Effects of land surface type changes on urban heat island: a case study of Chaoyang District, Beijing

Li Pengli; Muhammad Amir Siddique; Fan Boqing; Huang Huaguo; Liu Dongyun

doi:10.12171/j.1000-1522.20190045

Journal of Beijing Forestry University > 2020 > 42(3): 99-109. > DOI: 10.12171/j.1000-1522.20190045

Li Pengli, Muhammad Amir Siddique, Fan Boqing, Huang Huaguo, Liu Dongyun. Effects of land surface type changes on urban heat island: a case study of Chaoyang District, Beijing[J]. Journal of Beijing Forestry University, 2020, 42(3): 99-109. DOI: 10.12171/j.1000-1522.20190045

Citation:

PDF (1478 KB)

Effects of land surface type changes on urban heat island: a case study of Chaoyang District, Beijing

1.
School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
2.
School of Forestry, Beijing Forestry University, Beijing 100083, China

More Information

Received Date: January 16, 2019
Revised Date: August 21, 2019
Available Online: January 19, 2020
Published Date: March 30, 2020

Graphical Abstract

Abstract

Abstract

Objective Rapid development of urbanization has changed the nature and structure of underlying surface, which has affected the urban heat balance and led to the gradual spread of the urban heat island effect. Studying the spatial and temporal changes of urban underlying surface and its impact on urban heat islands is of great significance to alleviating urban thermal environment and reducing social and economic losses.
MethodIn this paper, the changes of regional normalized difference vegetation index (NDVI) were calculated and studied by Landsat remote sensing images from 2002 to 2017 in Chaoyang District of Beijing. Based on the atmospheric correction method, the land surface temperature (LST) was retrieved by Landsat thermal infrared band, and the obtained land surface temperature was further normalized. At the same time, using Google panchromatic satellite images from 2002 to 2017, based on DeepLabv3+ network, the underlying surface types in Chaoyang District were classified and its dynamic changes were analyzed by depth learning.
Result(1) The average land surface temperature in Chaoyang District showed rising trend in the past 15 years, and the urban heat island had intensified year by year. By 2017, there was no longer a single heat island center in the area, but it had become a complex mosaic structure and multi-center distribution. (2) The impervious surface area had decreased by 71.02 km², a decrease of 20.98% in 15 years. The total water area decreased by 2.53 km², a decrease of 24.12%; vegetation area increased by 73.54 km², an increase of 56.57%; (3) The correlation analysis between the land surface temperature and the dynamic change of underlying surface type showed that the land surface temperature was positively correlated with the impervious surface area and negatively correlated with the vegetation area. (4) From the perspective of total amount, the total amount of vegetation and water area was negatively correlated with the urban heat island effect in Chaoyang District and increased significantly from 2012 to 2017, but the urban heat island effect did not decrease but increased instead.
ConclusionThe mitigation effect of vegetation and water area on urban heat island effect had gradually become limited under the premise of increasing land use intensity, building density and human activities. Under the current urban development model, the land surface temperature in Chaoyang District will continue to rise and the urban heat island will be further intensified.
- landscape architecture,
- underlying surface,
- land surface temperature,
- urban heat island,
- urbanization

FullText(HTML)

References (30)

