文献类型：期刊文献

英文题名：Assessing the Effect of Temporal Interval Length on the Blending of Landsat-MODIS Surface Reflectance for Different Land Cover Types in Southwestern Continental United States

作者：Fu, Dongjie[1];Zhang, Lifu[1];Chen, Hao[1];Wang, Juan[2];Sun, Xuejian[1];Wu, Taixia[1]

第一作者：Fu, Dongjie

通讯作者：Zhang, LF[1]

机构：[1]Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China;[2]Beijing Union Univ, Coll Appl Arts & Sci, Urban Sci Dept, Beijing 100191, Peoples R China

第一机构：Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

通讯机构：[1]corresponding author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

年份：2015

卷号：4

期号：4

起止页码：2542-2560

外文期刊名：ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION

收录：;Scopus(收录号：2-s2.0-84952836745);WOS:【SCI-EXPANDED(收录号:WOS:000367723300037)】；

基金：This research is supported by the research grant funded by Natural Science Foundation of China (grant No. 41371362), the research grant funded by China Postdoctoral Science Foundation (grant No. 2014M550871), the research grant of the Direct Youth Foundation in Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (grant No. Y5SJ2000CX), Major Special Projectthe China High-Resolution Earth Observation System. We thank the USGS Earth Resources Observation Systems (EROS) data center for providing Landsat data and the Land Processes Distributed Active Archive Center (LP-DAAC) and MODIS science team for providing free MODIS products.

语种：英文

外文关键词：spatial-temporal image fusion; temporal interval; surface reflectance; Landsat; MODIS

摘要：Capturing spatial and temporal dynamics is a key issue for many remote-sensing based applications. Consequently, several image-blending algorithms that can simulate the surface reflectance with high spatial-temporal resolution have been developed recently. However, the performance of the algorithm against the effect of temporal interval length between the base and simulation dates has not been reported. In this study, our aim was to evaluate the effect of different temporal interval lengths on the accuracy using the widely used blending algorithm, Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), based on Landsat, Moderate-resolution Imaging Spectroradiometer (MODIS) images and National Land Cover Database (NLCD). Taking the southwestern continental United States as the study area, a series of experiments was conducted using two schemes, which were the assessment of STARFM with (i) a fixed base date and varied simulation date and (ii) varied base date and specific simulation date, respectively. The result showed that the coefficient of determination (R-2), Root Mean Squared Error (RMSE) varied, and overall trend of R-2 decreased along with the increasing temporal interval between the base and simulation dates for six land cover types. The mean R-2 value of cropland was lowest, whereas shrub had the highest value for two schemes. The result may facilitate selection of an appropriate temporal interval when using STARFM.