地理学报 ›› 2021, Vol. 76 ›› Issue (3): 566-583.doi: 10.11821/dlxb202103006
收稿日期:
2020-03-03
修回日期:
2020-10-18
出版日期:
2021-03-25
发布日期:
2021-05-25
作者简介:
沈中健(1991-), 男, 山东济南人, 博士生, 研究方向为城市热环境。E-mail: 619445503@qq.com
基金资助:
Received:
2020-03-03
Revised:
2020-10-18
Published:
2021-03-25
Online:
2021-05-25
Supported by:
摘要:
基于厦门、漳州、泉州三市1996—2017年的Landsat遥感数据与夜间灯光数据,应用总体耦合态势模型及协调性模型探讨了城镇发展与地表温度的时空耦合规律,并运用标准差椭圆、双变量空间自相关及景观指数分析两者之间的空间响应规律,结果表明:1996—2017年,闽南三市表征城镇发展变化的夜间灯光与地表温度的空间分布呈现出与地形、区位等因素的空间耦合性。三市夜间灯光与地表温度的总体耦合态势不断加强,协调类型逐渐增多;城镇发展早期,夜间灯光对地表温度的影响存在滞后性,在城镇发展后期,夜间灯光则对地表温度的影响呈超前性;夜间灯光与地表温度呈正相关关系,空间溢出效应明显。夜间灯光对地表温度的正向影响逐渐加强,其与地表温度的HH、LL聚集不断扩张;HH集聚连片趋势明显。厦门的城镇发展对地表温度的影响更显著,而在泉州、漳州则较弱。本文可为闽南三市热环境优化提供科学指导。
沈中健, 曾坚. 闽南三市城镇发展与地表温度的空间关系[J]. 地理学报, 2021, 76(3): 566-583.
SHEN Zhongjian, ZENG Jian. Spatial relationship of urban development to land surface temperature in three cities of southern Fujian[J]. Acta Geographica Sinica, 2021, 76(3): 566-583.
表1
1996—2017年闽南三市地表温度与夜间灯光总体耦合分析
年份 | 加权中心距离(km) | 时段 | 加权中心移动方向夹角(º) | ||||
---|---|---|---|---|---|---|---|
厦门 | 漳州 | 泉州 | 厦门 | 漳州 | 泉州 | ||
1996 | 26.160 | 26.371 | 41.259 | 1996—2002 | 178.393 | 153.699 | 47.076 |
2002 | 11.136 | 11.193 | 17.521 | 2002—2007 | 148.105 | 55.592 | 40.772 |
2007 | 5.792 | 12.913 | 17.843 | 2007—2012 | 11.625 | 18.155 | 49.796 |
2012 | 3.666 | 15.213 | 19.256 | 2012—2017 | 21.862 | 24.213 | 40.802 |
2017 | 3.223 | 12.879 | 11.441 | 1996—2017 | 178.337 | 17.430 | 25.995 |
表2
夜间灯光与地表温度协调变化类型划分
类型 | 形成条件 | 意义 |
---|---|---|
协调增进型 | 0.8 < O ≤ 1.0, UR ≈ TR >0 | NTL、LST协调增长, 城镇发展与LST呈协同增进状态 |
拮抗升温超前型 | 0 ≤ O < 0.5, TR > UR | NTL与LST变化协调度较弱, LST上升超前于城镇发展 |
磨合升温超前型 | 0.5 ≤ O < 0.8, TR > UR | NTL与LST变化处于勉强协调, LST上升超前于城镇发展 |
磨合升温滞后型 | 0.5 ≤ O < 0.8, TR < UR | NTL与LST变化处于勉强协调, LST上升滞后于城镇发展 |
拮抗升温滞后型 | 0 ≤ O < 0.5, TR < UR | NTL与LST变化协调度较弱, LST上升滞后于城镇发展 |
协调减退型 | 0.8 <O ≤ 1.0, UR ≈ TR < 0 | NTL、LST协调下降, 城镇发展与LST呈协同减退状态 |
表3
1996—2017年闽南三市夜间灯光与地表温度的相关参数
地区 | 年份 | 相关系数 | 标准差椭圆参数 | |||
---|---|---|---|---|---|---|
中心坐标(NTL, LST) | 方向性 | 离散性 | 方位角(º) | |||
厦门 | 1996 | 0.093*** | (0.239, 0.695) | 1.705 | 0.587 | 85.187 |
2002 | 0.545*** | (0.283, 0.565) | 2.285 | 0.438 | 67.655 | |
