A Simplified Data Assimilation Method for Reconstructing Time-Series MODIS NDVI Data
A Simplified Data Assimilation Method for Reconstructing Time-Series MODIS NDVI Data
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DOI：
10.1109/igarss.2008.4779536
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发表时间：
2008-07
期刊：
影响因子：
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通讯作者：
J. Gu;Xin Li;Chunlin Huang
中科院分区：
文献类型：
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作者：
J. Gu;Xin Li;Chunlin Huang
归一化差异植被指数(NDVI)是应用最广泛的植被指数，因其简单、易用、广为人知。时间序列归一化植被指数产品已被证明是学习过去事件、监测当前自然资源状况、提取树冠生物物理参数和在不同尺度上预测陆地生态系统的有力工具。然而，目前的NDVI产品在时空上仍然是不连续的，主要原因是云量、季节性降雪和大气变异性。本文提出了一种简化的数据同化方法，用于重建高质量的时间序列MODIS NDVI数据。结果表明，该方法是一种简单有效的高质量MODIS NDVI时间序列重建方法。
Normalized difference vegetation index (NDVI) is the most widely used vegetation index due to its simplicity, ease of application, and wide-spread familiarity. Time-series NDVI products have been proven to be a powerful tool to learn from past events, monitor current natural-resource conditions, extract canopy biophysical parameters and forecast terrestrial ecosystems on different scales. However, the current NDVI product is still spatiotemporally discontinuous mainly due to cloud cover, seasonal snow and atmospheric variability. In this work, a simplified data assimilation method is proposed to reconstruct high-quality time-series MODIS NDVI data. Results indicate that the newly developed method is easy and effective in reconstructing high-quality MODIS NDVI time series.