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遥感技术与应用  2015, Vol. 30 Issue (2): 267-276    DOI: 10.11873/j.issn.1004-0323.2015.2.0267
图像与数据处理     
基于AVHRR和TM数据的时间序列较高分辨率NDVI数据集重构方法
郭文静1,2,李爱农1,赵志强1,2,王继燕1,2
(1.中国科学院水利部成都山地灾害与环境研究所,成都610041;
2.中国科学院大学,北京100049)
Constructing the Time-series NDVI Dataset with a High Spatial and Temporal Resolution through Fusing AVHRR with TM Data
Guo Wenjing1,2,Li Ainong1,Zhao Zhiqiang1,2,Wang Jiyan1,2
( 1.Institute of Mountain Hazards and Environment,Chinese Academy of Science,Chengdu 610041,China;2.University of Chinese Academy of Sciences,Beijing 100049,China )
 全文: PDF(30552 KB)  
摘要:

由于技术条件的限制,一个传感器很难同时具有高空间分辨率和高时间分辨率。然而,在高分辨率尺度上监测地表景观季节性变化的能力是全球的迫切需要,融合周期短、覆盖范围广与分辨率高、周期长的遥感数据是一种较好的方法。基于AVHRR时间分辨率高和TM空间分辨率高及其数据积累时间长的特点,选择若尔盖高原为研究区域,在改进ESTARFM方法的基础上,对TM NDVI和AVHRR NDVI进行融合,构建高时空分辨率的NDVI数据集。研究结果表明:该方法能有机结合AVHRR NDVI的时间变化信息与TM NDVI的空间差异信息,有效实现高时空分辨率NDVI数据集的重构,3景预测高分辨率NDVI与MODIS NDVI产品相关系数分别达到了0.89、0.91和0.85。该方法能够在时间上保留高时间分辨率数据的时间变化信息,同时在空间上反映高空间分辨率数据的空间差异信息,从而为有效构建相对高分辨率时间序列NDVI数据集提供了可能的方法。

关键词: NDVI数据融合高时空分辨率时间序列ESTARFM    
Abstract:

Due to technique and budget limitations,Remotely sensed data,with high spatial and temporal resolutions,can hardly be provided by only sensor.However,the ability to monitor seasonal landscape changes at fine resolution is urgently needed for global change.One approach is to ”blend” the data from coarse\|resolution sensors with frequent coverage (e.g.AVHRR) with data from high\|resolution sensors with less frequent coverage (e.g.Landsat).To combine the high spatial resolution of Landsat and high temporal resolution of AVHRR data,this paper selected a study area in Zoige ,Sichuan province,China.A method for blending NDVI of different spatial and temporal resolution to produce high temporal\|spatial resolution NDVI data set which has been developed based on ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model).The result shows that the new method can combine the temporal information of AVHRR NDVI and spatial information of TM NDVI and realize the reconstruction of high spatial and temporal resolution NDVI data set (the correlation coefficient of three pairs of MODIS NDVI and predicted TM NDVI are 0.89,0.91 and 0.85).This method maintains the temporal trend of high temporal resolution data and the detailed spatial difference information of high spatial resolution data,thereby providing an effective tool to build a relatively high resolution NDVI time series data set.

Key words: NDVI    Data fusion    High temporal and spatial resolution    Time series    ESTARFM
收稿日期: 2014-03-17 出版日期: 2015-05-08
:  TP 701  
基金资助:

国家自然科学基金项目(41271433),中国科学院战略性先导科技专项(XDA05050105 ),全国生态环境十年变化(2000~2010年)遥感调查与评估项目(STSN\|01\|04)联合资助。

通讯作者: 李爱农(1974-),男,安徽庐江人,研究员,博导,中国科学院和四川省"百人计划"入选者,主要从事山地定量遥感与山区生态环境研究。Email:ainongli@imde.ac.cn。   
作者简介: 郭文静(1988-),女,河南洛阳人,硕士研究生,主要从事山地遥感研究。Email:guowenjing11@mails.ucas.ac.cn。
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引用本文:

郭文静,李爱农,赵志强,王继燕. 基于AVHRR和TM数据的时间序列较高分辨率NDVI数据集重构方法[J]. 遥感技术与应用, 2015, 30(2): 267-276.

Guo Wenjing,Li Ainong,Zhao Zhiqiang,Wang Jiyan. Constructing the Time-series NDVI Dataset with a High Spatial and Temporal Resolution through Fusing AVHRR with TM Data. Remote Sensing Technology and Application, 2015, 30(2): 267-276.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.2.0267        http://www.rsta.ac.cn/CN/Y2015/V30/I2/267

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