2007 | 0.762*** | (0.396, 0.435) | 3.090 | 0.324 | 60.893 | |
2012 | 0.824*** | (0.590, 0.439) | 3.572 | 0.280 | 59.003 | |
2017 | 0.859*** | (0.590, 0.481) | 4.388 | 0.228 | 63.135 | |
漳州 | 1996 | 0.149*** | (0.083, 0.501) | 1.526 | 0.615 | 8.685 |
2002 | 0.321*** | (0.058, 0.533) | 1.694 | 0.590 | 18.936 | |
2007 | 0.423*** | (0.091, 0.459) | 1.620 | 0.617 | 34.274 | |
2012 | 0.661*** | (0.168, 0.537) | 2.925 | 0.342 | 68.511 | |
2017 | 0.665*** | (0.168, 0.531) | 2.493 | 0.401 | 66.010 | |
泉州 | 1996 | 0.386*** | (0.120, 0.531) | 1.511 | 0.662 | 40.253 |
2002 | 0.643*** | (0.128, 0.513) | 2.179 | 0.459 | 51.330 | |
2007 | 0.696*** | (0.168, 0.498) | 2.464 | 0.406 | 54.827 | |
2012 | 0.736*** | (0.285, 0.504) | 3.430 | 0.292 | 68.086 | |
2017 | 0.806*** | (0.285, 0.534) | 3.913 | 0.256 | 65.969 |
表4
1996—2017年闽南三市地表温度与夜间灯光的双变量Moran's I统计值
年份 | 厦门 | 漳州 | 泉州 |
---|---|---|---|
1996 | 0.084(7.573)*** | 0.141(35.654)*** | 0.373(82.939)*** |
2002 | 0.541(45.293)*** | 0.310(80.156)*** | 0.636(128.881)*** |
2007 | 0.746(55.677)*** | 0.409(103.164)*** | 0.687(131.404)*** |
2012 | 0.809(58.262)*** | 0.641(135.030)*** | 0.721(135.594)*** |
2017 | 0.844(61.455)*** | 0.594(145.593)*** | 0.759(154.359)*** |
[1] | Wu Zixuan, Zhang Qiang, Song Changqing, et al. Impacts of urbanization on spatio-temporal variations of temperature over the Pearl River Delta. Acta Geographica Sinica, 2019,74(11):2342-2357. |
[ 吴子璇, 张强, 宋长青, 等. 珠三角城市化对气温时空差异性影响. 地理学报, 2019,74(11):2342-2357.] | |
[2] | Guo G H, Wu Z F, Chen Y B. Complex mechanisms linking land surface temperature to greenspace spatial patterns: Evidence from four southeastern Chinese cities. Science of the Total Environment, 2019,674:77-87. |
[3] | Qiao Zhi, Huang Ningyu, Xu Xinliang, et al. Spatio-temporal pattern and evolution of the urban thermal landscape in metropolitan Beijing between 2003 and 2017. Acta Geographica Sinica, 2019,74(3):475-489. |
[ 乔治, 黄宁钰, 徐新良, 等. 2003—2017年北京市地表热力景观时空分异特征及演变规律. 地理学报, 2019,74(3):475-489.] | |
[4] |
Song X P, Hansen M C, Stehman S V, et al. Global land change from 1982 to 2016. Nature, 2018,560(7720):639-643.
