在使用遥感数据提取煤火热异常信息的TAE算法的基础上,根据城市热岛特点对算法进行了改进,提出了针对城市热岛研究的Urban-TAE算法,即U-TAE算法。该算法使用不同范围的滑动窗口来探测整幅图像,根据稳健估计的方法设定地表温度高于全部像元以及窗口内像元温度统计均值+标准差的像元为热异常像元,并将滑动窗口的范围设置在5×5~151×151个像元之间,根据像元被记为热岛像元的次数是否为0来区别非热岛区与热岛区,在热岛区域内根据次数的多少来决定热岛强度,具有动态阈值的特点和无偏特性。研究结果表明,在城市热岛范围的提取上,2001年长沙市热岛面积在55.31 km2至68.35 km2之间;在城市热岛的强度分析上,宏观尺度的研究应选用较大的窗口来体现城-郊热岛关系以及热岛发展的总体趋势,而小窗口在微观分析城区内热岛的具体分布、与下垫面的关系以及驱动因子方面较有优势。与传统方法相比,U-TAE算法使得不同时相的实验结果具有可比性。
The urban thermal anomaly extraction (U-TAE) algorithm was proposed for the study of urban heat island, which was evolved from the TAE algorithm for thermal anomalies extraction of underground coal fires. The U-TAE algorithm detects the entire thermal infrared image by moving windows with different sizes, and the key of this robust algorithm was to set up thresholds for pixels with land surface temperatures (LST) higher than mean plus standard deviation. Mean and standard deviation were calculated from all pixels and those pixels in the moving windows (scope from 5×5 to 151×151 pixels). This algorithm can distinguish UHI areas from background areas according to the cumulative times of pixels, and determine UHI intensity according to the cumulative times in UHI areas. Cumulative times of zero are background areas and the others are UHI areas. This U-TAE algorithm has dynamic thresholds and unbias characteristics. Results showed that the heat island areas were between 55.31 km2 and 68.35 km2 in Changsha in 2001. In UHI intensity analysis, the UHI studies at macro-scale should use larger moving windows to reflect the relationship between urban and rural areas. Micro-scale studies should use smaller moving windows to analyze specific distribution of UHI, underlying surface and driving factors. Compared with traditional methods, U-TAE algorithm makes the results comparable in different time periods.
[1] 陈云浩,李京,李晓兵. 城市空间热环境遥感分析——格局、过程、模拟与影响.北京:科学出版社,2004. 1~5.
[2] Howard L. Climate of London deduced from meteorological observation. London: Harvey and Datron,1833.
[3] 李志乾,巩彩兰,胡勇,等. 城市热岛遥感研究进展. 遥感信息,2009,(8):100~105.
[4] 胡华浪,陈云浩,宫阿都. 城市热岛的遥感研究进展. 国土资源遥感,2005,(3):5~9, 13.
[5] 李福建,马安青,丁原东,等. 基于LANDSAT数据的城市热岛效应研究. 遥感技术与应用,2009,24(4):553~558.
[6] Rao P K. Remote sensing of urban heat islands from an environment satellite. Bulletin of the American Meteorologieal Society,1972,53: 647~648.
[7] 陈云浩,史培军,李晓兵. 基于遥感与GIS的上海城市空间热环境研究. 测绘学报,2002,31(5):139~144.
[8] 周红妹,周成虎,葛伟强. 基于遥感与GIS的城市热场分布规律研究. 地理学报,2001,56(2):189~197.
[9] 宫阿都,江樟焰,李京,等. 基于Landsat TM图像的北京城市地表温度遥感反演研究. 遥感信息,2003(3):18~20.
[10] 彭征,廖和平,郭月婷,等. 山地城市土地覆盖变化对地表温度的影响. 地理研究,2009,28(3):673~684.
[11] 历华,曾永年,贠培东,等. 基于MODIS数据的长株潭地区城市热岛时空分析. 测绘科学,2007,32(5):108~116.
[12] 覃志豪,Zhang M,Karnieli A,等. 用陆地卫星TM6数据演算地表温度的单窗算法. 地理学报,2001,56(4):456~466.
[13] Jimenez-Munoz J C,Sobrino J A. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research,2003,108(D22):4688~4695.
[14] 黄妙芬,邢旭峰,王培娟,等. 利用LANDSAT/TM 热红外通道反演地表温度的三种方法比较. 干旱区地理,2006,29(1):132~137.
[15] Streutker D R. A remote sensing study of the urban heat island of Houston, Texas. International Journal of Remote Sensing,2002,23:2595~2608.
[16] Zhang J,Wang Y,Wang Z. Change analysis of land surface temperature based on robust statics in the estuarine area of Pearl River (China) from 1990 to 2000 by Landsat TM/ETM+. International Journal of Remote Sensing,2007, 28(10):2383~2390.
[17] 张勇,余涛,顾行发,等. CBERS-02 IRMSS热红外数据地表温度及其在城市热岛效应定量化分析中的应用. 遥感学报,2006,10(5):789~797.
[18] Zhang J. Spatial and statistical analysis of thermal satellite imagery for extraction of coal fire related anomalies.Vienna: PhD thesis, Technical University Vienna, Austria,2004.
[19] Kuenzer C,Hecker C,Zhang J,et al. The potential of multidiurnal MODIS thermal band data for coal fire detection. International Journal of Remote Sensing,2008,29(3):923~944.
[20] 张月丛,赵志强,李双成,等. 基于SPOT NDVI 的华北北部地表植被覆盖变化趋势. 地理研究,2008,27(4):746~754.
[21] 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. 遥感学报,2005,9(5):589~595.
[22] 徐涵秋. 基于谱间特征和归一化指数分析的城市建筑用地信息提取. 地理研究,2005,24(2):311~320.
[23] 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. 国土资源遥感,2004,(3):28~32,36.
[24] Nerry F,Labed J,Stoll M P. Spectral properties of land surfaces in the thermal infrared 1. Laboratory measurements of absolute spectral emissivity signatures. Journal of Geophysical Research, 1990,95:7027~7044.
[25] Salisbury J W,D'Aria D M. Emissivity of terrestrial materials in the 8-14μm atmospheric window. Remote Sensing of Environment,1992,42:83~106.
[26] Kuenzer C,Zhang J,Li J,et al. Detecting unknown coal fires: synergy of coal fire risk area delineation and improved thermal anomaly extraction. International Journal of Remote Sensing,2007,28(19-20):4561~4585.
