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遥感技术与应用  2013, Vol. 28 Issue (1): 90-96    DOI: 10.11873/j.issn.1004-0323.2013.1.90
图像与数据处理     
融合QA-SDS的MODIS NDVI时序数据重构
樊辉1,2
(1.云南大学亚洲国际河流中心,云南 昆明 650091;
2.云南省国际河流与跨境生态安全重点实验室,云南 昆明 650091)
MODIS NDVI Time-series Data Reconstruction Integrating with the Quality Assessment Science Data Set(QA-SDS)
Fan Hui1,2
(1.Asian International Rivers Center of Yunnan University,Kunming 650091,China;
2.Yunnan Key Laboratory of International Rivers and Transboundary Eco-security,Kunming 650091,China)
 全文: PDF(6787 KB)  
摘要:

基于云南省MOD13Q1时序数据,对比分析了不同质量设置(UI5、UI5-CSS、UI3、UI3-CSS)和不同时序重构方法(简单线性插值、Savitzky-Golay滤波、非对称高斯函数拟合法和双逻辑函数拟合法)组合下NDVI时序重构效果。结果表明:NDVI时序中无效像元数和最大间隙长度在时间和地域上的分布差异受气候干、雨季影响显著。非对称高斯函数拟合法和双逻辑函数拟合法的稳健性和拟合效果较优。NDVI时序中无效像元最大间隙长度是衡量数据质量优劣和时序重构可行性的重要指标,雨季降水和多云天气过于集中是影响云南省境内部分地区时序重构质量提升的关键。基于重构NDVI时序,云南省全境NDVI时空分布呈现雨季大于干季、西部大于东部、南部高于北部、河谷大于山地的特征。

关键词: MODIS NDVI时序分析数据质量评价云南省    
Abstract:

Satellite-derived NDVI time series are often contaminated by negative atmospheric conditions and sunsensor-surface viewing geometries.The reconstruction of high quality NDVI time-series is crucial to the detection of long-term vegetation cover changes and the remote sensing of vegetation phenology.In this paper,MOD13Q1 time-series data covered in Yunnan province were employed to address the performance effectiveness of time-series data reconstruction methods (e.g.linear interpolation,Savitzky-Golay filtering,asymmetric Gaussian and double logistic function-fitting) through integrating with different quality setting (e.g.UI5,UI5-CSS,UI3,UI3-CSS).The results show that seasonal and regional variations in the number and the maximum gap length of invalid pixels of time-series data were mainly controlled by local climate.A comparison of four selected methods revealed that the superiority of the robustness and fitting capability of asymmetric Gaussian and double logistic function-fitting methods over the other fitting techniques.The maximum gap length of invalid pixels in time-series data is an important data quality indicator reflecting the feasibility for meaningful reconstruction.Concentrated clouds and precipitation in the rainy season is a crucial factor of influencing the fitting accuracy of the reconstructed time-series data in some parts of the study area.The reconstructed NDVI time-series data show that the NDVI values are higher in the rainy season than those in the dry season,higher in the western than those in the eastern,higher in the southern than those in the northern, and higher in the river valley than those in the uplands in the study area.

Key words: MODIS NDVI    Time-series analysis    Data quality evaluation    Yunnan province
收稿日期: 2011-12-30 出版日期: 2013-06-21
:  TP 79  
基金资助:

国家自然科学基金项目(41061010)、云南省应用基础研究面上项目(2010ZC002)、“十二五”支撑计划(2011BAC09B07)资助。

作者简介: 樊辉(1972-),男,江西修水人,博士,副研究员,主要从事全球变化与资源环境遥感研究。Email:fanhui@ynu.edu.cn。
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引用本文:

樊辉. 融合QA-SDS的MODIS NDVI时序数据重构[J]. 遥感技术与应用, 2013, 28(1): 90-96.

Fan Hui. MODIS NDVI Time-series Data Reconstruction Integrating with the Quality Assessment Science Data Set(QA-SDS). Remote Sensing Technology and Application, 2013, 28(1): 90-96.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2013.1.90        http://www.rsta.ac.cn/CN/Y2013/V28/I1/90

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