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遥感技术与应用  2006, Vol. 21 Issue (4): 391-395    DOI: 10.11873/j.issn.1004-0323.2006.4.391
综述     
NDVI 时间序列数据集重建方法述评
顾 娟, 李 新, 黄春林
(中国科学院寒区旱区环境与工程研究所, 甘肃兰州 730000)
Research on the Reconstructing of Time-series NDVI Data
GU Juan, LI Xin, HUANG Chun-lin
(Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China)
 全文: PDF 
摘要:

基于NOAA/AVHRR、SPOT/VEGETATION 以及MODIS 等卫星影像得到的归一化植被指数(NDVI,Normalized Difference Vegetation Index) 时序资料已经在植被动态变化监测、宏观植被覆盖分类和植物生物物理参数反演方面得到了广泛的应用, 但由于受云层、天气等因素的影响,NDVI 数据集存在大量的噪声, 因此对NDVI 时间序列数据集进行重建, 提高NDVI 数据集质量的研究逐步受到关注。对近年来普遍使用的几种NDVI 时间序列数据集重建方法(最大值合成、最佳指数斜率提取、中值迭代滤波、时间窗内的线性内插、傅里叶变换、S2G 滤波) 进行了详细介绍并评述了这些方法的优缺点。

关键词: NDVI时间序列重建    
Abstract:

 Although the Normalized Difference Vegetation Index (NDVI) time-series data derived from NOAA/AVHRR, SPOT/VEGETATION and MODIS, has been successfully used in research regarding global vegetation change, land cover classification and biophysical parameters inversion. However, due to effect of cloud and atmospheric conditions, residual noise in the NDVI time-series data will induce erroneous resultsin our further quantitive analysis. In this paper, some general reconstructing methods are introduced, including Maximum Value Compositing (MVC) , the Best Index Slope Extraction (B ISE) , Media Iteration Filter (MIF) , Temporal Window Operation (TWO ) , Fourier Transform (FT ) and Savitzky-Golay Filter (S2G Filter). With the development of change detection research, it is necessary to reconstruct the NDVI time-series datasets in order to provide high-quality data for the study of vegetation response to global climate change.

Key words: Normalized difference vegetation index (NDVI)    Time-series data    Reconstructing
收稿日期: 2006-02-07 出版日期: 2011-09-27
:  TP 79  
基金资助:

 国家重点基础研究发展项目(2001CB309404)、国家自然科学基金项目(90202014) 和中国科学院寒区旱区环境与工程研究所创新课题(CACX2003102) 资助。

作者简介: 顾娟(1982- ) , 女, 博士研究生, 现从事遥感与地理信息系统应用研究。
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引用本文:

顾 娟, 李 新, 黄春林. NDVI 时间序列数据集重建方法述评[J]. 遥感技术与应用, 2006, 21(4): 391-395.

GU Juan, LI Xin, HUANG Chun-lin. Research on the Reconstructing of Time-series NDVI Data. Remote Sensing Technology and Application, 2006, 21(4): 391-395.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2006.4.391        http://www.rsta.ac.cn/CN/Y2006/V21/I4/391