References

[1]	彭少麟, 周凯, 叶有华, 等. 城市热岛效应研究进展[J]. 生态环境, 2005, 14(4):574−579. Peng S L, Zhou K, Ye Y H, et al. Research progress in urban heat island[J]. Ecology and Environment, 2005, 14(4): 574−579.
[2]	Oke T R. The distinction between canopy and boundary-layer urban heat islands[J]. Atmosphere, 1976, 14(4): 268−277. doi: 10.1080/00046973.1976.9648422
[3]	Oke T R. Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations[J]. Journal of Climatology, 1981, 1(3): 237−254. doi: 10.1002/joc.3370010304
[4]	Oke T R. Street design and urban canopy layer climate[J]. Energy and Buildings, 1988, 11(1/3): 103−113.
[5]	Oke T R. The heat island of the urban boundary layer: characteristics, causes and effects[M]//Cermak J E, Davenport A G, Plate E J, et al. Wind climate in cities. Dordrecht: Springer, 1995: 81−107.
[6]	Oke T R. Towards better scientific communication in urban climate[J]. Theoretical and Applied Climatology, 2006, 84(1/3): 179−190.
[7]	Roth M, Oke T R, Emery W J. Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology[J]. International Journal of Remote Sensing, 1989, 10(11): 1699−1720. doi: 10.1080/01431168908904002
[8]	Grimmond C S B, Roth M, Oke T R, et al. Climate and more sustainable cities: climate information for improved planning and management of cities (producers/capabilities perspective)[J]. Procedia Environmental Sciences, 2010, 1: 247−274. doi: 10.1016/j.proenv.2010.09.016
[9]	Voogt J A, Oke T R. Thermal remote sensing of urban climates[J]. Remote Sensing of Environment, 2003, 86(3): 370−384. doi: 10.1016/S0034-4257(03)00079-8
[10]	Dousset B. Surface temperature statistics over Los Angeles: the influence of land use[C]//IGARSS’91 remote sensing: global monitoring for earth management. Espoo: IEEE, 1991.
[11]	Gallo K P, Mcnab A L, Karl T R, et al. The use of a vegetation index for assessment of the urban heat island effect[J]. International Journal of Remote Sensing, 1993, 14(11): 2223−2230. doi: 10.1080/01431169308954031
[12]	Nichol J E. High-resolution surface temperature patterns related to urban morphology in a tropical city: a satellite-based study[J]. Journal of Applied Meteorology, 1996, 35(1): 135−146. doi: 10.1175/1520-0450(1996)035<0135:HRSTPR>2.0.CO;2
[13]	Ben-Dor E, Saaroni H. Airborne video thermal radiometry as a tool for monitoring microscale structures of the urban heat island[J]. International Journal of Remote Sensing, 1997, 18(14): 3039−3053. doi: 10.1080/014311697217198
[14]	Hafner J, Kidder S Q. Urban heat island modeling in conjunction with satellite-derived surface/soil parameters[J]. Journal of Applied Meteorology, 1999, 38(4): 448−465. doi: 10.1175/1520-0450(1999)038<0448:UHIMIC>2.0.CO;2
[15]	Yuan F, Bauer M E. 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, 2007, 106(3): 375−386. doi: 10.1016/j.rse.2006.09.003
[16]	杨可明, 周玉洁, 齐建伟, 等. 城市不透水面及地表温度的遥感估算[J]. 国土资源遥感, 2014, 26(2):134−139. doi: 10.6046/gtzyyg.2014.02.22 Yang K M, Zhou Y J, Qi J W, et al. Remote sensing estimating of urban impervious surface area and land surface temperature[J]. Remote Sensing for Land & Resources, 2014, 26(2): 134−139. doi: 10.6046/gtzyyg.2014.02.22
[17]	Xiao R B, Ouyang Z Y, Zheng H, et al. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China[J]. Journal of Environmental Sciences, 2007, 19(2): 250−256. doi: 10.1016/S1001-0742(07)60041-2
[18]	孟宪磊. 不透水面、植被、水体与城市热岛关系的多尺度研究[D]. 上海: 华东师范大学, 2010. Meng X L. Multi-scale relationships between impervious surface, vegetation, water and urban heat island[D]. Shanghai: East China Normal University, 2010.
[19]	Zhou J, Chen Y H, Zhang X, et al. Modelling the diurnal variations of urban heat islands with multi-source satellite data[J]. International Journal of Remote Sensing, 2013, 34(21): 7568−7588. doi: 10.1080/01431161.2013.821576
[20]	李延明, 张济和, 古润泽. 北京城市绿化与热岛效应的关系研究[J]. 中国园林, 2004, 20(1):72−75. doi: 10.3969/j.issn.1000-6664.2004.01.020 Li Y M, Zhang J H, Gu R Z. Research on the relationship between urban greening and the effect of urban heat island[J]. Chinese Landscape Architecture, 2004, 20(1): 72−75. doi: 10.3969/j.issn.1000-6664.2004.01.020
[21]	彭静, 刘伟东, 龙步菊, 等. 北京城市热岛的时空变化分析[J]. 地球物理学进展, 2007, 22(6):1942−1947. doi: 10.3969/j.issn.1004-2903.2007.06.043 Peng J, Liu W D, Long B J, et al. A study of the urban heat island of Beijing based on remote sensing images[J]. Progress in Geophysics, 2007, 22(6): 1942−1947. doi: 10.3969/j.issn.1004-2903.2007.06.043
[22]	葛荣凤, 王京丽, 张力小, 等. 北京市城市化进程中热环境响应[J]. 生态学报, 2016, 36(19):6040−6049. Ge R F, Wang J L, Zhang L X, et al. Impacts of urbanization on the urban thermal environment in Beijing[J]. Acta Ecologica Sinica, 2016, 36(19): 6040−6049.
[23]	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. Cao L Q, Zhang L P, Li P X, et al. Simulation study of influence of change of land surface types on urban heat island[J]. Geomatics and Information Science of Wuhan University, 2008, 33(12): 1229−1232.
[24]	祝善友, 高牧原, 陈亭, 等. 基于ENVI-met模式的城市近地表气温模拟与分析:以南京市部分区域为例[J]. 气候与环境研究, 2017, 22(4):499−508. doi: 10.3878/j.issn.1006-9585.2017.16197 Zhu S Y, Gao M Y, Chen T, et al. Simulation and analysis of urban near-surface air temperature based on ENVI-met model: a case study in some areas of Nanjing[J]. Climatic and Environmental Research, 2017, 22(4): 499−508. doi: 10.3878/j.issn.1006-9585.2017.16197
[25]	Pakarnseree R, Chunkao K, Bualert S. Physical characteristics of Bangkok and its urban heat island phenomenon[J]. Building and Environment, 2018, 143: 561−569. doi: 10.1016/j.buildenv.2018.07.042
[26]	Yin C H, Yuan M, Lu Y P, et al. Effects of urban form on the urban heat island effect based on spatial regression model[J]. Science of the Total Environment, 2018, 634: 696−704. doi: 10.1016/j.scitotenv.2018.03.350
[27]	Xu Y, Ren C, Ma P F, et al. Urban morphology detection and computation for urban climate research[J]. Landscape and Urban Planning, 2017, 167: 212−224. doi: 10.1016/j.landurbplan.2017.06.018
[28]	北京市统计局. 北京区域统计年鉴2018[M]. 北京: 中国统计出版社, 2018. Beijing Municipal Burbeau of Statistics. Beijing Statistical Yearbook 2018[M]. Beijing: China Statistics Press, 2018.
[29]	Sobrino J A, Jiménez-Muñoz J C, Paolin L. Land surface temperature retrieval from LANDSAT TM 5[J]. Remote Sensing of Environment, 2004, 90(4): 434−440. doi: 10.1016/j.rse.2004.02.003
[30]	徐涵秋, 陈本清. 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, 2003, 18(3):129−133. doi: 10.3969/j.issn.1004-0323.2003.03.002 Xu H Q, Chen B Q. An image processing technique for the study of urban heat island changes using different seasonal remote sensing data[J]. Remote Sensing Technology and Application, 2003, 18(3): 129−133. doi: 10.3969/j.issn.1004-0323.2003.03.002