doi: 10.1038/s41586-018-0411-9 pmid: 30089903 |
[5] | Wang Y S, Zhan Q M, Ouyang W L. How to quantify the relationship between spatial distribution of urban waterbodies and land surface temperature? Science of the Total Environment, 2019,671. DOI: 10.1016/j.scitotenv.2021.146056. |
[6] | Shen Zhongjian, Zeng Jian. Spatial relationship of heat island intensity to correlated land surface factors in Xiamen City. Scientia Geographica Sinica, 2020,40(5):842-852. |
[ 沈中健, 曾坚. 厦门市热岛强度与相关地表因素的空间关系研究. 地理科学, 2020,40(5):842-852.] | |
[7] | Yu Chen, Hu Deyong, Cao Shisong, et al. The spatial characteristics and changes of ISP-LST of Beijing in recent 30 years. Geographical Research, 2019,38(9):2346-2356. |
[ 于琛, 胡德勇, 曹诗颂, 等. 近30年北京市ISP-LST空间特征及其变化. 地理研究, 2019,38(9):2346-2356.] | |
[8] | 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. Remote Sensing of Environment, 2018,215:255-267. |
[9] | Zhu X M, Wang X H, Yan D J, et al. Analysis of remotely-sensed ecological indexes' influence on urban thermal environment dynamic using an integrated ecological index: A case study of Xi'an, China. International Journal of Remote Sensing, 2019,40(9):3421-3447. |
[10] | Wang D C, Sun Z C, Chen J H, et al. Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration. PeerJ, 2019,7:e7874. DOI: 10.7717/peerj.7874. |
[11] |
Li B Y, Wang W, Bai L, et al. Effects of spatio-temporal landscape patterns on land surface temperature: A case study of Xi'an city, China. Environmental Monitoring and Assessment, 2018,190(7):419. DOI: 10.1007/s10661-018-6787-z.
doi: 10.1007/s10661-018-6787-z pmid: 29934727 |
[12] | Liu Dan, Yu Chenglong. Urban expansion and its influence on spatio-temporal variation of thermal environment: A case study of Harbin city. Ecology and Environmental Sciences, 2018,27(3):509-517. |
[ 刘丹, 于成龙. 城市扩张对热环境时空演变的影响: 以哈尔滨为例. 生态环境学报, 2018,27(3):509-517.] | |
[13] | Yang Zhiwei, Chen Yingbiao, Wu Zhifeng, et al. The coupling between construction land expansion and urban heat island expansion in Guangdong-Hong Kong-Macao Greater Bay. Journal of Geo-information Science, 2018,20(11):1592-1603. |
[ 杨智威, 陈颖彪, 吴志峰, 等. 粤港澳大湾区建设用地扩张与城市热岛扩张耦合态势研究. 地球信息科学学报, 2018,20(11):1592-1603.] | |
[14] | Yang C, Zhan Q M, Gao S H, et al. How do the multi-temporal centroid trajectories of urban heat island correspond to impervious surface changes: A case study in Wuhan, China. International Journal of Environmental Research and Public Health, 2019,16(20):3865. DOI: 10.3390/ijerph16203865. |
[15] | Willie Y A, Pillay R, Zhou L, et al. Monitoring spatial pattern of land surface thermal characteristics and urban growth: A case study of King Williams using remote sensing and GIS. Earth Science Informatics, 2019,12(4):447-464. |
[16] | Yang Zhiwei, Chen Yingbiao, Wu Zhifeng, et al. Spatial pattern of urban heat island and multivariate modeling of impact factors in the Guangdong-Hong Kong-Macao Greater Bay area. Resources Science, 2019,41(6):1154-1166. |
[ 杨智威, 陈颖彪, 吴志峰, 等. 粤港澳大湾区城市热岛空间格局及影响因子多元建模. 资源科学, 2019,41(6):1154-1166.] | |
[17] | Peng Baofa, Shi Yishao, Wang Hefeng, et al. The impacting mechanism and laws of function of urban heat islands effect: A case study of Shanghai. Acta Geographica Sinica, 2013,68(11):1461-1471. |
[ 彭保发, 石忆邵, 王贺封, 等. 城市热岛效应的影响机理及其作用规律: 以上海市为例. 地理学报, 2013,68(11):1461-1471.] | |
