Guo Xiaoyi, Zhang Hongyan, Wu Zhengfang, Zhao Jianjun, Zhang Zhengxiang
School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
Sensors (Basel). 2017 Jun 6;17(6):1298. doi: 10.3390/s17061298.
Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI products in China, which could provide useful information for the choice of NDVI products in subsequent studies of vegetation dynamics.
来自多个卫星传感器的归一化植被指数（NDVI）时间序列是研究植被动态的关键数据。陆地长期数据记录第4版（LTDR V4）NDVI数据集最近以0.05×0.05°的空间分辨率和每日时间分辨率发布。在本研究中，对由LTDR V4和中分辨率成像光谱仪（MODIS）NDVI数据集（MOD13C1）合成的2001年至2014年中国年度NDVI时间序列进行了比较和评估。LTDR V4和MOD13C1数据集之间的NDVI空间模式总体上匹配。高NDVI值和低NDVI值之间的过渡带通常与半干旱和亚湿润地区的边界相匹配。根据基于像素的相关性分析，发现两个数据集之间存在显著且较高的决定系数。由于2005年至2006年期间NOAA AVHRR传感器的变化，LTDR V4的空间平均NDVI相对于MOD13C1数据集的空间平均NDVI具有弱得多的正回归斜率。由于中国西部大气水汽含量相对较低，LTDR V4实测的NDVI值在中国西部始终高于MOD13C1，而在中国东部则出现相反的观测结果。总体而言，18.54%的LTDR V4 NDVI像素呈现显著趋势，而35.79%的MOD13C1 NDVI像素呈现显著趋势。在东北平原、环渤海经济圈、黄土高原和长江三角洲，两个数据集的显著趋势之间观察到良好的一致性。相比之下，这两个数据集在西北沙漠地区和中国南方存在差异。根据植被类型对回归斜率值进行的趋势分析表明，LTDR V4和MOD13C1数据集之间具有良好的一致性。本研究展示了中国AVHRR LTDR和MODIS MOD13C1 NDVI产品在空间和时间上的一致性和差异，可为后续植被动态研究中NDVI产品的选择提供有用信息。
