基于Landsat8影像的安庆市城市热岛效应分析
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摘要
从美国地质勘探局(United States Geological Survey,USGS)下载Landsat8卫星影像(2014/05/01和2018/04/10)作为数据源,安庆市市区为研究区,采用单窗算法反演出安庆市辖区的地表温度,并对反演结果进行归一化处理和分级,对安庆市市辖区的热岛效应进行时空变化分析。在此基础上,分析研究区内的NDBBI(归一化差值裸地与建筑用地指数),NDVI(归一化植被指数),MNDWI(改进的归一化水体指数),BSI(裸土指数)等与地表温度之间的关系。研究表明:(1)安庆市城市热岛效应显著,城区温度明显高于周边郊区;(2)安庆市热岛效应与NDVI,MNDWI呈负相关,与BSI,NDBBI呈正相关;(3)2014—2018年,安庆市城市热岛效应不断增强,热岛效应面积不断增加。
The data sources were selected from the remote sensing images(on May 1st, 2014 and April 10 th,2018)by Landsat8 satellites downloaded from the U.S. Geological Survey and the urban area of Anqing City is the study area. The paper adopted the mono-window algorithm to invert the land surface temperature of the Anqing City, and the paper normalized and graded the results, then made the spatio-temporal change analysis of urbanheat island effect in the Anqingdowntown area. On this basis above, the paper analyzed the relationship between the urban surface temperature and NDBBI, NDVI, MNDWI, BSI etc. The research shows:(1) Urban heat island effect in Anqing is very remarkable and temperature of downtown area is higher than that of the surrounding suburbs;(2) The heat island effect in Anqing is negatively correlated with NDVI and MNDWI, and positively correlated with BSI and NDBBI;(3) From 2014 to 2018,urban heat island effect in Anqing increased and the area of heat island effect have increased.
The data sources were selected from the remote sensing images(on May 1st, 2014 and April 10 th,2018)by Landsat8 satellites downloaded from the U.S. Geological Survey and the urban area of Anqing City is the study area. The paper adopted the mono-window algorithm to invert the land surface temperature of the Anqing City, and the paper normalized and graded the results, then made the spatio-temporal change analysis of urbanheat island effect in the Anqingdowntown area. On this basis above, the paper analyzed the relationship between the urban surface temperature and NDBBI, NDVI, MNDWI, BSI etc. The research shows:(1) Urban heat island effect in Anqing is very remarkable and temperature of downtown area is higher than that of the surrounding suburbs;(2) The heat island effect in Anqing is negatively correlated with NDVI and MNDWI, and positively correlated with BSI and NDBBI;(3) From 2014 to 2018,urban heat island effect in Anqing increased and the area of heat island effect have increased.
引文
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[17]方慧婷,杨英宝,汪子豪.长三角夏季热岛效应时空演变分析[J].地理空间信息,2017,15(8):109-112.
[18]罗小瑞,沈非,王正,等.合肥市热岛效应时空演变分析[J].安徽农学通报,2016,22(23):91-95.
[19]尤承增,杨新源,束安,等.基于Landsat数据的城市热岛效应分析与研究[J].环境工程,2016(S1):1145-1150.
[20]周鹏,方刚,陈丽,等.基于Landsat 8影像的马鞍山市热岛效应研究[J].石家庄学院学报,2016,18(3):63-69.
[21]祁凯英.单窗算法地表温度反演的初步研究[J].内蒙古煤炭经济,2015(7):196-199.
[22]覃志豪, LI Wenjuan,Zhang Minghua,等.单窗算法的大气参数估计方法[J].国土资源遥感,2003,15(2):37-43.
[23]胡德勇,乔琨,王兴玲,等.利用单窗算法反演Landsat 8 TIRS数据地表温度[J].武汉大学学报(信息科学版),2017,42(7):869-876.
[2] RAO P K. Remote Sensing of Urban Heat Islands from an Environmental Satellite[J].Bulletin of the American Meteorological Society,1972,53:647-648.
[3] STREUTKER D R. A Remote Sensing Study of the Urban Heat Island Of Houston,Texas[J].International Journal of Remote Sensing,2002,23(13):2595-2608.
[4]李璇琼,李永树,卢正,等.兰州市热岛效应时空演化研究[J].城市发展研究,2015,22(7):18-22.
[5]方刚.基于Landsat8卫星影像和地表参数的宿州市城市热岛效应分析[J].土壤通报,2014,45(5):1241-1246.
[6]胡德勇,乔琨,王兴玲,等.单窗算法结合Landsat8热红外数据反演地表温度[J].遥感学报,2015,19(6):964-976.
[7]覃志豪,Arnon Karnieli.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.
[8]邓书斌. ENVI遥感图像处理方法[M].2版.高等教育出版社,2014.
[9] SOBRINO J A,JIMéNEZ-MU?OZ J C,PAOLINI L.Land Surface Temperature Retrieval from LANDSAT TM5[J]. Remote Sensing of Environment,2004,90(4);434-440.
[10] PUREVDORJ T S,TATEISHI R,ISHIYAMA T,et al.Relationships between Percent Vegetation Cover and Vegetation Indices[J].International Journal of Remote Sensing,1998,19(18):3519-3535.
[11] RIKIMARU A. Landsat T M Data Processing Guide for Forest Canopy Density Mapping and Monitoring Model[C]//ITTO Workshop on Utilization of Remote Sensing in Site Assessment and Planning for Rehabilitation of Logged-over Forest.Bangkok,Thailand,1996:1-8.
[12]吴志杰,赵书河.基于TM图像的“增强的指数型建筑用地指数”研究[J].国土资源遥感,2012,24(2):50-55.
[13]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.
[14] TOBY N. CARLSON,ROBERT R.GILLIES,EILEEN M. PERRY. A Method to Make Use of Thermal Infrared Temperature and NDVI measurements to Infer Surface Soil Water Content and Fractional Vegetation Cover[J].Remote Sensing Reviews,1994,9(1):161-173.
[15] PRICE J C. Using Spatial Context in Satellite Data to Infer Regional Scale Evapotranspiration[J]. IEEE Transactions on Geoscience&Remote Sensing,1990,28(5):940-948.
[16]张宇,赵伟,龙凤,等.基于Landsat TM/TIRS的重庆市主城区热岛效应研究[J].水土保持研究,2015,22(5):191-196.
[17]方慧婷,杨英宝,汪子豪.长三角夏季热岛效应时空演变分析[J].地理空间信息,2017,15(8):109-112.
[18]罗小瑞,沈非,王正,等.合肥市热岛效应时空演变分析[J].安徽农学通报,2016,22(23):91-95.
[19]尤承增,杨新源,束安,等.基于Landsat数据的城市热岛效应分析与研究[J].环境工程,2016(S1):1145-1150.
[20]周鹏,方刚,陈丽,等.基于Landsat 8影像的马鞍山市热岛效应研究[J].石家庄学院学报,2016,18(3):63-69.
[21]祁凯英.单窗算法地表温度反演的初步研究[J].内蒙古煤炭经济,2015(7):196-199.
[22]覃志豪, LI Wenjuan,Zhang Minghua,等.单窗算法的大气参数估计方法[J].国土资源遥感,2003,15(2):37-43.
[23]胡德勇,乔琨,王兴玲,等.利用单窗算法反演Landsat 8 TIRS数据地表温度[J].武汉大学学报(信息科学版),2017,42(7):869-876.