[18] | Min M, Lin C, Duan X J, et al. Spatial distribution and driving force analysis of urban heat island effect based on raster data: A case study of the Nanjing metropolitan area, China. Sustainable Cities and Society, 2019,50:101637. DOI: 10.1016/j.scs.2019.101637. |
[19] | Yang Zhiwei, Chen Yingbiao, Wu Zhifeng, et al. Spatial variability of urban thermal environment based on natural blocks. Progress in Geography, 2019,38(12):1944-1956. |
[ 杨智威, 陈颖彪, 吴志峰, 等. 基于自然区块的城市热环境空间分异性研究. 地理科学进展, 2019,38(12):1944-1956.] | |
[20] | Yao L, Xu Y, Zhang B L. Effect of urban function and landscape structure on the urban heat island phenomenon in Beijing, China. Landscape and Ecological Engineering, 2019,15(4):379-390. |
[21] | Du Zhiwei, Li Xun. Growth or shrinkage: New phenomena of regional development in the rapidly-urbanising Pearl River Delta. Acta Geographica Sinica, 2017,72(10):1800-1811. |
[ 杜志威, 李郇. 珠三角快速城镇化地区发展的增长与收缩新现象. 地理学报, 2017,72(10):1800-1811.] | |
[22] | Chen Yingbiao, Zheng Zihao, Wu Zhifeng, et al. Review and prospect of application of nighttime light remote sensing data. Progress in Geography, 2019,38(2):205-223. |
[ 陈颖彪, 郑子豪, 吴志峰, 等. 夜间灯光遥感数据应用综述和展望. 地理科学进展, 2019,38(2):205-223.] | |
[23] | Luo Qing, Li Xiaojian. The spatial differentiation and influencing factors of urban centers in China based on VIIRS night light. Geographical Research, 2019,38(1):155-166. |
[ 罗庆, 李小建. 基于VIIRS夜间灯光的中国城市中心的分异特征及其影响因素. 地理研究, 2019,38(1):155-166.] | |
[24] | Wang Chao, Kan Aike, Zeng Yelong, et al. Population distribution pattern and influencing factors in Tibet based on random forest model. Acta Geographica Sinica, 2019,74(4):664-680. |
[ 王超, 阚瑷珂, 曾业隆, 等. 基于随机森林模型的西藏人口分布格局及影响因素. 地理学报, 2019,74(4):664-680.] | |
[25] | Feng G Q, Wang K, Yin D M, et al. How to account for endmember variability in spectral mixture analysis of night-time light imagery? International Journal of Remote Sensing, 2020,41(8):3147-3161. |
[26] | Wang Liwei, Feng Changchun. Spatial expansion pattern and its driving dynamics of Beijing-Tianjin-Hebei metropolitan region: Based on nighttime light data. Acta Geographica Sinica, 2016,71(12):2155-2169. |
[ 王利伟, 冯长春. 转型期京津冀城市群空间扩展格局及其动力机制: 基于夜间灯光数据方法. 地理学报, 2016,71(12):2155-2169.] | |
[27] | Su Yongxian, Chen Xiuzhi, Ye Yuyao, et al. The characteristics and mechanisms of carbon emissions from energy consumption in China using DMSP/OLS night light imageries. Acta Geographica Sinica, 2013,68(11):1513-1526. |
[ 苏泳娴, 陈修治, 叶玉瑶, 等. 基于夜间灯光数据的中国能源消费碳排放特征及机理. 地理学报, 2013,68(11):1513-1526.] | |
[28] | Liao W L, Liu X P, Wang D G, et al. The impact of energy consumption on the surface urban heat island in China's 32 major cities. Remote Sensing, 2017,9(3):250. DOI: 10.1007/s00376-014-3222-4. |
[29] | Li L L, Yu T, Zhao L M, et al. Characteristics and trend analysis of the relationship between land surface temperature and nighttime light intensity levels over China. Infrared Physics & Technology, 2019,97:381-390. |
[30] | Lin Zhongli, Xu Hanqiu, Chen Hong. Urban heat island change and its relationship to the urbanization of three major urban agglomerations in China's eastern coastal region. Research of Environmental Sciences, 2018,31(10):1695-1704. |
[ 林中立, 徐涵秋, 陈弘. 我国东部沿海三大城市群热岛变化及其与城市群发展的关系. 环境科学研究, 2018,31(10):1695-1704.] | |
[31] |
Chen S S, Hu D Y, Wong M S, et al. Characterizing spatiotemporal dynamics of anthropogenic heat fluxes: A 20-year case study in Beijing-Tianjin-Hebei region in China. Environmental Pollution, 2019,249:923-931.
