福州主城区热岛效应与不透水面的关系及时空变化分析
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摘要
城市气候环境和下垫面性质对人类健康具有重要的影响.为了研究福州主城区不透水面与城市热岛效应之间的时空变化关系,本研究以1994年、2000年、2009年、2018年4期Landsat遥感影像数据作为数据源,基于线性光谱分解原理提取福州主城区不同时期不透水面信息和利用单窗算法反演出地表温度,分别从空间维度和时间维度进行对比分析,结果表明:不透水面与城市热岛的分布具有显著的正相关关系,R2达到0. 70以上. 1994年-2018年,福州主城区不透水面增加了89. 58 km2,年平均增速为3. 73 km2/年.就福州主城区而言,不透水面丰度每增加0. 1,可导致局部地表温度上升1℃以上,并且不透水面的空间分布与热岛的分布特征具有较强的一致性.
Urban climate and underlying surface properties have important impacts on human health. In order to study the spatial-temporal relationship between impervious surface and urban heat island effect in Fuzhou,the Landsat remote sensing image data of 1994,2000,2009 and 2018 were used as data sources to extract impervious surface information in Fuzhou urban area at different periods based on linear spectral decomposition principle and to invert it using single window algorithm. The results show that: There is a significant positive correlation between the impermeable surface and the distribution of urban heat island,R2 is above 0. 70. From 1994 to 2018,the impervious surface of Fuzhou's main urban area increased by 89. 58 km2,with an average annual growth rate of 3. 73 km2 a year. For the main urban area of Fuzhou,every 0. 1 increase of impervious surface abundance can cause the local surface temperature to rise by more than 1 degree celsius,and the spatial distribution of impervious surface has a strong consistency with the distribution characteristics of heat island.
Urban climate and underlying surface properties have important impacts on human health. In order to study the spatial-temporal relationship between impervious surface and urban heat island effect in Fuzhou,the Landsat remote sensing image data of 1994,2000,2009 and 2018 were used as data sources to extract impervious surface information in Fuzhou urban area at different periods based on linear spectral decomposition principle and to invert it using single window algorithm. The results show that: There is a significant positive correlation between the impermeable surface and the distribution of urban heat island,R2 is above 0. 70. From 1994 to 2018,the impervious surface of Fuzhou's main urban area increased by 89. 58 km2,with an average annual growth rate of 3. 73 km2 a year. For the main urban area of Fuzhou,every 0. 1 increase of impervious surface abundance can cause the local surface temperature to rise by more than 1 degree celsius,and the spatial distribution of impervious surface has a strong consistency with the distribution characteristics of heat island.
引文
[1]李延明,徐佳,张济和,等.城市绿化对北京城市热岛效应的缓解作用[J].北京园林,2002,18(4):12-16.
[2]薛志成.城市热岛效应威胁人类健康[J].安全与健康,2002(13):15-16.
[3]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.
[4]徐涵秋.城市不透水面与相关城市生态要素关系的定量分析[J].生态学报,2009,29(5):2456-2462.
[5]邹春城.基于不透水面百分比,景观指数与土地利用类型的福州市城市热环境分析[D].福州:福建师范大学,2014.
[6] RIDD M K. Exploring a V-I-S(vegetation-impervious surface-soil)model for urban ecosystem analysis through remote sensing:comparative anatomy for cities[J]. International Journal of Remote Sensing,1995,16(12):2165-2185.
[7] CARLSON T N,ARTHUR S T. The impact of land use-land cover changes due to urbanization on surface microclimate and hydrology:a satellite perspective[J]. Global and Planetary Change,2000,25(1-2):49-65.
[8] YUANG 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.
[9] WU C,MURRAY A T. Erface stimating impervious sudistribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84:493-505.
[10]徐涵秋.一种快速提取不透水面的新型遥感指数[J].武汉大学学报(信息科学版),2008,33(11):1150-1153.
[11]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595.
