张亚军,李大成

• 1:太原理工大学矿业工程学院
• 2:高分辨率对地观测系统山西数据与应用中心

摘要(Abstract)：

针对目前高空间和高时间分辨率覆盖全球观测的卫星亮度温度影像数据缺失问题,该文以中分辨率成像光谱仪(MODIS)和Landsat 8卫星数据为例,提出了两种不同融合策略生成亮度温度,并评估其融合效果:先融合-后反演和先反演-后融合,从而将MODIS亮温数据降尺度到Landsat 8空间分辨率。该实验过程采用时空自适应反射率融合模型(STARFM),并将预测生成的亮温数据与预测时刻Landsat8亮温数据进行对比分析,计算相关系数、结构相似性和均方根误差(RMSE)等指标。结果得出以STARFM为核心算法的两种融合策略均可较好地应用于生成高时间高空间分辨率的亮度温度,且先融合-后反演的策略相对于先反演-后融合的策略有更高的融合精度。

关键词(KeyWords)： 数据融合;融合;STARFM;地表亮度温度

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41501372);; 山西省高校科技创新研究项目(2016144);; 民用空间基础设施建设项目([2016]2316)

作者(Author): 张亚军,李大成

DOI: 10.16251/j.cnki.1009-2307.2020.04.012

参考文献(References)：

• [1] 李召良,段四波,唐伯惠,等.热红外地表温度遥感反演方法研究进展[J].遥感学报,2016,20(5):899-920.(LI Zhaoliang,DUAN Sibo,TANG Bohui,et al.Review of methods for land surface temperature derived from thermal infrared remotely sensed data[J].Journal of Remote Sensing,2016,20(5):899-920.)
• [2] 丁凤,徐涵秋.单窗算法和单通道算法对参数估计误差的敏感性分析[J].测绘科学,2007,32(1):87-90,95.(DING Feng,XU Hanqiu.Sensitivity analysis of mono-window algorithm and single-channel algorithm to the possible errors in parameter estimation[J].Science of Surveying and Mapping,2007,32(1):87-90,95.)
• [3] 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 Zhijun,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.)
• [4] JIMENEZ-MUNOZ J C,CRISTOBAL J,SOBRINO J A,et al.Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(1):339-349.
• [5] QIN Z H,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,2001,106(D19):22655-22670.
• [6] ROZENSTEIN O,QIN Z H,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.
• [7] 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.
• [8] 石亦霏,查勇.不同土地利用类型的地表亮温变化特征[J].安徽农业科学,2011,39(29):18201-18204.(SHI Yifei,ZHA Yong.Surface brightness temperature variation of different land use types[J].Agricultural Science and Technology,2011,39(29):18201-18204.)
• [9] GAO F,MASEK J,SCHWALLER M,et al.On the blending of the Landsat and MODIS surface reflectance:predicting daily Landsat surface reflectance[J].IEEE Transactions on Geoscience & Remote Sensing,2006,44(8):2207-2218.
• [10] ZHU X L,CHEN J,GAO F,et al.An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions[J].Remote Sensing of Environment,2010,114(11):2610-2623.
• [11] HILKER T,WULDER M A,COOPS N C,et al.A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS[J].Remote Sensing of Environment,2009,113(8):1613-1627.
• [12] YANG G J,PU R L,ZHAO C J,et al.Estimation of subpixel land surface temperature using an endmember index based technique:a case examination on ASTER and MODIS temperature products over a heterogeneous area[J].Remote Sensing of Environment,2011,115(5):1202-1219.
• [13] WU M,LI H,HUANG W,et al.Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring[J].Environmental Science Processes & Impacts,2015,17(8):1396-1404.
• [14] BAI Y,WONG M S,SHI W Z,et al.Advancing of land surface temperature retrieval using extreme learning machine and spatio-temporal adaptive data fusion algorithm[J].Remote Sensing,2015,7(4):4424-4441.
• [15] 邬明权,王洁,牛铮,等.融合MODIS与Landsat数据生成高时间分辨率Landsat数据[J].红外与毫米波学报,2012,31(1):80-84.(WU Mingquan,WANG Jie,NIU Zheng,et al.A model for spatial and temporal data fusion[J].Journal of Infrared and Millimeter Waves,2012,31(1):80-84.)
