[1]郄宇凡,王宁练*,吴玉伟,等.山地冰川表面温度反演算法对比——以祁连山七一冰川为例[J].山地学报,2021,(1):129-142.[doi:10.16089/j.cnki.1008-2786.000581]
　QIE Yufan,WANG Ninglian*,WU Yuwei,et al.Comparison of Algorithms for Retrieving Mountain Glacier Surface Temperature from Remote Sensing Data: A Case Study on the Qiyi Glacier in the Qilian Mountains, China[J].Mountain Research,2021,(1):129-142.[doi:10.16089/j.cnki.1008-2786.000581]
点击复制

山地冰川表面温度反演算法对比——以祁连山七一冰川为例()
分享到：

《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2021年第1期
页码:
129-142
栏目:
山地技术
出版日期:
2021-01-25

文章信息/Info

Title:
Comparison of Algorithms for Retrieving Mountain Glacier Surface Temperature from Remote Sensing Data: A Case Study on the Qiyi Glacier in the Qilian Mountains, China
文章编号:
1008-2786-(2021)1-129-14
作者:
郄宇凡1; 2;  王宁练1; 2; 3*;  吴玉伟1; 2;  陈安安1; 2
1.陕西省地表系统与环境承载力重点实验室,西安 710127; 2. 西北大学 城市与环境学院,西安 710127; 3.中国科学院青藏高原地球科学卓越创新中心,北京 100101
Author(s):
QIE Yufan1; 2;  WANG Ninglian1; 2; 3*;  WU Yuwei1; 2;  Chen Anan1; 2
1. Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi'an 710127, China; 2. College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China; 3. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
关键词:
冰川表面温度;  Landsat 8;  七一冰川
Keywords:
glacier surface temperature;  Landsat 8;  Qiyi Glacier
分类号:
P343.6
DOI:
10.16089/j.cnki.1008-2786.000581
文献标志码:
A
摘要:
冰川表面温度决定冰川表面热力状况分布和消融状态,其对建立冰川能量—物质平衡模型和研究气候变化背景下的冰川响应具有重要意义。Landsat系列卫星提供了海量免费高空间分辨率遥感数据,广泛应用于表面温度的时空变化研究。本文使用2013年5月至2014年9月的10景Landsat 8 TIRS热红外数据,对比三种单通道温度反演算法(覃志豪单窗算法、Juan C.Jiménez-Muñoz普适性单通道算法和Jordi Cristóbal普适性单通道改进算法)和两种劈窗温度反演算法(Juan C.Jiménez-Muñoz劈窗算法和Offer Rozenstein劈窗算法)在祁连山七一冰川表面的准确度和适用性,结果表明:(1)劈窗算法反演精度高于单通道算法,其中Offer Rozenstein劈窗算法误差最小,均方根误差为1.75 K、平均绝对误差为1.49 K,而Jordi Cristóbal普适性单通道改进算法误差较大,均方根误差和平均绝对误差分别为3.35 K和2.72 K;(2)夏季消融期各算法均有较大偏差,冬季是各算法反演误差最小的季节;(3)覃志豪单窗算法对水汽含量敏感性最低,Offer Rozenstein劈窗算法对水汽含量和发射率的敏感性较高; Jordi Cristóbal普适性单通道改进算法在低大气含水量的高海拔冰川地区存在一定局限性。研究结果为不同表面温度反演算法在高海拔山地冰川区域的对比和适用性研究提供了科学依据。
Abstract:
Changes in glacier surface temperature can affect the thermal and the surface ablation statuses of a glacier. Landsat series satellites provide a huge and high spatial resolution remote sensing data, which has been widely used for the study on the temporal and spatial changes of the Earth surface temperature, including the glacier surface temperature. Some algorithms for retrieving the land surface temperature from the remote sensing data have been developed, such as single-channel algorithms(for examples, Qin Zhihao's algorithm, Juan C. Jiménez-Muñoz's algorithm and Jordi Cristóbal's algorithm)and split window algorithms(for examples, Juan C. Jiménez-Muñoz's algorithm and Offer Rozenstein algorithm). In this paper, we evaluated the accuracies and the adaptabilities of these algorithms for estimations of the glacier surface temperature based on the Landsat8 Thermal Infrared Sensor data and the observed glacier surface temperature data by the autonomous weather stations on the Qiyi Glacier in the Qilian Mountains in China over the period of May 2013 through September 2014. The results indicated that:(1)The accuracy of the split window algorithm was higher than that of the single channel algorithm, among which, the error of Offer Rozenstein SW_R algorithm was the smallest, with a root-mean-square error(RMSE)of 1.75 K and mean absolute error(MAE)of 1.49 K, while that of Jordi Cristóbal SC_T algorithm was higher, with RMSE of 3.35 K and MAE of 2.72 K.(2)All the retrieval algorithms had larger errors in summer melting season but smaller in winter.(3)The Qin Zhihao MW algorithm had the lowest sensitivity to the variations in water vapor, while the Offer Rozenstein SW_R algorithm had a higher sensitivity to water vapor and emissivity, and there were some limitations of Jordi Cristóbal SC_T algorithm for high altitude glacier areas. This comparative analysis provides a basis for selecting a suitable algorithm for retrieving the glacier surface temperature by using the remote sensing data.

