城市化下城市热环境与下垫面关系研究——以郑州市为例
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摘要
随着城市化的发展,城市热岛现象日益增多,严重危害人体健康.基于Landsat 8数据,利用劈窗算法对郑州市地表温度进行反演,分析郑州市热环境空间分布,并对郑州市植被覆盖、不透水面与热环境关系进行定量分析,以此对城市规划建设及热岛效应防治提供借鉴依据.结果表明:(1)郑州市城市热岛效应明显,高温主要集中在三环内,三环与四环间以中温为主,四环以外以低温为主;(2)从各区热环境分布看,中原区、管城区、金水区以高温区、次高温区为主,二七区、惠济区以低温区为主;(3)地表温度与植被覆盖高度负相关,与不透水面高度正相关,两者结合可起到综合降温作用.
With the development of urbanization,the phenomenon of urban heat island is increasing,which seriously endangers human health.Based on Landsat 8,the land surface temperature of Zhengzhou is retrieved by using the split window algorithm.The spatial distribution of thermal environment in Zhengzhou was analyzed,and the relationship between vegetation cover,impervious surface area and thermal environment in Zhengzhou was quantitatively analyzed to provide reference basis for urban planning and construction and heat island effect control.The results show that:(1)The urban heat island effect of Zhengzhou is obvious,and the high temperature is mainly inside the tricyclic ring;(2)Viewing from the distribution of thermal environment in different areas,the Zhongyuan District,Guancheng District and Jinshui District were dominated by high temperature area and secondary high temperature area;(3)The land surface temperature is negatively correlated with vegetation cover and positively correlated with the impermeable surface area,and the combination of the two can play a comprehensive cooling effect.
With the development of urbanization,the phenomenon of urban heat island is increasing,which seriously endangers human health.Based on Landsat 8,the land surface temperature of Zhengzhou is retrieved by using the split window algorithm.The spatial distribution of thermal environment in Zhengzhou was analyzed,and the relationship between vegetation cover,impervious surface area and thermal environment in Zhengzhou was quantitatively analyzed to provide reference basis for urban planning and construction and heat island effect control.The results show that:(1)The urban heat island effect of Zhengzhou is obvious,and the high temperature is mainly inside the tricyclic ring;(2)Viewing from the distribution of thermal environment in different areas,the Zhongyuan District,Guancheng District and Jinshui District were dominated by high temperature area and secondary high temperature area;(3)The land surface temperature is negatively correlated with vegetation cover and positively correlated with the impermeable surface area,and the combination of the two can play a comprehensive cooling effect.
引文
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[2]黄宏涛,吴荣军,王晓云,等.城市热岛效应研究进展[J].河南科学,2015,33(7):1 214-1 220.
[3]杨朝斌,何兴元,张树文,等.基于Landsat 8的城市热岛效应与地表因子关系研究——以长春市为例[J].干旱区资源与环境,2016,30(12):110-115.
[4]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):6 040-6 049.
[5]刘冰冰,曾永年.基于Landsat 8数据的城市群热岛效应分析——长株潭城市群为例[J].山东农业大学学报:自然科学版,2018,49(4):591-597.
[6]吴宝军,雷雅凯,段彦博,等.基于马尔科夫模型的郑州市城市热岛效应分析及预测[J].水土保持研究,2017,24(3):241-245.
[7]段金龙,宋轩,张学雷.基于RS的郑州市城市热岛效应时空演变[J].应用生态学报,2011,22(1):165-170.
[8] ROZENSTEIN O,QIN Z,DERIMIAN Y,et al.Derivation of Land Surface Temperature for Landsat-8TIRS Using a Split Window Algorithm[J].Sensors,2014,14(4):5 768-5 780.
[9]覃志豪,Arnon Karnieli.用NOAA-AVHRR热通道数据演算地表温度的劈窗算法[J].国土资源遥感,2001(2):33-42.
[10]李瑶,潘竟虎.基于Landsat 8劈窗算法与混合光谱分解的城市热岛空间格局分析——以兰州市中心城区为例[J].干旱区地理,2015,38(1):111-119.
[11]宋挺,段峥,刘军志,等.Landsat8数据地表温度反演算法对比[J].遥感学报,2015,19(3):451-464.
[12]覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004(3):28-32,36-41,74.
[13]SOBRINO J A,JIMENEZ-MUNOZ J C,PAOLINI L.Land surface temperature retrieval from Landsat TM 5[J].Remote Sensing of Environment,2004,90(4):434-440.
[14]党青,杨武年.植被覆盖度与城区地表热量的动态变化分析[J].物探化探计算技术,2011,33(5):555-558,465.
[15]陈松林,王天星.等间距法和均值标准差法界定城市热岛的对比研究[J].地球信息科学学报,2009,11(2):145-150.
[16]胡平.基于Landsat 8的成都市中心城区城市热岛效应研究[D].成都:成都理工大学,2015.
[17]李登科,范建忠,王娟.陕西省植被覆盖度变化特征及其成因[J].应用生态学报,2010,21(11):2 896-2 903.
[18]曹瓅,杨昆,洪亮.昆明市主城区不透水面遥感监测及时空变化研究[J].云南师范大学学报:自然科学版,2018,38(1):66-72.
[19]徐涵秋,王美雅.地表不透水面信息遥感的主要方法分析[J].遥感学报,2016,20(5):1 270-1 289.