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一种拓展的半物理时空融合算法及其初步应用
引用本文:李大成,唐娉,胡昌苗,郑柯.一种拓展的半物理时空融合算法及其初步应用[J].遥感学报,2014,18(2):307-319.
作者姓名:李大成  唐娉  胡昌苗  郑柯
作者单位:中国科学院 遥感与数字地球研究所, 北京 100101;太原理工大学 矿业工程学院, 山西 太原 030024;中国科学院 遥感与数字地球研究所, 北京 100101;中国科学院 遥感与数字地球研究所, 北京 100101;中国科学院 遥感与数字地球研究所, 北京 100101
基金项目:国家高技术研究发展计划(863计划)(编号:2009AA122002)
摘    要:Landsat 5卫星较低的时间分辨率(16天)使得其很难获得大区域的、时相一致的清晰影像数据集。本文发展了一种基于半物理模型的时空融合算法-即乘性调制融合算法,并借助多时序的MODIS反射率数据来生成多时相的Landsat TM/ETM+反射率合成影像,经镶嵌后得到区域尺度的高时空分辨率地表反射率数据集(Landsat TM/ETM+)。本文利用吉林省2006年—2011年的Landsat 5 TM地表反射率数据以及500 m的MOD09A1反射率产品来生成3个时相的Landsat 5 TM反射率合成数据,从而获得研究区在上述时相下地表反射率数据的镶嵌图。初步分析表明,所生成的Landsat 5 TM反射率数据的光谱分布特征与MOD09A1反射率数据较为一致,且图像在整体上光谱特征的连续性较好。

关 键 词:时空融合  半物理模型  乘性调制  Landsat  TM/ETM+  MODIS  地表反射率数据集
收稿时间:2013/8/26 0:00:00
修稿时间:2013/11/27 0:00:00

Spatial-temporal fusion algorithm based on an extended semi-physical model and its preliminary application
LI Dacheng,TANG Ping,HU Changmiao and ZHENG Ke.Spatial-temporal fusion algorithm based on an extended semi-physical model and its preliminary application[J].Journal of Remote Sensing,2014,18(2):307-319.
Authors:LI Dacheng  TANG Ping  HU Changmiao and ZHENG Ke
Institution:Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;Taiyuan University of Technology, Institute of Mining engineering, Taiyuan 030024, China;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Abstract:Regional and clear data sets on a specified date is difficult for Landsat 5 because of low temporal resolution (16 d). In this study, we develop a spatial-temporal fusion algorithm based on semi-physical model-multiplicative modulation fusion algorithm and generate synthetic multi-temporal Landsat 5 TM/ETM+ reflectance data with the help of multi-temporal MODIS reflectance data. A regional scaled data set of surface reflectance with high spatial and temporal resolution is retrieved after image mosaicking. In this study, we generate three temporal Landsat 5 TM reflectance data that cover Jilin Province in China by utilizing Landsat 5 TM surface reflectance data, and the 500 m MOD09A1 reflectance products were collected from 2006 to 2011.Surface reflectance mosaic data that cover the study area were then derived. Primary analysis shows that the generated Landsat 5 TM reflectance data have good agreement with the MOD09A1 reflectance data in spectral distribution features, and color distribution appears to be uniform (no obvious color differences).
Keywords:spatial-temporal fusion  semi-physical model  multiplicative modulation  Landsat TM/ETM+  MODIS  surface reflectance data sets
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