1989～2015年海口城市热环境与景观格局的时空演变及其相互关系
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摘要
利用1989,1999,2007和2015年的4期Landsat5TM/8OLI-TIRS遥感数据,综合应用遥感、地理信息系统、景观生态学和统计分析相结合的方法,探讨海口城市热环境与景观格局的时空演变关系.结果显示,1989～2015年间,海口城市陆地表面温度(LST)总体呈逐步上升的趋势.城市热岛面积逐步扩大,空间质心向西南方向转移,且在2007年以后转移速率明显加快;冷岛质心则向东部生态核心区转移.城市LST较高的区域往往与不透水表面分布一致,较低的LST与绿地或水体分布一致.4期绿地的平均LST比不透水表面低4.17℃,其中2015年绿地景观类型百分比(PLAND)每增加10%导致LST下降0.57℃;不透水表面每增加10%,LST则上升0.78℃.不同时期绿地和不透水表面的平均LST与PLAND、最大斑块指数(LPI)、聚集度指数(AI)均表现为一致的极显著相关关系,且相关性逐年增强,其中绿地为负相关,不透水表面为正相关;景观斑块的大小和聚集程度对城市LST有较大影响.研究结果可以拓展对城市热环境与景观格局时空演变关系的认识,为城市规划和决策者提供参考.
Landsat 5 TM/8 OLI-TIRS thermal infrared remote sensing data from 1989, 1999, 2007 and 2015 were used here to explore the spatio-temporal evolution and interrelationship between the thermal environment and landscape patterns in Haikou, China.Through the integration of remote sensing, geographic information systems, landscape ecology and statistical analysis methods, our results showed that the land surface temperature(LST) of Haikou City showed a gradual increase from 1989 to 2015. The area of urban heat island gradually expanded, the spatial center of mass shifted southwest, and the transfer rate accelerated significantly after2007. In addition, the center of cold island mass was transferred to the eastern eco-centric area. The distribution of high land surface temperature in the city correlates with impervious surface, while the low LST correlated with the distribution of green land or water.The mean LST of green space was 4.17℃ lower than that of impervious surface. In 2015, 10% increase in percentage composition of landscape(PLAND) of green space caused a 0.57℃ loss in LST, whereas a 10% increase in PLAND of impervious surface caused a 0.78℃ increase in LST. The mean LST of green space and impervious surface in different years was consistently and highly significantly correlated with PLAND, largest patch index(LPI) and aggregation index(AI). In fact, the correlation grew stronger over the years. The correlation of LST with green space was negative, while it was positive for impervious surface. The size and degree of aggregation of landscape patches had great influence on urban LST. These results expand our understanding of the spatio-temporal evolution and interrelationship between urban thermal environment and landscape patterns, as well as provide a reference for urban planners and policy makers.
Landsat 5 TM/8 OLI-TIRS thermal infrared remote sensing data from 1989, 1999, 2007 and 2015 were used here to explore the spatio-temporal evolution and interrelationship between the thermal environment and landscape patterns in Haikou, China.Through the integration of remote sensing, geographic information systems, landscape ecology and statistical analysis methods, our results showed that the land surface temperature(LST) of Haikou City showed a gradual increase from 1989 to 2015. The area of urban heat island gradually expanded, the spatial center of mass shifted southwest, and the transfer rate accelerated significantly after2007. In addition, the center of cold island mass was transferred to the eastern eco-centric area. The distribution of high land surface temperature in the city correlates with impervious surface, while the low LST correlated with the distribution of green land or water.The mean LST of green space was 4.17℃ lower than that of impervious surface. In 2015, 10% increase in percentage composition of landscape(PLAND) of green space caused a 0.57℃ loss in LST, whereas a 10% increase in PLAND of impervious surface caused a 0.78℃ increase in LST. The mean LST of green space and impervious surface in different years was consistently and highly significantly correlated with PLAND, largest patch index(LPI) and aggregation index(AI). In fact, the correlation grew stronger over the years. The correlation of LST with green space was negative, while it was positive for impervious surface. The size and degree of aggregation of landscape patches had great influence on urban LST. These results expand our understanding of the spatio-temporal evolution and interrelationship between urban thermal environment and landscape patterns, as well as provide a reference for urban planners and policy makers.