[12]林云杉,徐涵秋,周榕.城市不透水面及其与城市热岛的关系研究——以泉州市区为例[J].遥感技术与应用,2007,22(1):14-19.
[13]岳文泽,吴次芳.基于混合光谱分解的城市不透水面分布估算[J].遥感学报,2007,11(6):914-922.
[14]陶秋香,陶华学,张连蓬.线性混合光谱模型在植被高光谱遥感分类中的应用研究[J].勘察科学技术,2004(1):21-24.
[15]周存林,徐涵秋.福州城区不透水面的光谱混合分析与识别制图[J].中国图象图形学报,2007,12(5):875-881.
[16]崔天翔,宫兆宁,赵文吉,等.不同端元模型下湿地植被覆盖度的提取方法——以北京市野鸭湖湿地自然保护区为例[J].生态学报,2013,33(4):1160-1171.
[17] WU C,MURRAY A T. Estimating impervious surface distribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84(4):493-505.
[18]覃志豪,ARNONKARNIELI.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.
[19]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,2004,16(3):28-32.
[20] SMITH M J D,GOODCHILD M F,LONGLEY P. Geospatial analysis:a comprehensive guide to principles,techniques and software tools[M]. 2nd ed. Leicester:Metador,2007.
[21]沈德才,杨燕琼,吴振彪,等.基于Landsat8的东莞市热岛效应研究[J].林业与环境科学,2014(6):20-24.
[2]薛志成.城市热岛效应威胁人类健康[J].安全与健康,2002(13):15-16.
[3]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.
[4]徐涵秋.城市不透水面与相关城市生态要素关系的定量分析[J].生态学报,2009,29(5):2456-2462.
[5]邹春城.基于不透水面百分比,景观指数与土地利用类型的福州市城市热环境分析[D].福州:福建师范大学,2014.
[6] RIDD M K. Exploring a V-I-S(vegetation-impervious surface-soil)model for urban ecosystem analysis through remote sensing:comparative anatomy for cities[J]. International Journal of Remote Sensing,1995,16(12):2165-2185.
[7] CARLSON T N,ARTHUR S T. The impact of land use-land cover changes due to urbanization on surface microclimate and hydrology:a satellite perspective[J]. Global and Planetary Change,2000,25(1-2):49-65.
[8] YUANG 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.
[9] WU C,MURRAY A T. Erface stimating impervious sudistribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84:493-505.
[10]徐涵秋.一种快速提取不透水面的新型遥感指数[J].武汉大学学报(信息科学版),2008,33(11):1150-1153.
[11]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595.
[12]林云杉,徐涵秋,周榕.城市不透水面及其与城市热岛的关系研究——以泉州市区为例[J].遥感技术与应用,2007,22(1):14-19.
[13]岳文泽,吴次芳.基于混合光谱分解的城市不透水面分布估算[J].遥感学报,2007,11(6):914-922.
[14]陶秋香,陶华学,张连蓬.线性混合光谱模型在植被高光谱遥感分类中的应用研究[J].勘察科学技术,2004(1):21-24.
[15]周存林,徐涵秋.福州城区不透水面的光谱混合分析与识别制图[J].中国图象图形学报,2007,12(5):875-881.
[16]崔天翔,宫兆宁,赵文吉,等.不同端元模型下湿地植被覆盖度的提取方法——以北京市野鸭湖湿地自然保护区为例[J].生态学报,2013,33(4):1160-1171.
[17] WU C,MURRAY A T. Estimating impervious surface distribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84(4):493-505.
[18]覃志豪,ARNONKARNIELI.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.
[19]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,2004,16(3):28-32.
[20] SMITH M J D,GOODCHILD M F,LONGLEY P. Geospatial analysis:a comprehensive guide to principles,techniques and software tools[M]. 2nd ed. Leicester:Metador,2007.
[21]沈德才,杨燕琼,吴振彪,等.基于Landsat8的东莞市热岛效应研究[J].林业与环境科学,2014(6):20-24.