基于Landsat-8热红外数据的太湖地区地表温度反演与热岛效应分析

doi:10.3969/j.issn.1000-5641.2016.04.015

华东师范大学学报(自然科学版)

基于Landsat-8热红外数据的太湖地区地表温度反演与热岛效应分析

阚增辉^[1,2], 刘朝顺^[1,2], 李志军^[3]

1. 华东师范大学地理信息科学教育部重点实验室, 上海200241; 2. 华东师范大学环境遥感与数据同化联合实验室, 上海 3. 江苏省靖江市气象局, 江苏靖江214500

收稿日期:2015-07-08 出版日期:2016-07-25 发布日期:2016-09-29
通讯作者: 刘朝顺，男，博士，副研究员，研究方向为陆面定量遥感研究. E-mail: csliu@re.ecnu.edu.cn.
作者简介:阚增辉, 男, 硕士研究生, 研究方向为遥感与GIS应用. Email:kzh_ecnu_gis@163.com.
基金资助:
国家自然科学基金(41101037,41271055)；上海市科委重点支撑项目(13231203804)；中央高校基本科研业务费专项(华东师范大学)；地理信息科学教育部重点实验室主任基金(KLGIS2011C06)；江苏省气象局青年开放基金项目(Q201005)

Retrieval of land surface temperature based on Landsat-8 thermal infrared data and heat island effect analysis over the Taihu Lake region

KAN Zeng-hui^[1,2], LIU Chao-shun^[1,2], LI Zhi-jun^[3]

1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China;
2. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, East China Normal University, Shanghai 200241, China;
3. Jingjiang Meteorological Bureau, Jingjiang Jiangsu 214500, China

Received:2015-07-08 Online:2016-07-25 Published:2016-09-29

摘要/Abstract

摘要：

应用 Landsat-8 TIRS 遥感数据结合气象资料, 使用三种不同的反演方法获得苏南太湖地区的地表温度(LST)数据. 分析发现, 辐射传输方程法反演的结果最接近于实测值；在缺乏实时大气廓线的情况下,普适性单通道算法更适用于 Landsat-8 热红外波段的地表温度反演；分裂窗算法在三种算法中精度最差. 在反演结果的基础上, 分析了不同地物的 LST 特征, 建筑用地温度最高, 水体最低. 归一化植被指数(NDVI)和 LST 之间存在明显的负相关关系, 证明了城市绿地是缓解城市热岛效应、改善城市热环境的重要途径. 最后对 2000 年和 2014 年的两时相 LST 进行标准化和分区处理, 分析发现, 苏南太湖地区的热岛现象近些年来在不断加剧, 城市热岛由原来单个存在逐渐成为多个热岛并存的局面, 建筑用地的增加是导致整个城市热岛加剧的主要原因.

关键词: Landsat-8;TIRS, 大气辐射传输, 单通道算法, 分裂窗算法, 太湖地区

Abstract:

Using three different retrieval algorithms based on Landsat-8 thermal infrared data and meteorological data, land surface temperature (LST) of the Taihu Lake region is obtained. After comparing the values of three different algorithms with measured values, we find that the result of radiative transfer equation (RTE) is a good approximation to the measured values. When the real-time atmospheric profile is absent, general single-channel algorithm (SC) is more suitable for land surface temperature retrieval based on Landsat 8 thermal infrared data.The split window algorithm (SW) has the lowest accuracy. After analyzing the LST
characteristics of different land cover based on the result of RTE, we find that built-up areas has the highest LST while water body has the lowest LST. There is a negative correlation relationship between the normalized difference vegetation index (NDVI) and the LST values, which indicates that urban green space is a key way to improve urban thermal environment and alleviate urban heat island effect. Finally, after comparing the LST results in year 2000 and 2014, we find that the heat island phenomenon of the Taihu Lake region is increasing in the past 14 years and single existent urban heat islands has gradually become coexistent heat islands now. Building land expansion is the main reason that leads to the increasing of urban heat island.