引文
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[34]Myint,S W,Brazel A,Okin G,et al.Combined effects of impervious surface and vegetation cover on air temperature variations in a rapidly expanding desert city[J].GIS Science&Remote Sensing,2010,47(3):301-320.
[35]Kong F H,Nakagoshi N.Spatial-temporal gradient analysis of urban green spaces in Jinan,China[J].Landscape and Urban Planning,2006,78(3):147-164.
[36]Chen A L,Yao L,Sun R H,et al.How many metrics are required to identify the effects of the landscape pattern on land surface temperature?[J].Ecological Indicators,2014,45:424-433.
[37]傅伯杰,陈利顶,马克明,等.景观生态学原理及应用[M].北京:科学出版社,2011:86-92.Fu B J,Chen L D,Ma K M,et al.Principles and applications of landscape ecology[M].Beijing:Science Press,2011:86-92.
[38]Sun Q Q,Wu Z F,Tan J J.The relationship between land surface temperature and land use/land cover in Guangzhou,China[J].Environmental Earth Sciences,2012,65(6):1687-1694.
[39]王蕾,张树文,姚允龙.绿地景观对城市热环境的影响--以长春市建成区为例[J].地理研究,2014,33(11):2095-2104.Wang L,Zhang S W,Yao Y L.The impacts of green landscape on urban thermal environment:A case study in Changchun city[J].Geographical Research,2014,33(11):2095-2104.
[40]Rogan J,Ziemer M,Martin D G,et al.The impact of tree cover loss on land surface temperature:a case study of central Massachusetts using Landsat Thematic Mapper thermal data[J].Applied Geography,2013,45:49-57.
[41]唐泽,郑海峰,任志彬,等.城市地表热力景观格局时空演变--以长春市为例[J].生态学报,2017,37(10):3264-3273.Tang Z,Zheng H F,Ren Z B,et al.Spatial and temporal changes to urban surface thermal landscape patterns:a case study of Changchun City[J].Acta Ecologica Sinica,2017,37(10):3264-3273.
[42]Peng J,Jia J L,Liu Y X,et al.Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas[J].Remote Sensing of Environment,2018,215:255-267.
[43]徐永明,刘勇洪.基于TM影像的北京市热环境及其与不透水面的关系研究[J].生态环境学报,2013,22(4):639-643.Xu Y M,Liu Y H.Study on the thermal environment and its relationship with impervious surface in Beijing city using TM image[J].Ecology and Environmental Sciences,2013,22(4):639-643.
[2]Zhou D C,Bonafoni S,Zhang L X,et al.Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China[J].Science of the Total Environment,2018,628-629:415-429.
[3]Grimm N B,Faeth S H,Golubiewski N E,et al.Global change and the ecology of cities[J].Science,2008,319(5864):756-760.
[4]Greenea G S,Kedronb P J.Beyond fractional coverage:A multilevel approach to analyzing the impact of urban tree canopy structure on surface urban heat islands[J].Applied Geography,2018,95:45-53.
[5]Deng J S,Wang K,Hong Y,et al.Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization[J].Landscape and Urban Planning,2009,92(3/4):187-198.
[6]姚远,陈曦,钱静.城市地表热环境研究进展[J].生态学报,2018,38(3):1134-1147.Yao Y,Chen X,Qian J.Research progress on the thermal environment of the urban surfaces[J].Acta Ecologica Sinica,2018,38(3):1134-1147.
[7]Voogt J A,Oke T R.Thermal remote sensing of urban climates[J].Remote Sensing of Environment,2003,86(3):370-384.
[8]Pan J H.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,2016,44(1):111-127.
[9]Sultana S,Satyanarayana A N V.Urban heat island intensity during winter over metropolitan cities of India using remote-sensing techniques:impact of urbanization[J].International Journal of Remote Sensing,2018,39(20):6692-6730.