参考文献/References:

[1] ANDERSON M C, NORMAN J M, KUSTAS W P, et al. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales [J]. Remote Sensing of Environment, 2008(112): 4227-4241. DOI: 10.1016/j.rse.2008.07.009
[2] KALMA J D, MCVICAR T R, MCCABE M F. Estimating land surface evaporation: a review of methods using remotely sensed surface temperature data [J]. Surveys in Geophysics, 2008, 29(4): 421-469. DOI: 10.1007/s10712-008-9037-z
[3] WU Yuwei, WANG Ninglian, HE Jianqiao, et al. Estimating mountain glacier surface temperatures from Landsat-ETM + thermal infrared data: a case study of Qiyi glacier, China [J]. Remote Sensing of Environment, 2015, 163:286-295. DOI: 10.1016/j.rse.2015.03.026
[4] ZHANG Renhua, TIAN Jing, SU Hongbo, et al. Two improvements of an operational two-layer model for terrestrial surface heat flux retrieval [J]. Sensors, 2008, 8(10): 6165-6187. DOI: 10.3390/s8106165
[5] DOUSSET B, GOURMELON F. Satellite multi-sensor data analysis of urban surface temperatures and landcover [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2003, 58(1-2): 43-54. DOI: 10.1016/S0924-2716(03)00016-9
[6] WENG Qihao. Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2009, 64(4): 335-344. DOI: 10.1016/j.isprsjprs.2009.03.007
[7] HANSEN J, RUEDY R, SATO M, et al. Global surface temperature change [J]. Reviews of Geophysics, 2010, 48(4): RG4004. DOI: 10.1029/2010RG000345
[8] HOLDERNESS T, BARR S, DAWSON R, et al. An evaluation of thermal Earth observation for characterizing urban heatwave event dynamics using the urban heat island intensity metric [J]. International Journal of Remote Sensing, 2013, 34(3): 864-884. DOI: 10.1080/01431161.2012.714505
[9] 施雅风,黄茂桓, 任炳辉. 中国冰川概论[M]. 北京: 科学出版社, 1988: 105-119. [SHI Yafeng, HUANG Maohuan, REN Binghui. An introduction to the glaciers in China [M]. Beijing: Science Press, 1988: 105-119]
[10] 黄茂桓. 我国冰川温度研究40年[J]. 冰川冻土, 1999, 21(3): 193-199. [HUANG Maohuan. Forty year's study of glacier temperature in China [J]. Journal of Glaciology and Geocryology, 1999, 21(3): 193-199]
[11] 王宁练, 贺建桥, 吴红波, 等. 青藏高原昆仑山求勉雷克塔格冰川春季表面温度空间变化特征及其影响因素[J]. 冰川冻土, 2013, 35(5):1088-1094. [WANG Ninglian, HE Jianqiao, WU Hongbo, et al. Spatial variation in spring surface temperature of the Qiumianleiketage Glacier in the Kunlun Mountains, Tibetan Plateau, and their influencing factors [J], Journal of Glaciology and Geocryology, 2013, 35(5):1088-1094] DOI: 10.7522/j.issn.1000-0240.2013.0122
[12] LI Zhaoliang, TANG Bohui, WU Hua, et al. Satellite-derived land surface temperature: current status and perspectives [J]. Remote Sensing of Environment, 2013, 131: 14-37. DOI: 10.1016/j.rse.2012.12.008
[13] QIN Zhihao, KARNIELI A, BERLINER P. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region [J]. International Journal of Remote Sensing, 2001, 22(18): 3719-3746. DOI: 10.1080/01431160010006971
[14] JIMéNEZ-MuñOZ 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): 4688. DOI: 10.1029/2003JD003480
[15] ROY D P, WULDER M A, LOVELAND T R, et al. Landsat-8: science and product vision for terrestrial global change research [J]. Remote Sensing of Environment, 2014, 145: 154-172. DOI: 10.1016/j.rse.2014.02.001
[16] 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 and Remote Sensing Letters, 2014, 11(10): 1840-1843. DOI: 10.1109/LGRS.2014.2312032
[17] WANG Fei, QIN Zhihao, SONG Caiying, et al. An improved mono-window algorithm for land surface temperature retrieval from Landsat 8 thermal infrared sensor data [J]. Remote Sensing, 2015, 7(4): 4268-4289. DOI: 10.3390/rs70404268
