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Received：13 January 2016，
Published：2017-01
移动端阅览
静止卫星地表温度数据是研究昼夜气候和环境变化的重要参数。但现有发布的静止卫星地表温度数据由于受到云等大气因素的影响，往往出现数值缺失现象。针对该问题，提出基于昼夜变化模型的风云静止卫星地表温度空值数据的稳健修复方法。由多项式、傅里叶函数和高斯函数构建新的昼夜变化模型，并利用Levenberg-Marquardt算法进行模型参数的求解与优化，进而实现空值修复。以风云2号F星数据(FY-2F)为例，模拟不同类型的像元缺失情况进行修复，并将不同模型修复结果与真实温度值比较，同时也对真实数据进行了测试。结果表明：本文提出的修复方法能有效对温度空值数据修复，且优于传统方法。
Land Surface Temperature (LST) derived from geostationary satellites (GEO-LST) is one of the key parameters in analyzing diurnal climate and environment changes. Compared with polar-orbiting satellite data
the LST of geostationary satellites has become increasingly attractive because of its high temporal resolution. GEO-LST has been widely applied in meteorological
climatological
and hydrological studies. However
the existing GEO-LST products can suffer from cloud cover
cloud contamination
and atmospheric disturbance
resulting in missing data. The objective of this study is to develop a new method for reconstructing Feng Yun geostationary satellite (FY-2F) LSTs based on Diurnal Temperature Cycle (DTC) and robust regression.The hourly LSTs from FY-2F with 5 km spatial resolution are adopted for this study
and different types of missing pixels are simulated and reconstructed based on a new model. This model is composed of polynomial
Fourier
and Gaussian functions (PFG)
and a robust regression called Levenberg–Marquardt (LM) algorithm is adopted for solving and optimizing the modelparameters. A performance test is conducted by comparing the PFG model based on the LM algorithm with the other two methods implemented on FY-2F data
namely
a method based on Least Square (LS) algorithm modeling of the previous model (van den Bergh. F VAN2006) and a method based on LS algorithm modeling of the PFG. Moreover
the new method is also tested for real LST products (with missing data).By comparing the reconstructed results of different methods (LM-PFG
LS-PFG
and LS-VAN2006) with the real LST values
the simulated experiment indicates that the LM-PFG method obtains the lowest root mean square compared with the other two methods. The stability analysis of these methods shows that LM-PFG is the least sensitive to missing samples
which validates that LM-PFG is more stable than LS-PFG and LS-VAN2006. Simultaneously
experimental results show that LM-PFG can also reconstruct the missing values with high accuracy and better than the other methods.In this study
an approach for reconstructing GEO-LSTs based on DTC and robust regression is proposed. The method is evaluated using simulated and real FY-2F LST products and can obtain high scores on quantitative evaluation and visual connectivity. Further work can be conducted to expand this method to other potential GEO-LSTs
such as Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager LSTs or Geostationary Operational Environmental Satellite Imager LSTs. Similar to previous studies
the reconstructed LST values of the proposed method are estimated under cloud-free conditions. LSTs under cloudy conditions should be investigated in future studies.