[10]Yu Z W,Guo X Y,Zeng Y X,et al.Variations in land surface temperature and cooling efficiency of green space in rapid urbanization:The case of Fuzhou city,China[J].Urban Forestry&Urban Greening,2018,29:113-121.
[11]Li Z L,Tang B H,Wu H,et al.Satellite-derived land surface temperature:current status and perspectives[J].Remote Sensing of Environment,2013,131:14-37.
[12]Lazzarini M,Marpu P R,Ghedira H.Temperature-land cover interactions:the inversion of urban heat island phenomenon in desert city areas[J].Remote Sensing of Environment,2013,130:136-152.
[13]Mohan M,Kandya A.Impact of urbanization and land-use/land cover change on diurnal temperature range:a case study of tropical urban airshed of India using remote sensing data[J].Science of the Total Environment,2015,506-507:453-465.
[14]Amiri R,Weng Q H,Alimohammadi A,et al.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(12):2606-2617.
[15]Li X M,Zhou W Q,Ouyang Z Y,et al.Spatial pattern of green space affects land surface temperature:evidence from the heavily urbanized Beijing metropolitan area,China[J].Landscape Ecology,2012,27(6):887-898.
[16]Maimaitiyiming M,Ghulam A,Tiyip T,et al.Effects of green space spatial pattern on land surface temperature:implications for sustainable urban planning and climate change adaptation[J].ISPRSJournal of Photogrammetry and Remote Sensing,2014,89:59-66.
[17]Morabito M,Crisci A,Messeri A,et al.The impact of built-up surfaces on land surface temperatures in Italian urban areas[J].Science of The Total Environment,2016,551-552:317-326.
[18]Connors J P,Galletti C S,Chow W.Landscape configuration and urban heat island effects:Assessing the relationship between landscape characteristics and land surface temperature in Phoenix,Arizona[J].Landscape Ecology,2013,28(2):271-283.
[19]Kayet N,Pathak K,Chakrabarty A,et al.Spatial impact of land use/land cover change on surface temperature distribution in Saranda Forest,Jharkhand[J].Modeling Earth Systems and Environment,2016,2:127.
[20]黄丽明,陈健飞.城市景观格局时空特征的热环境效应研究--以广州市花都区为例[J].自然资源学报,2015,30(3):480-490.Huang L M,Chen J F.Study on thermal environment effect of urban landscape pattern:A case study on Huadu district,Guangzhou[J].Journal of Natural Resources,2015,30(3):480-490.
[21]黄木易,岳文泽,何翔.巢湖流域地表热环境与景观变化相关分析及其尺度效应[J].中国环境科学,2017,37(8):3123-3133.Huang M Y,Yue W Z,He X.Correlation analysis between land surface thermal environment and landscape change and its scale effect in Chaohu Basin[J].China Environmental Science,2017,37(8):3123-3133.
[22]Estoque R C,Murayama Y,Myint S W.Effects of landscape composition and pattern on land surface temperature:An urban heat island study in the megacities of Southeast Asia[J].Science of the Total Environment,2017,577:349-359.
[23]Myint S W,Wentz E A,Brazel A J,et al.The impact of distinct anthropogenic and vegetation features on urban warming[J].Landscape Ecology,2013,28(5):959-978.
[24]Weng Q H,Lu D H,Schubring J.Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies[J].Remote Sensing of Environment,2004,89(4):467-483.
[25]Hamada S,Ohta T.Seasonal variations in the cooling effect of urban green areas on surrounding urban areas[J].Urban Forestry&Urban Greening,2010,9(1):15-24.
[26]Zhou W Q,Huang G L,Cadenasso M.Does spatial configuration matter?Understanding the effects of land cover pattern on land surface temperature in urban landscapes[J].Landscape and Urban Planning,2011,102(1):54-63.
[27]Zhang X Y,Zhong T Y,Feng X Z,et al.Estimation of the relationship between vegetation patches and urban land surface temperature with remote sensing[J].International Journal of Remote Sensing,2009,30(8):2105-2118.