[18] CRISTOBAL J, JIMENEZ-MUNOZ J C, PRAKASH A, et al. An improved single-channel method to retrieve land surface temperature from the Landsat-8 thermal band [J]. Remote Sensing, 2018, 10(3): 431. DOI: 10.3390/rs10030431
[19] 孟翔晨, 历华, 杜永明, 等. Landsat 8地表温度反演及验证——以黑河流域为例[J]. 遥感学报, 2018, 22(5): 857-871. [MENG Xiangchen, LI Hua, DU Yongming, et al. Retrieval and validation of the land surface temperature derived from Landsat 8 data: a case study of the Heihe River Basin [J]. Journal of Remote Sensing, 2018, 22(5): 857-871] DOI: 10.11834/jrs.20187411
[20] ROZENITEIN O, QIN Zhihao, DERIMIAN Y, et al. Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm [J]. Sensors, 2014, 14(4): 5768-5780. DOI: 10.3390/s140405768
[21] YU Xiaolei, GUO Xulin, WU Zhaocong. Land surface temperature retrieval from Landsat 8 TIRS—comparison between radiative transfer equation-based method, split window algorithm and single channel method [J]. Remote Sensing, 2014, 6(10): 9829-9852. DOI: 10.3390/rs6109829
[22] 宋挺, 段峥, 刘军志, 等. Landsat 8 数据地表温度反演算法对比[J]. 遥感学报, 2015, 19(3): 451-464. [SONG Ting, DUAN Zheng, LIU Junzhi, et al. Comparison of four algorithms to retrieve land surface temperature using Landsat 8 satellite [J]. Journal of Remote Sensing, 2015, 19(3): 451-464] DOI: 10.11834/jrs.20154180
[23] GARCIA-SANTOS V, CUXART J, MARTINEZ-VILLGARASA D, et al. Comparison of three methods for estimating land surface temperature from Landsat 8-TIRS sensor data [J]. Remote Sensing, 2018, 10(9): 1450. DOI: 10.3390/rs10091450
[24] WANG Lei, LU Yao, YAO Yunlong. Comparison of three algorithms for the retrieval of land surface temperature from Landsat 8 images [J]. Sensors, 2019, 19(22): 5049. DOI: 10.3390/s19225049
[25] 赵伟,李爱农,张正健,等.基于Landsat8热红外遥感数据的山地地表温度地形效应研究[J].遥感技术与应用,2016, 31(1): 63-73. [ZHAO Wei, LI Ainong, ZHANG Zhengjian, et al. A study on land surface temperature terrain effect over mountainous area based on Landsat 8 thermal infrared data [J]. Remote Sensing Technology and Application, 2016, 31(1): 63-73] DOI: 10.11873/j.issn.1004-0323.2016.1.0063
[26] BARSI J A, SCHOTT J R, HOOK S J, et al. Landsat-8 Thermal Infrared Sensor(TIRS)vicarious radiometric calibration [J]. Remote Sensing, 2014, 6(11): 11607-11626. DOI: 10.3390/rs61111607
[27] 徐涵秋. 新型Landsat 8卫星影像的反射率和地表温度反演[J]. 地球物理学报, 2015, 58(3): 741-747. [XU Hanqiu. Retrieval of the reflectance and land surface temperature of the newly-launched Landsat 8 satellite [J]. Chinese Journal of Geophysics, 2015, 58(3): 741-747] DOI: 10.6038/cjg20150304
[28] 徐涵秋, 林中立, 潘卫华. 单通道算法地表温度反演的若干问题讨论—以Landsat系列数据为例[J].武汉大学学报(信息科学版), 2015, 40(4): 487-492. [XU Hanqiu, LIN Zhongli, PAN Weihua. Some issues in land surface temperature retrieval of Landsat thermal data with the single-channel algorithm [J]. Geomatics and Information Science of Wuhan University, 2015, 40(4): 487-492] DOI: 10.13203/j.whugis20130733
[29] 徐涵秋. Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响[J]. 遥感学报, 2016, 20(2): 229-235. [XU Hanqiu. Change of Landsat 8 TIRS calibration parameters and its effect on land surface temperature retrieval [J]. Journal of Remote Sensing, 2016, 20(2): 229-235] DOI: 10.11834/jrs.20165165
[30] 中国科学院高山冰雪利用研究队. 祁连山现代冰川考察报告[M]. 北京: 科学出版社,1958: 52-56. [Investigation team on utilization of snow and ice resources in mountain regions, Chinese Academy of Sciences. Investigations report of glaciers in the Qilian Mountains [M]. Beijing: Science Press, 1958: 52-56]