蔡迪花, 郭铌, 李崇伟. 2009. 基于DEM的气温插值方法研究. 干旱气象, 27(1): 10–17
Cai D H, Guo N and Li C W. 2009. Interpolation of air temperature based on DEM over eastern region of Gansu. Journal of Arid Meteorology, 27(1): 10–17
Coops N C, Duro D C, Wulder M A and Han T. 2007. Estimating afternoon MODIS land surface temperatures (LST) based on morning MODIS overpass, location and elevation information. International Journal of Remote Sensing, 28(10): 2391–2396
Duan S B, Li Z L, Wang N, Wu H and Tang B H. 2012. Evaluation of six land-surface diurnal temperature cycle models using clear-sky in situ and satellite data. Remote Sensing of Environment, 124: 15–25
Duan S B, Li Z L, Tang B H, Wu H, Tang R L, Bi Y Y and Zhou G Q. 2014. Estimation of diurnal cycle of land surface temperature at high temporal and spatial resolution from clear-sky MODIS data. Remote Sensing, 6(4): 3247–3262
Elagib N A, Alvi S H and Mansell M G. 1999. Day-length and extraterrestrial radiation for Sudan: a comparative study. International Journal of Solar Energy, 20(2): 93–109
Fan J Y. 2003. A modified Levenberg-Marquardt algorithm for singular system of nonlinear equations. Journal of Computational Mathematics, 21(5): 625–636
Finsterle S and Kowalsky M B. 2011. A truncated Levenberg-Marquardt algorithm for the calibration of highly parameterized nonlinear models. Computers and Geosciences, 37(6): 731–738
Gavin H P. 2016. The Levenberg-Marquardt Method for Nonlinear Least Squares Curve-Fitting Problems. Durham: Department of Civil and Environmental Engineering, Duke University: 1–18
Göttsche F M and Olesen F S. 2001. Modelling of diurnal cycles of brightness temperature extracted from METEOSAT data. Remote Sensing of Environment, 76(3): 337–348
Göttsche F M and Olesen F S. 2009. Modelling the effect of optical thickness on diurnal cycles of land surface temperature. Remote Sensing of Environment, 113(11): 2306–2316
Huang F, Zhan W F, Duan S B, Ju W M and Quan J L. 2014. A generic framework for modeling diurnal land surface temperatures with remotely sensed thermal observations under clear sky. Remote Sensing of Environment, 150: 140–151
景月岭, 李建波, 林皋. 2008. 结构动力数值分析的时频域转换算法研究. 大连理工大学学报, 48(6): 875–880
Jing Y L, Li J B and Lin G. 2008. Research on numerical conversion algorithms of structure dynamic analysis in time and frequency domains. Journal of Dalian University of Technology, 48(6): 875–880
Ke L H, Ding X L and Song C Q. 2013. Reconstruction of time-series MODIS LST in Central Qinghai-Tibet Plateau using geostatistical approach. IEEE Geoscience and Remote Sensing Letters, 10(6): 1602–1606
Keramitsoglou I, Kiranoudis C T and Weng Q H. 2013. Downscaling geostationary land surface temperature imagery for urban analysis. IEEE Geoscience and Remote Sensing Letters, 10(5): 1253–1257
李静, 罗奇峰. 2013. HHT变换的特点及其优越性分析//中国地震学会成立三十年学术研讨会. 北京: 中国地震学会 Li J and Luo Q F. 2013. Study on estimation of LST under cloudy region in MODIS images//The Thirty Year Academic Conference of the Seismological Society of China. Beijing: Seismological Society of China
Li Z L, Tang B H, Wu H, Ren H Z, Yan G J, Wan Z M, Trigo I F and Sobrino J A. 2013. Satellite-derived land surface temperature: current status and perspectives. Remote Sensing of Environment, 131: 14–37
刘梅. 2012. MODIS影像中云覆盖像元地表温度的估算研究. 南京: 南京大学 Liu M. 2012. Study on Estimation of LST under Cloudy Region in MODIS Images. Nanjing: Nanjing University
Ma C F and Jiang L H. 2007. Some research on Levenberg-Marquardt method for the nonlinear equations. Applied Mathematics and Computation, 184(2): 1032–1040
Madsen K, Nielsen H B and Tingleff O. 2004. Methods for non-linear least squares problems (2nd ed.). SIAM Journal on Optimization, 16(1): 487–490
