生态与环境

利用MODIS/EVI 时间序列数据分析 干旱对植被的影响

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  • 1. 中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室, 北京100101|
    2. 中国科学院研究生院, 北京100049
赵伟( 1984-)| 男, 江西上高人, 硕士研究生, 主要从事遥感时间序列数据分析方面研究. E-mail: zhaow.06s@igsnrr.ac.cn

收稿日期: 2007-08-01

  修回日期: 2007-10-01

  网络出版日期: 2007-11-25

基金资助

中国科学院2003 年度“百人计划”项目和国家杰出青年科学基金项目( 40425012) .

Impact of Drought on the Vegetation State Using MODIS/EVI Time- ser ies Data

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  • 1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101|
    2. Graduate School of the Chinese Academy of Sciences, Beijing 100049

Received date: 2007-08-01

  Revised date: 2007-10-01

  Online published: 2007-11-25

摘要

为了分析2006 年四川重庆地区夏季干旱对该地区植被生长的影响, 选取该地区多年中分 辨率成像光谱仪(MODIS)增强植被指数( EVI) 时间序列数据进行研究, 利用时间序列谐波分析 (HANTS) 算法对EVI 数据进行去云处理, 并根据处理后的结果( 重构的EVI 数据以及HANTS 分 析得到相应频率对应的振幅和相位) , 分析干旱对该地区的影响, 同时结合地面气象数据加以补 充说明。将干旱年份和正常年份对比分析, 结果表明, 处理后的EVI 时间序列数据能较好地反映 干旱对地表植被的影响, 振幅和相位的空间分布特征能够很好地反映干旱的影响范围。

本文引用格式

赵伟, 李召良 . 利用MODIS/EVI 时间序列数据分析 干旱对植被的影响[J]. 地理科学进展, 2007 , 26(6) : 44 -55 . DOI: 10.11820/dlkxjz.2007.06.005

Abstract

MODIS/EVI time series data were selected to analyze the response of vegetation growth to drought in Sichuan and Chongqing provinces in 2006. To remove the cloud contaminated images, the HANTS algorithm was first used to reconstruct cloud- free images. With the cloud- free images and HANTS algorithm’s components (amplitude and phase), the drought influence to the study region was analyzed combined with the land surface meteorological data. Comparing the performance of the drought year and normal years, the result showed that the processed EVI data could reflect the influence of drought to surface vegetation well, and the amplitude and phase could indicate the spatial distribution of drought.

Key words: EVI; HANTS; MODIS; NDVI; Time series data

参考文献


[1] Leonard S. Unganai, Felix N. Kogan. Drought Monitoring and Corn Yield Estimation in Southern Africa from AVHRR Data. Remote Sensing of Environment, 1998, 63:219~232.

[2] X Song, G Saito, M Kodama & H Sawada. Early detection system of drought in East Asia using NDVI from NOAA/AVHRR data. International Journal of Remote Sensing, 2004, 25(16): 1911~1917.

[3] Verhoef W, Menenti M, Azzah S.A colour composite of NOAA—AVHRR—NDVI based on time series analysis 1981~1992. International Journal of Remote Sensing, 1996, 17: 231~235.

[4] 赵英石等. 遥感应用分析原理与方法. 北京: 科学出版社, 2003.

[5] 刘玉洁, 杨忠东等. MODIS 遥感信息处理原理和算法. 北京: 科学出版社, 2001.

[6] 王正兴, 刘闯, HUETE Alfredo. 植被指数研究进展: 从AVHRR- NDVI 到MODIS- EVI. 生态学报, 2003, 23( 5) : 979~987.

[7] Alfredo Huete, Chris Justice,Wim van Leeuwen.MODIS VEGETATION INDEX (MOD 13) ALGORITHM THEORETICAL BASIS DOCUMENT Version 3.April 30, 1999.

[8] Huete A, Justice C, &Liu H. Development of vegetation and soil indices for MODIS- EOS. Remote Sensing of Environment, 1994, 49, 224~234.

[9] 李红军, 郑力, 雷玉平等.基于EOS/MODIS 数据的NDVI 与EVI 比较研究. 地理科学进展, 2007, 26( 1) : 26~32.

[10] 王长耀, 林文鹏. 基于MODIS EVI 的冬小麦产量遥感预测研究. 农业工程学报, 2005, 21( 10) : 90~94.

[11] Roerink G J, Menenti M. Reconstructing cloudfree NDVI composites using Fourier analysis of time series. International Journal of Remote Sensing, 2000, 21(9): 1911~1917.

[12] 王丹, 姜小光. 利用NOAA 数据分析中国地区植被覆盖变化周期. 中国图像图形学报, 2006, 11( 4) : 516~520.

[13] 于信芳, 庄大方. 基于MODIS/NDVI 数据的东北森林物候期监测. 资源科学,2006,28 ( 4) : 111~117.

[14] Aaron Moody, David M Johnson. Land surface phenologies from AVHRR using the discrete Fourier transform. Remote Sensing of Environment, 2001, 75, 305~323.

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