• [16] TIAN F,WANG Y,FENSHOLT R,et al.Mapping and evaluation of NDVI trends from synthetic time series obtained by blending Landsat and MODIS data around a coalfield on the Loess Plateau[J].Remote Sensing,2013,5(9):4255-4279.
• [17] JARIHANI B,MCVICAR T,VAN NIEL T G,et al.Blending Landsat and MODIS data to generate multispectral indices:a comparison of “index-then-blend” and “blend-then-index” approaches[J].Remote Sensing,2014,6(10):9213-9238.
• [18] LIU H,WENG Q H.Enhancing temporal resolution of satellite imagery for public health studies:a case study of West Nile Virus outbreak in Los Angeles in 2007[J].Remote Sensing of Environment,2012,117:57-71.
• [19] WENG Q H,FU P,GAO F.Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data[J].Remote Sensing of Environment,2014,145:55-67.
• [20] 吴文丰.基于Landsat-8与MODIS数据的地表温度时空融合:SADFAT算法改进及编程实现[D].福州:福建师范大学,2016.(WU Wenfeng.Spatial-temporal fusion of land surface temperatures retrieved from Landsat-8 and MODIS imageries:improvement and programming realization of SADFAT Algorithm[D].Fuzhou:Fujian Normal University,2016.)
• [21] 吴文丰,丁凤,黎勤生,等.基于IDL与C#混合编程的遥感数据时空融合系统设计与实现[J].福建电脑,2015(12):3-4.(WU Wenfeng,DING Feng,LI Qinsheng,et al.Design and implementation of spatio-temporal fusion system for remote sensing data based on mixed programming of IDL and C#[J].Fujian Computer,2015(12):3-4.)
• [22] 丁凤,徐涵秋.基于Landsat TM的3种地表温度反演算法比较分析[J].福建师范大学学报(自然科学版),2008,24(1):91-96.(DING Feng,XU Hanqiu.Comprison of three algorithms for retrieving land surface temperature from Landsat TM thermal infrared band[J].Journal of Fujian Normal University(Natural Science Edition),2008,24(1):91-96.)
• [23] 杨强,王婷婷,陈昊,等.基于MODIS EVI数据的锡林郭勒盟植被覆盖度变化特征[J].农业工程学报,2015,31(22):191-198,315.(YANG Qiang,WANG Tingting,CHEN Hao,et al.Characteristics of vegetation cover change in Xilin Gol League based on MODIS EVI data[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(22):191-198,315).
• [24] 张开,周红敏,王锦地,等.融合Landsat ETM+和MODIS数据估算高时空分辨率地表短波反照率[J].遥感学报,2014,18(3):497-517.(ZHANG Kai,ZHOU Hongmin,WANG Jindi,et al.Estimation and validation of high spatio-temporal resolution albedo by fusig Landsat ETM+ and MODES data,Journal of Remote Sensing,2014,18(3):497-517.)
• [25] MASEK J G,VERMOTE E F,SALEOUS N E,et al.A Landsat surface reflectance dataset for North America,1990-2000[J].IEEE Geoscience & Remote Sensing Letters,2006,3(1):68-72.
• [26] FIELD C B,RANDERSON J T,MALMSTR?M C M.Global net primary production:combining ecology and remote sensing[J].Remote Sensing of Environment,1995,51(1):74-88.
• [27] CRAMER W P,KICKLIGHTER D W,BONDEAU A,et al.Comparing global models of terrestrial net primary productivity (NPP):overview and key results[J].Global Change Biology,1999,5(S1):1-15.
• [28] ANDERSON M C,KUSTAS W P,NORMAN J M,et al.Mapping daily evapotranspiration at field to global scales using geostationary and polar orbiting satellite imagery[J].Hydrology & Earth System Sciences,2011,15(1):223-239.
• [29] CAMMALLERI C,ANDERSON M C,GAO F,et al.Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion[J].Agricultural & Forest Meteorology,2014,186(10):1-11.
• [30] 刘琳,刘雪梅,张渊智.香港城市热岛效应的遥感反演分析[J].测绘科学技术,2017,5(2):23-33.(LIU Lin,LIU Xuemei,ZHANG YUanzhi.A remote sensing study of the urban heat island of Hong Kong[J].Geomatics Science and Technology,2017,5(2):23-33.)