pattern to control the regional air pollution at the source[J]. Environment Protection, 2014,42(6):20-22. ] doi: 10.3969/j.issn.0253-9705.2014.06.004
[37]	顾莹,束炯.上海近30年人为热变化及与气温的关系研究[J].长江流域资源与环境,2014,23(8):1105-1110. doi: 10.11870/cjlyzyyhj201408009
	[ Gu Y, Shu J.Variation of anthropogenic heat in Shanghai in recent 30 years and its relation to air temperature[J]. Resources and Environment in the Yangtze Basin, 2014,23(8):1105-1110. ] doi: 10.11870/cjlyzyyhj201408009

安全等级	划分标准
不安全临界安全	区域内的高温区与次高温区热岛足迹内部的中温区、次低温区与低温区
较安全安全	热岛足迹外部的中温区热岛足迹外部的次低温区与低温区

地表温度等级	面积/km²	比例/%
低温	5925.59	5.96
次低温	21 422.25	21.54
中温	36 791.99	36.99
次高温	26 348.76	26.49
高温	8969.99	9.02

区域	2005年			2010年			2015年
区域	面积		比例		面积	比例	面积	比例
不安全	23 278.62	23.41		29 361.92	29.52		35 222.33	35.41
临界安全	5059.76	5.09		6578.00	6.61		7196.30	7.24
较安全	46 319.21	46.57		39 262.04	39.48		31 583.56	31.76
安全	24 801.00	24.93		24 256.63	24.39		25 456.40	25.59

城市	2005-2010年变化面积					2010-2015年变化面积					2005-2015年变化比例
城市	不安全		临界安全		较安全	安全	不安全	临界安全	较安全	安全	不安全	临界安全	较安全	安全
上海	350.84	19.66	-521.60	151.10		878.17	22.55	-658.45	-242.27		21.13	0.73	-20.29	-1.57
南京	752.39	429.49	-1043.21	-138.68		-32.66	263.77	-312.07	80.96		11.78	11.35	-22.18	-0.94
无锡	356.02	204.92	-413.97	-146.96		154.53	27.46	-99.35	-82.65		11.60	5.28	-11.66	-5.22
常州	421.22	158.34	-467.79	-111.77		0.74	50.34	-118.45	67.38		10.23	5.06	-14.22	-1.08
苏州	458.47	292.88	-495.73	-255.63		1013.61	-38.84	-681.22	-293.55		19.30	3.33	-15.43	-7.20
南通	-1574.12	200.78	-509.18	1882.53		1382.36	-247.83	846.66	-1981.19		-2.39	-0.59	4.21	-1.23
扬州	274.26	183.18	-861.06	403.62		107.58	47.85	359.69	-515.12		5.90	3.57	-7.74	-1.72
镇江	302.20	-1.03	-231.82	-69.34		93.35	100.78	-317.04	122.91		11.49	2.90	-15.94	1.56
泰州	112.81	107.63	-1018.37	797.93		48.53	154.13	32.47	-235.14		2.94	4.77	-17.98	10.26
杭州	1613.45	-232.86	712.03	-2092.62		-470.62	184.19	-3348.07	3634.49		7.45	-0.32	-17.19	10.06
宁波	446.05	-39.33	-303.23	-103.49		561.44	-25.86	-523.05	-12.52		13.44	-0.87	-11.02	-1.55
绍兴	875.55	-70.38	-12.42	-792.75		318.29	203.33	-1402.99	881.37		15.60	1.74	-18.49	1.16
湖州	978.01	91.07	-719.27	-349.81		48.30	50.87	-390.17	290.99		19.40	2.68	-20.97	-1.11
嘉兴	1216.04	-8.28	-1172.57	-35.19		287.35	0.03	-247.39	-40.00		42.14	-0.23	-39.80	-2.11
台州	-498.83	185.25	49.68	263.91		1425.83	-183.67	-821.85	-420.32		11.31	0.02	-9.42	-1.91
舟山	-1.03	-3.10	-48.64	52.78		43.61	9.19	2.78	-55.58		10.11	1.44	-10.89	-0.66

区域	耕地-林地	耕地-草地	耕地-水域	耕地-建设	林地-耕地	林地-建设	草地-建设	水域-建设	建设-耕地
不安全	3.57	0.24	2.95	49.67	3.33	2.07	0.12	2.07	9.41
临界安全	0.78	0.06	1.18	4.48	0.67	0.39	0.04	0.33	1.32
较安全	5.15	0.22	3.31	11.94	4.92	0.87	0.11	0.55	5.68
安全	3.35	0.12	2.81	2.09	3.13	0.70	0.07	0.18	1.20
合计	12.85	0.64	10.25	68.18	12.05	4.03	0.34	3.13	17.61

长江三角洲城市群热环境安全格局及土地利用变化影响研究

Study on the Security Pattern of the Heat Environment and the Influence of Land Use Change in the Yangtze River Delta Urban Agglomeration

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