Key words: Landsat-8;TIRS; , atmospheric radiation transmission;SW;SC;Taihu Lake region

阚增辉, 刘朝顺, 李志军. 基于Landsat-8热红外数据的太湖地区地表温度反演与热岛效应分析[J]. 华东师范大学学报(自然科学版), doi: 10.3969/j.issn.1000-5641.2016.04.015.

KAN Zeng-hui, LIU Chao-shun, LI Zhi-jun. Retrieval of land surface temperature based on Landsat-8 thermal infrared data and heat island effect analysis over the Taihu Lake region[J]. Journal of East China Normal University(Natural Sc, doi: 10.3969/j.issn.1000-5641.2016.04.015.

参考文献

[ 1 ] 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 [J]. 干旱区地理,2006, 29(1): 132-137.
[ 2 ] 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.
[ 3 ] JIMENEZ-MUNOZ J C, SOBRINO J A. A generalized single-channel method for retrieving land surface temperature from remote sensing data [J]. Journal of Geophysical Research, 2003, 108(D22): 2015-2023.
[ 4 ] ANDING D, KAUTH R. Estimation of sea surface temperature from space [J]. Remote Sensing of Environment, 1971, 1(4): 217-220.
[ 5 ] QIN Z, DALL’OLMO G, KARNIELI A, et al. Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-advanced very high resolution radiometer data [J]. Journal of Geophysical Research Atmospheres, 2001, 106(D19): 22655-22670.
[ 6 ] SOBRINO J A, LI Z L, STOLL M P, et al. Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data [J]. International Journal of Remote Sensing, 1996, 17(11): 2089-2114.
[ 7 ] JIMENEZ-MUNOZ J C, SOBRINO J A. Split-window coefficients for land surface temperature retrieval from low-resolution thermal infrared sensors [J]. IEEE Geoscience & Remote Sensing Letters, 2008, 5(4): 806-809.
[ 8 ] JIMENEZ-MUNOZ J C, SOBRINO J A, SKOKOVIC D, et al. Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data [J]. IEEE Geoscience & Remote Sensing Letters, 2014, 11(10): 1840-1843.
[ 9 ] SNYDER W C, WANZ, ZHANGY, et al. Classification-based emissivity for land surface temperature measurement from space [J]. International Journal of Remote Sensing, 1998, 19(14): 2753-2774.
[10] VAN DE GRIENDAA, OWE M. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces [J]. International Journal of Remote Sensing, 1993, 84(3): 1119-1131.
[11] QIN Z, GAO M. An algorithm to retrieve land surface temperature from ASTER thermal band data for agricultural drought monitoring [J]. Proceedings of SPIE-The International Society for Optical Engineering, 2006, 6359. DOI: 10.1117/12.689307.
[12] 王国复, 李集明, 邓莉,等. 中国气象科学数据共享服务网总体设计与建设 [J].应用气象学报, 2004, 15(z1): 10-16.
[13] CATTRALL C, THOME K J. Exploitation of MODTRAN4 capabilities to predict at-sensor radiance [J]. Optical Spectroscopic Techniques & Instrumentation for Atmospheric & Space Research V, 2003, 5157:98-106.
[14] SOBRINO J A, JIM´ENEZ-MU˜ NOZ J C, PAOLINI L. Land surface temperature retrieval from LANDSAT TM 5 [J]. Remote Sensing of Environment, 2004, 90(4): 434-440.
[15] COLL C, CASELLES V, VALOR E, et al. Comparison between different sources of atmospheric profiles for land surface temperature retrieval from single channel thermal infrared data [J]. Remote Sensing of Environment, 2012, 117(1): 199-210.
[16] LO C P, QUATTROCHI D A, LUVALL J C. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect [J]. International Journal of Remote Sensing, 1997, 18(2): 287-304.
[17] WILSON J S, CLAY M, MARTIN E, et al. Evaluating environmental influences of zoning in urban ecosystems with remote sensing [J]. Remote Sensing of Environment, 2003, 86(3): 303-321.

基于Landsat-8热红外数据的太湖地区地表温度反演与热岛效应分析

Retrieval of land surface temperature based on Landsat-8 thermal infrared data and heat island effect analysis over the Taihu Lake region

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