Evaluating temporal consistency of long-term global NDVI datasets for trend analysis
As a way to understand vegetation changes, trend analysis on NDVI (normalized difference vegetation index) time series data have been widely performed at regional to global scales. However, most long-term NDVI datasets are based upon multiple sensor systems and unsuccessful corrections related to sensor shifts potentially introduce substantial uncertainties and artifacts in the analysis of trends.