[31] WU Xuejiao, HE Jianqiao, JIANG Xi, et al. Analysis of surface energy and mass balance in the accumulation zone of Qiyi Glacier, Tibetan Plateau in an ablation season [J]. Environmental Earth Sciences, 2016, 75(9):785. DOI: 10.1007/s12665-016-5591-8
[32] YAO Tandong, THOMPSON L, YANG Wei, et al. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings [J]. Nature Climate Change, 2012, 2(9): 663-667. DOI: 10.1038/NCLIMATE1580
[33] 王宁练, 贺建桥, 蒲健辰, 等. 近50年来祁连山七一冰川平衡线高度变化研究[J]. 科学通报, 2010, 55(32): 3107-3115. [WANG Ninglian, HE Jianqiao, PU Jianchen, et al. Variations in equilibrium line altitude of the Qiyi Glacier, Qilian Mountains, over the past 50 years [J]. Chinese Science Bulletin, 2010, 55(32): 3107-3115] DOI: 10.1017/S0004972710001772
[34] 王坤, 井哲帆, 吴玉伟, 等. 祁连山七一冰川表面运动特征最新观测研究[J]. 冰川冻土, 2014, 36(3): 537-545. [WANG Kun, JING Zhefan, WU Yuwei, et al. Latest survey and study of surface flow features of the Qiyi Glacier in the Qilian Mountains [J]. Journal of Glaciology and Geocryology, 2014, 36(3): 537-545] DOI: 10.7522/j.issn.1000-0240.2014.0064
[35] GAO Bocai, KAUFMAN Y J. MODIS atmosphere L2 water vapor product [EB/OL]. http://dx.doi.org/10.5067/MODIS/MOD05_L2.006. html, 2021-1-6.
[36] CHEN Feng, ZHAO Xiaofeng, YE Hong, et al. Retrieving land surface temperature from Landsat TM using different atmospheric products as ancillary data [C]. Proceedings of 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, 2011: 421-426. DOI: 10.1109/ICSDM.2011.5969079
[37] PRATA A J. Land surface temperatures derived from the advanced very high resolution radiometer and the along-track scanning radiometer 1. theory [J]. Journal of Geophysical Research, 1993, 98(D9): 16689-16702. DOI: 10.1029/93JD01206
[38] SNYDER W C, WAN Z, ZHANG Y, et al. Classification-based emissivity for land surface temperature measurement from space [J]. International Journal of Remote Sensing, 1998, 19(14): 2753-2774. DOI: 10.1080/014311698214497
[39] SOBRINO J A, RAISSOUNI N. Toward remote sensing methods for land cover dynamic monitoring: application to Morocco [J]. International Journal of Remote Sensing, 2000, 21(2): 353-366. DOI: 10.1080/014311600210876
[40] HORI M, AOKI T, TANIKAWA T, et al. Modeling angular-dependent spectral emissivity of snow and ice in the thermal infrared atmospheric window [J]. Applied Optics, 2013, 52(30): 7243-7255. DOI: 10.1364/AO.52.007243
[41] FRENIERRE J L, MARK B G. A review of methods for estimating the contribution of glacial meltwater to total watershed discharge [J]. Progress in Physical Geography, 2014, 38(2): 173-200. DOI: 10.1177/0309133313516161
[42] 陆品廷. 基于Landsat 8数据的青藏高原地区地表温度反演研究[D].南京: 南京信息工程大学, 2018. [LU Pinyan. Study on land surface temperature retrieval of Tibetan Plateau from Landsat 8 data [D]. Nanjing: Nanjing University of Information Science and Technology, 2018] DOI: CNKI:CDMD:2.1018.130709

备注/Memo

备注/Memo:
收稿日期(Received date):2020-02-06; 改回日期(Accepted data):2020-12-18
基金项目(Foundation item)中国科学院战略性先导科技专项(A类)(XDA19070302、XDA20060201); 第二次青藏高原综合科学考察研究(2019QZKK020102)。 [The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19070302、XDA20060201); The Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK020102)]
作者简介(Biography):郄宇凡(1995- ),男,硕士研究生,主要研究方向:冰川温度反演。[QIE Yufan(1995- ), male, born in Shenmu, Shaanxi province, M.Sc.candidate, research on glacier temperature retrieve] E-mail:yufanqie@stumail.nwu.edu.cn
*通讯作者(Corresponding author):王宁练(1966- ),男,博士,教授,主要研究方向:冰冻圈与全球变化。[WANG Ninglian(1966- ), male, Ph.D., professor, research on cryosphere and global change] E-mail:nlwang@nwu.edu.cn
更新日期/Last Update: 2021-01-30