[1]	Wang Xin, Liu Xinyue, Mu Yanmei, Liu Peng, Jia Xin. Changes in vegetation phenology and its responses to climatic factors in the Mu Us Desert[J]. Journal of Beijing Forestry University, 2023, 45(7): 61-75. DOI: 10.12171/j.1000-1522.20220443
[2]	Yu Peiyang, Tong Xiaojuan, Li Jun, Zhang Jingru, Liu Peirong, Xie Han. Simulation analysis on phenology of woody plants in the warm-temperate region of China[J]. Journal of Beijing Forestry University, 2021, 43(11): 28-39. DOI: 10.12171/j.1000-1522.20200367
[3]	Zhang Jingru, Tong Xiaojuan, Meng Ping, Zhang Jinsong, Liu Peirong. Comparative study on phenology in a mountainous plantation in northern China based on vegetation index, chlorophyll fluorescence and carbon flux[J]. Journal of Beijing Forestry University, 2020, 42(11): 17-26. DOI: 10.12171/j.1000-1522.20200113
[4]	Zhang Xu, Song Wenqi, Zhao Huiying, Zhu Liangjun, Wang Xiaochun. Variation of July NDVI recorded by tree-ring index of Pinus koraiensis and Abies nephrolepis forests in the southern Xiaoxing'an Mountains of northeastern China[J]. Journal of Beijing Forestry University, 2018, 40(12): 9-17. DOI: 10.13332/j.1000-1522.20180295
[5]	Zhu Yakun, Qin Shugao, Zhang Yuqing, Zhang Jutao, Shao Yanying, Gao Yan. Vegetation phenology dynamic and its responses to meteorological factor changes in the Mu Us Desert of northern China[J]. Journal of Beijing Forestry University, 2018, 40(9): 98-106. DOI: 10.13332/j.1000-1522.20180020
[6]	YANG Shu-ping, ZHANG De-shun, LI Yue-zhong, JU Rui-ting, LIU Ming. Evaluation system for the resistance of landscape tree to diseases and pests and its application in Shanghai under climate warming[J]. Journal of Beijing Forestry University, 2017, 39(8): 87-97. DOI: 10.13332/j.1000-1522.20160346
[7]	CHEN Jing-ru, DU Yan-jun, ZHANG Yu-hong, PAN Jie, CHEN Fei-fei, DAI Wu-jun, LIU Tong, ZHOU Zhi-qiang. Peak flowering responses to the global warming of woody species in Heilongjiang Province,northeastern China.[J]. Journal of Beijing Forestry University, 2016, 38(11): 50-56. DOI: 10.13332/j.1000-1522.20160186
[8]	WANG Ge, HAN Lin, ZHANG Yu, . Temporal variation and spatial distribution of NDVI in northeastern China.[J]. Journal of Beijing Forestry University, 2012, 34(6): 86-91.
[9]	SONG Fu-qiang, KANG Mu-yi, YANG Peng, CHEN Ya-ru, LIU Yang, XING Kai-xiong.. Comparison and validation of GIMMS, SPOT-VGT and MODIS global NDVI products in the Loess Plateau of northern Shaanxi Province, northwestern China[J]. Journal of Beijing Forestry University, 2010, 32(4): 72-80.
[10]	SONG Yan, JI Jing-jun, ZHU Lin-hong, ZHANG Shi-ying. Characteristics of Asian-African summer monsoon pre-and post-global warming in mid-1980s[J]. Journal of Beijing Forestry University, 2007, 29(2): 24-33.

Cited By

Cited by

Periodical cited type(1)

杨博文，刘凤莲，陈洪敏. 三江并流区森林植被时空演变及驱动因素. 森林工程. 2025(01): 108-125 .

Other cited types(6)

Get Citation

PDF

XML

Article views PDF downloads Cited by(7)

Turn off MathJax

Article Contents

Abstract

References

Effects of land surface type changes on urban heat island: a case study of Chaoyang District, Beijing