欧阳晓莹, 贾立. 2011. 基于静止气象卫星FY-2C/SVISSR的地表温度时间序列反演研究//第五届海峡两岸遥感遥测会议. 哈尔滨: 中国地理学会 Ouyang X Y and Jia L. 2011. Retrieval of land surface temperature time series based on geostationary meteorological satellite FY-2C/SVISSR//5th Annual Symposium of Remote Sensing on Both Sides of the Taiwan Straits. Harbin: The Geographical Society of China
Parton W J and Logan J A. 1981. A model for diurnal variation in soil and air temperature. Agricultural Meteorology, 23: 205–216
Schädlich S, Göttsche F M and Olesen F S. 2001. Influence of land surface parameters and atmosphere on METEOSAT brightness temperatures and generation of land surface temperature maps by temporally and spatially interpolating atmospheric correction. Remote Sensing of Environment, 75(1): 39–46
司少玲, 关永. 2006. 三角函数曲线数据拟合最佳次数的确定. 计算机工程与设计, 27(24): 4660–4662
Si S L and Guan Y. 2006. Determination of optimal power of data fitting to characteristic curve of trigonometric function. Computer Engineering and Design, 27(24): 4660–4662
宋挺, 段峥, 刘军志, 石浚哲, 严飞, 盛世杰, 黄君, 吴蔚. 2015. Landsat 8数据地表温度反演算法对比. 遥感学报, 19(3): 451–464
Song T, Duan Z, Liu J Z, Shi J Z, Yan F, Sheng S J, Huang J and Wu W. 2015. Comparison of four algorithms to retrieve land surface temperature using Landsat 8 satellite. Journal of Remote Sensing, 19(3): 451–464
Udahemuka G, van den Bergh F, van Wyk B J and van Wyk M A. 2007. Robust fitting of diurnal brightness temperature cycle//18th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA). Pietermaritzburg, Kwazulu-Natal, South Africa
van den Bergh F, van Wyk M A and van Wyk B J. 2006. A Comparison of data-driven and model-driven approaches to brightness temperature diurnal cycle interpolation//Proceeding of the 17th Annual Symposium of the Pattern Recognition Association of South Africa. Parys, South Africa: 252–256
韦飞, 王世金, 梁金宝, 王月, 张申毅, 荆涛, 张焕新, 张斌全, 冷双. 2013. 风云二号03批卫星空间环境监测器. 地球物理学报, 56(1): 1–11
Wei F, Wang S J, Liang J B, Wang Y, Zhang S Y, Jing T, Zhang H X, Zhang B Q and Leng S. 2013. Next generation Space Environment Monitor (SEM) for FY-2 satellite series. Chinese Journal of Geophysics, 56(1): 1–11
Wilamowski B M and Yu H. 2010. Improved computation for Levenberg-Marquardt training. IEEE Transactions on Neural Networks, 21(6): 930–937
杨柳, 陈艳萍. 2005. 一种新的Levenberg-Marquardt算法的收敛性. 计算数学, 27(1): 55–62
Yang L and Chen Y P. 2005. On the convergence of a new Levenberg-Marquardt method. Mathematica Numerica Sinica, 27(1): 55–62
杨柳, 陈艳萍. 2008. 求解非线性方程组的一种新的全局收敛的Levenberg-Marquardt算法. 计算数学, 30(4): 388–396
Yang L and Chen Y P. 2008. A new globally convergent Levenberg-Marquardt method for solving nonlinear system of equations. Mathematica Numerica Sinica, 30(4): 388–396
Zhan W F, Chen Y H, Zhou J, Wang J F, Liu W Y, Voogt J, Zhu X L, Quan J L and Li J. 2013. Disaggregation of remotely sensed land surface temperature: literature survey, taxonomy, issues, and caveats. Remote Sensing of Environment, 131: 119–139
张鸿燕, 耿征. 2009. Levenberg-Marquardt算法的一种新解释. 计算机工程与应用, 45(19): 5–8
Zhang H Y and Geng Z. 2009. Novel interpretation for Levenberg-Marquardt algorithm. Computer Engineering and Applications, 45(19): 5–8
周义, 覃志豪, 包刚. 2014. 热红外遥感图像中云覆盖像元地表温度估算研究进展. 光谱学与光谱分析, 34(2): 364–369
Zhou Y, Qin Z H and Bao G. 2014. Progress in retrieving land surface temperature for the cloud-covered pixels from thermal infrared remote sensing data. Spectroscopy and Spectral Analysis, 34(2): 364–369
Wu P H, Shen H F, Zhang L P and Göttsche F M. 2015. Integrated fusion of multi-scale Polar-orbiting and geostationary satellite observations for the mapping of high spatial and temppral resolution land surface temperature. Remote Sensing of Enviroment, 156: 169–181
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