Abstract
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.
Highlights
Vegetation, which plays a key role in the terrestrial ecosystem, maintains energy exchange and the global atmospheric, hydrologic, and carbon cycles in many ways [1]
We focus on the annual Normalized Difference Vegetation Index (NDVI) which is the most generally used metric in long-term vegetation studies
The annual NDVI values are relatively high for both products in most of eastern China
Summary
Vegetation, which plays a key role in the terrestrial ecosystem, maintains energy exchange and the global atmospheric, hydrologic, and carbon cycles in many ways [1]. Variations in vegetation constitute good indicators in ecological and environmental assessment from local to global scales [1,2,3,4]. In recent decades, monitoring changes and trends in vegetation have been improved by multiple remotely sensed datasets. Remote sensing technology provides unique insight into the dynamics of vegetation. 1970s, diverse spectral indices have been extensively used to characterize the status of vegetation. The Normalized Difference Vegetation Index (NDVI) exploits the difference in the spectral
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