doi: 10.1016/j.envpol.2019.03.113 pmid: 30965544 |
[32] | Chen W, Zhang Y, Peng C Y, et al. Evaluation of urbanization dynamics and its impacts on surface heat islands: A case study of Beijing, China. Remote Sensing, 2017,9(5):453. DOI: 10.3390/rs9050453. |
[33] | Yue W Z, Qiu S S, Xu H, et al. Polycentric urban development and urban thermal environment: A case of Hangzhou, China. Landscape and Urban Planning, 2019,189(9):58-70. |
[34] | Fujian Statistical Bureau. Fujian Statistical Yearbook. http://tjj.fujian.gov.cn/, 2017-09-04. |
[ 福建省统计局. 福建统计年鉴. http://tjj.fujian.gov.cn/, 2017-09-04.] | |
[35] | Elvidge C, Baugh K, Kihn E, et al. Mapping city lights with nighttime data from the DMSP Operational Linescan System. Photogrammetric Engineering and Remote Sensing, 1997,63:727-734. |
[36] | Yu Z W, Yao Y W, Yang G Y, et al. Spatiotemporal patterns and characteristics of remotely sensed region heat islands during the rapid urbanization (1995-2015) of Southern China. Science of the Total Environment, 2019,674(7):242-254. |
[37] |
Liu G L, Zhang Q, Li G Y, et al. Response of land cover types to land surface temperature derived from Landsat-5 TM in Nanjing Metropolitan Region, China. Environmental Earth Sciences, 2016,75(20):1386-1397.
doi: 10.1007/s12665-016-6202-4 |
[38] | Lei Jinrui, Chen Zongzhu, Wu Tingtian, et al. Spatio-temporal evolution and interrelationship between thermal environment and landscape patterns of Haikou City, 1989-2015. China Environmental Science, 2019,39(4):1734-1743. |
[ 雷金睿, 陈宗铸, 吴庭天, 等. 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. 中国环境科学, 2019,39(4):1734-1743.] | |
[39] |
Yang Z W, Chen Y B, Qian Q L, et al. The coupling relationship between construction land expansion and high-temperature area expansion in China's three major urban agglomerations. International Journal of Remote Sensing, 2019,40(17):6680-6699.
doi: 10.1080/01431161.2019.1590877 |
[40] | Ding Mengmeng, Cao Weidong, Zhang Dapeng, et al. Study on the measurement and coordination of road traffic and economic development in Anhui province. Resources and Environment in the Yangtze Basin, 2018,27(3):503-513. |
[ 丁萌萌, 曹卫东, 张大鹏, 等. 安徽省公路交通与经济发展水平测度及协调性研究. 长江流域资源与环境, 2018,27(3):503-513.] | |
[41] |
Liu N N, Liu C Z, Xia Y F, et al. Examining the coordination between urbanization and eco-environment using coupling and spatial analyses: A case study in China. Ecological Indicators, 2018,93:1163-1175.
doi: 10.1016/j.ecolind.2018.06.013 |
[42] |
Wang Q R, Mao Z X, Xian L H, et al. A study on the coupling coordination between tourism and the low-carbon city. Asia Pacific Journal of Tourism Research, 2019,24(6):550-562.
doi: 10.1080/10941665.2019.1610002 |
[43] |
Anselin L. Local indicators of spatial association: LISA. Geographical Analysis, 1995,27(2):93-115.
doi: 10.1111/gean.1995.27.issue-2 |
[44] |
Xu Dong, Huang Zhenfang, Huang Rui. The spatial effects of haze on tourism flows of Chinese cities: Empirical research based on the spatial panel econometric model. Acta Geographica Sinica, 2019,74(4):814-830.
doi: 10.11821/dlxb201904014 |
[ 徐冬, 黄震方, 黄睿. 基于空间面板计量模型的雾霾对中国城市旅游流影响的空间效应. 地理学报, 2019,74(4):814-830.] | |
[45] | Shen Zhongjian, Zeng Jian, Liang Chen. Spatial relationship of greenspace landscape pattern with land surface temperature in three cities of southern Fujian. Chinese Journal of Ecology, 2020,39(4):1309-1317. |
[ 沈中健, 曾坚, 梁晨. 闽南三市绿地景观格局与地表温度的空间关系. 生态学杂志, 2020,39(4):1309-1317.] | |
[46] |
Lin Y, Jim C Y, Deng J S, et al. Urbanization effect on spatiotemporal thermal patterns and changes in Hangzhou (China). Building and Environment, 2018,145:166-176.
doi: 10.1016/j.buildenv.2018.09.020 |
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