Validation of FY-2C derived land surface temperature over the source region of the Yellow River: A case study of Maqu County
WANG Yawei1, SONG Xiaoning1, TANG Bohui2, LI Zhaoliang3,4, LENG Pei1
1. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
3. Key Laboratory of Agri-Informatics, Ministry of Agriculture, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agriculture Sciences, Beijing 100081, China;
4. ICube of Universit? de Strasbourg, Strasbourg 67412, France
Land surface temperature (LST) is an essential parameter in such fields of research as climate, hydrology and ecology, and it plays a significant role in the understanding of the water and energy balance of the Earth's surface. Because the heterogeneity of the underlying surface is most likely a main source of the uncertainties of the satellite derived LST, this paper aims to evaluate the accuracy of the FY-2C derived LST over the heterogeneous area of Maqu County in the source region of the Yellow River and subsequently to provide solid basis for the future development of the LST inversion algorithm and product. MODIS LST product (MOD11B1) was primarily conducted to verify the FY-2C derived LST over the study area. In addition to the MODIS data, soil temperature measurements from 20 soil samples of the study area were also implemented to validate the FY-2C derived LST. The results indicate that a significant correlation exists between the two datasets, with the coefficient of correlation, varying from 0.72 to 0.95, root mean square error(RMSE) ranging from 0.44 to 3.87 K, and the average RMSE being 1.90 K. The FY-2C derived LST exhibits a consistent variation with the measured soil temperature, and the coefficient of correlation reaches 0.69.
王亚维, 宋小宁, 唐伯惠, 李召良, 冷佩. 基于FY-2C数据的地表温度反演验证——以黄河源区玛曲为例[J]. 国土资源遥感, 2015, 27(4): 68-72.
WANG Yawei, SONG Xiaoning, TANG Bohui, LI Zhaoliang, LENG Pei. Validation of FY-2C derived land surface temperature over the source region of the Yellow River: A case study of Maqu County. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(4): 68-72.
[1] 徐希孺, 柳钦火, 陈家宜.遥感陆面温度[J].北京大学学报:自然科学版, 1998, 34(2/3):248-253. Xu X R, Liu Q H, Chen J Y.Remote sensing of land surface temperature[J].Acta Scientiarum Naturalium Universitatis Pekinensis, 1998, 34(2/3):248-253.[2] Price J C.Land surface temperature measurements from the split window channels of the NOAA7/AVHRR[J].Journal of Geophysical Research, 1984, 89(D5):7231-7237.[3] 祝善友, 张桂欣, 尹球.地表温度热红外遥感反演的研究现状及其发展趋势[J].遥感技术与应用, 2006, 21(5):420-425. Zhu S Y, Zhang G X, Yin Q.Actualities and development trends of the study on land surface temperature retrieving from thermal infrared remote sensing[J].Remote Sensing Technology and Application, 2006, 21(5):420-425.[4] 甘甫平, 陈伟涛, 张绪教, 等.热红外遥感反演陆地表面温度研究进展[J].国土资源遥感, 2006, 18(1):6-11.doi:10.6046/gtzyyg.2006.01.02. Gan F P, Chen W T, Zhang X J, et al.The progress in the study of thermal infrared remote sensing for retrieving land surface temperature[J].Remote Sensing for Land and Resources, 2006(1):6-11.doi:10.6046/gtzyyg.2006.01.02.[5] Becker F.The impact of spectral emissivity on the measurement of land surface temperature from a satellite[J].International Journal of Remote Sensing, 1987, 8(10):1509-1522.[6] 李健.长白山地区地表温度反演研究[D].长春:吉林大学, 2005. Li J.A Study of Land Surface Temperature Retrieval for the Region of Changbai Mountain of China[D].Changchun:Jilin University, 2005.[7] Vidal A.Atmospheric and emissivity correction of land surface temperature measured from satellite using ground measurements of satellite data[J].International Journal of Remote Sensing, 1991, 12(12):2449-2460.[8] 柳钦火, 徐希孺, 陈家宜.遥测地表温度与比辐射率的迭代反 演方法——理论推导与数值模拟[J].遥感学报, 1998, 2(1):1-9. Liu Q H, Xu X R, Chen J Y.The retrieval of land surface temperature and emissivity by remote sensing data:Theory and digital simulation[J].Journal of Remote Sensing, 1998, 2(1):1-9.[9] Qin Z H, Karnieli A.Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data[J].International Journal of Remote Sensing, 1999, 20(12):2367- 2393.[10] Gao C X, Tang B H, Wu H, et al.A generalized split-window algorithm for land surface temperature estimation from MSG-2/SEVIRI data[J].International Journal of Remote Sensing, 2013, 34(12):4182-4199.[11] Qian Y G, Qiu S, Wang N, et al.Land surface temperature and emissivity retrieval from time-series mid-infrared and thermal infrared data of SVISSR/FY-2C[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(3):1552-1563.[12] Trigo I F, Monteiro I T, Olesen F, et al.An Assessment of remotely sensed land surface temperature[J].Journal of Geophysical Research:Atmospheres(1984-2012), 2008, 113(D17):D17108.[13] Trigo I F, Peres L F, DaCamara C C, et al.Thermal land surface emissivity retrieved from SEVIRI/Meteosat[J].IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(2):307-315.[14] Tang B H, Bi Y Y, Li Z L, et al.Generalized split-window algorithm for estimate of land surface temperature from Chinese geostationary FengYun meteorological satellite(FY-2C) data[J].Sensors, 2008, 8(2):933-951.[15] 张霄羽, 王娇.基于静止气象卫星数据的地表温度遥感估算[J].遥感技术与应用, 2013, 28(1):12-17. Zhang X Y, Wang J.Estimation of land surface temperature using geostationary meteorological satellite data[J].Remote Sensing Technology and Application, 2013, 28(1):12-17.[16] 国家卫星气象中心.风云卫星遥感数据服务网[EB/OL].[2014-05-04].http://www.nsmc.cma.gov.cn/NSMC/Home/Index.html. National Satellite Meteorological Center.FENGYUN Satellite Data Center[EB/OL].[2014-05-04].http://www.nsmc.cma.gov.cn/NSMC/Home/Index.html.[17] 胡菊旸.风云卫星地表温度反演算法研究[D].北京:中国气象科学研究院, 2012. Hu J Y.The Study of Algorithms for Land Surface Temperature Retrieval from Feng Yun Satellite Data[D].Beijing:Chinese Academy of Meteorological Sciences, 2012.[18] Wan Z M, Dozier J.A generalized split-window algorithm for retrieving land-surface temperature from space[J].IEEE Transections on Geoscience and Remote Sensing 1996, 34(4):892-905.[19] Lagouarde J P, Dayau S, Moreau P, et al.Directional anisotropy of brightness surface temperature over vineyards:Case study over the medoc region(SW France)[J].IEEE Geoscience and Remote Sensing Letters, 2014, 11(2):574-578.[20] Lagouarde J P, Hénon A, Kurz B, et al.Modelling daytime thermal infrared directional anisotropy over Toulouse city centre[J].Remote Sensing of Environment, 2010, 114(1):87-105.[21] Ren H Z, Yan G J, Chen L, et al.Angular effect of MODIS emissivity products and its application to the split-window algorithm[J].ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(4):498-507.
2015, Vol. 27 