〔1〕 Myneni R B, Keeling C, Tucker CJ , et al. Increase Plant Growth in the North high Latitudes from 1981 to 1991〔J 〕.Nature, 1997, 386: 698~ 702.
〔2〕 Mark R, Rick C, Mick C, et al. Long-Term Studies of Vegetation Dynamics〔J〕. Science, 2001, 293: 650~ 655.
〔3〕 IGBP J R G. Townshend (Ed). Improved GlobalData for Land Applications〔A 〕. IGBP Global Change Report, vol. 20.Stockho lm, Sweden: International Geosphere-Biosphere Programme
[C ]. 1992.
〔4〕 Myneni R B, Tucker C J , Asrar G, et al. Interannual Variation in Satellite-sensed Vegetation Index Data from 1981 to 1991〔J〕. Journal of Geophysical Research, 1998, 103: 6145~ 6160.
〔5〕 Defries R S, Townshend J R G. NDVI-derived Land-cover Classifications at A Global-scale〔J〕. International Journal of Remote Sensing, 1994, 15 (17) : 3567~ 3586.
〔6〕 JamesM E, Kalluri S N V. The Pathfinder AVHRR Land Data Set- an Improved Coarse Resolution Data Set for Terrestrial Monitoring 〔J 〕. International Journal of Remote Sensing, 1994, 15 (17) : 3347~ 3363.
〔7〕 DiL , Rundquist D C, Han L. Modelling Relationship Between NDVI and Precipitation During Vegetation Cycles〔J〕.International Journal of Remote Sensing, 1994, 15: 2121~2136.
〔8〕 卢玲, 李新, 程国栋. 利用NOAA AVHRR 植被指数数据集分析黑河流域季候特征〔J〕. 中国沙漠, 2002, 22 (2) : 187~ 191.
〔9〕 Fang Jingyun, Piao Shilong, He Jinsheng, et al. Increasing Terrestrial Vegetation Activity in China, 1982~ 1999〔J 〕.Science in China Ser C Life Science, 2004, 47 (3) : 229~ 240.
〔10〕 Telesca L , Lasaponara R. Quantifying Intra-annual Persistent Behaviour in SPOT-VEGETATION NDVI Data for Mediterranean Ecosystems of Southern Italy〔J 〕. Remote Sensing of Environment, 2006, 101: 95~ 103.
〔11〕 Myeong S, David J N , Michael J D. A Temporal Analysis of Urban forest Carbon Storage Using Remote Sensing〔J〕. Remote Sensing of Environment, 2006, 101: 277~ 282.
〔12〕 Potter C S, Brook s V. Global Analysis of Empirical Relations Between Annual Climate and Seasonality of NDVI〔J 〕.International Journal of Remote Sensing, 1998, 19 (15) : 2921~ 2948.
〔13〕 Zhou L M , Tucker C J , Kaufmann R K, et al. Variations in Northern Vegetation Activity Inferred from Satellite Data of Vegetation Index During 1981 to 1999〔J 〕. Journal of Geophysical Research-Atmospheres, 2001, 106 (D17) : 20069~20083.
〔14〕 刘玉洁, 杨忠东. MOD IS 遥感信息处理原理与算法〔M 〕. 北京: 科学出版社, 2001.
〔15〕 毕晓丽, 王辉, 葛剑平. 植被归一化指数(NDV I) 及气候因子相关起伏型时间序列变化分析〔J 〕. 应用生态学报, 2005, 16(2) : 284~ 288.
〔16〕 Deering D W. Rangeland Reflectance Characteristics Measured by Aircraft and Spacecraft Sensors〔〕. Ph D. Dsertation, Texas A &M University, College Station, 1978.
〔17〕 赵英时. 遥感应用分析原理与方法〔M 〕. 北京: 科学出版社,2003.
〔18〕 Gutman G G. Vegetation Indices from AVHRR: An Updateand Future Prospects〔J 〕. Remote sensing of Environment,1991, 60: 35~ 57.
〔19〕 Hui Qing Liu, Alfredo Huete. A Feedback BasedModification of the NDVI to Minimize Canopy Background and Atmospheric Noise〔J〕. IEEE Transactions on Geoscience and Remote sensing, 1995, 33 (2) : 457~ 465.
〔20〕 Cilar J , Ly H, Li Z Q , et al. Multitemporal, Multichannel AVHRR Data Sets for Land Biosphere Studies-artifacts and Corrections〔J 〕. Remote Sensing of Environment, 1997, 60:35~ 57.
〔21〕 Holben B N. Characteristic of Maximum Value Composite Images for Temporal AVHRR Data〔J〕. International Journal
of Remote Sensing, 1986, 7 (11) : 1417~ 1434.
〔22〕 Cihlar J , Manak D, Dapos IM. Evaluation of Compositing Algorithms for AVHRR Data Over Land〔J〕. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32 (2) : 427~437.
〔23〕 Cihlar J C, Manak D, Voisin N. AVHRR Bidirectional Reflectance Effects and Compositing〔J〕. Remote Sensing of Environment, 1994, 48: 77~ 88.
〔24〕 Viovy N , Arino O , Belward A S. The Best Index Slope Extraction (BISE) : A Method for Reducing Noise in NDVI Time Series〔J〕. International Journal of Remote Sensing, 1992,13: 1585~ 1590.
〔25〕 Lovell J L , Graetz R D. Filtering Pathfinder AVHRR L and NDV IData fo rA ustralia〔J〕. International Journal of Remo te Sensing, 2001, 22 (13) : 2649~ 2654.
〔26〕 M ingguoM a, F rank V eroustraete. Reconstructing Pathfinder AVHRR Land NDVI Time-series Data for the Northwest of China〔J 〕. Advances in Space Research, 2006, 37: 835~ 840.
〔27〕 Park J , Tateishi R. Correction of Time Series NDVI by the Method of Temporal Window Operation (TWO) , 1998, P ro2 ceedings of the 1998 Asian Conference on Remote Sensing 〔OL 〕. http: //www. gisdevelopment. net/aars/acrs/1998/ps-2/ps2004. shtml.
〔28〕 Savitzky A , GolayM J E. Smoothing and Differentiation of Data by Simplified Least Squares Procedures〔J 〕. Analytical Chemistry, 1964, 36: 1627~ 1639.
〔29〕 Jonsson P, Eklundh, L. Seasonality Extraction by Function Fitting to Time-series of Satellite Sensor Data〔J 〕. IEEE Transactions on Geoscience and Remote sensing, 2002, 40(8) : 1824~ 1832.
〔30〕 Jin Chen, Per Jobnsson, Masayuki Tamura, et al. A Simple Method for Reconstructing a High-quality NDVI Time-series Data Set Based on the Savitzky-Golay Filter〔J 〕. Remote sensing of Environment, 2004, 91: 332~ 344.
〔31〕 Sellers P J , Tucker C J , Collatz G J , et al. A Global 131 NDVI Dataset for Climate Studies: Part II. The Generation of Global Fields of Terrestrial Biophysical Parameters from the NDVI〔J 〕. International Journal of Remote Sensing,1994, 15 (17) : 3519~ 3545.
〔32〕 Cihlar J. Identification of Contaminated Pixels in AVHRR Composite Images for Studies of Land Biosphere〔J〕. Remote Sensing of Environment, 1996, 56: 149~ 153.
〔33〕 Roerink G J , MenentiM , VerhoefW. Reconstructing Cloud-free NDVI Composites Using Fourier Analysis of Time Series〔J 〕. International Journal of Remote Sensing, 2000,21 (9) : 1911~ 1917.
〔34〕 郑玉坤, 庄大方. 多时相AVHRR 数据的傅立叶分析〔J 〕. 中国科学院研究生院学报, 2003, 20 (1) : 62~ 68.

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