[28]Liu G L,Zhang Q,Li G Y,et al.Response of land cover types to land surface temperature derived from Landsat-5TM in Nanjing Metropolitan Region,China[J].Environmental Earth Sciences,2016,75(20):1386.
[29]Sobrino J A,Jimenez-Munoz J C,Paolini L.Land surface temperature retrieval from LANDSAT TM5[J].Remote Sensing of Environment,2004,90(4):434-440.
[30]Artis D A,Carnahan W H.Survey of emissivity variability in thermography of urban areas[J].Remote Sensing of Environment,1982,12(4):313-329.
[31]Abutaleb K,Ngie A,Darwish A,et al.Assessment of urban heat island using remotely sensed imagery over Greater Cairo,Egypt[J].Advances in Remote Sensing,2015,4(4):35-47.
[32]钱敏蕾,徐艺扬,李响,等.上海市城市化进程中热环境响应的空间评价[J].中国环境科学,2015,35(2):624-633.Qian M L,Xu Y Y,Li X.An assessment of spatial thermal environmental response to rapid urbanization of Shanghai[J].China Environmental Science,2015,35(2):624-633.
[33]孟丹,王明玉,李小娟,等.京沪穗三地近十年夜间热力景观格局演变对比研究[J].生态学报,2013,33(5):1545-1558.Meng D,Wang M Y,Li X J,et al.The dynamic change of the thermal environment landscape patterns in Beijing,Shanghai and Guangzhou in the recent past decade[J].Acta Ecologica Sinica,2013,33(5):1545-1558.
[34]Myint,S W,Brazel A,Okin G,et al.Combined effects of impervious surface and vegetation cover on air temperature variations in a rapidly expanding desert city[J].GIS Science&Remote Sensing,2010,47(3):301-320.
[35]Kong F H,Nakagoshi N.Spatial-temporal gradient analysis of urban green spaces in Jinan,China[J].Landscape and Urban Planning,2006,78(3):147-164.
[36]Chen A L,Yao L,Sun R H,et al.How many metrics are required to identify the effects of the landscape pattern on land surface temperature?[J].Ecological Indicators,2014,45:424-433.
[37]傅伯杰,陈利顶,马克明,等.景观生态学原理及应用[M].北京:科学出版社,2011:86-92.Fu B J,Chen L D,Ma K M,et al.Principles and applications of landscape ecology[M].Beijing:Science Press,2011:86-92.
[38]Sun Q Q,Wu Z F,Tan J J.The relationship between land surface temperature and land use/land cover in Guangzhou,China[J].Environmental Earth Sciences,2012,65(6):1687-1694.
[39]王蕾,张树文,姚允龙.绿地景观对城市热环境的影响--以长春市建成区为例[J].地理研究,2014,33(11):2095-2104.Wang L,Zhang S W,Yao Y L.The impacts of green landscape on urban thermal environment:A case study in Changchun city[J].Geographical Research,2014,33(11):2095-2104.
[40]Rogan J,Ziemer M,Martin D G,et al.The impact of tree cover loss on land surface temperature:a case study of central Massachusetts using Landsat Thematic Mapper thermal data[J].Applied Geography,2013,45:49-57.
[41]唐泽,郑海峰,任志彬,等.城市地表热力景观格局时空演变--以长春市为例[J].生态学报,2017,37(10):3264-3273.Tang Z,Zheng H F,Ren Z B,et al.Spatial and temporal changes to urban surface thermal landscape patterns:a case study of Changchun City[J].Acta Ecologica Sinica,2017,37(10):3264-3273.
[42]Peng J,Jia J L,Liu Y X,et al.Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas[J].Remote Sensing of Environment,2018,215:255-267.
[43]徐永明,刘勇洪.基于TM影像的北京市热环境及其与不透水面的关系研究[J].生态环境学报,2013,22(4):639-643.Xu Y M,Liu Y H.Study on the thermal environment and its relationship with impervious surface in Beijing city using TM image[J].Ecology and Environmental Sciences,2013,22(4):639-643.