Relating Vegetation Dynamics to Climate Variables in Taiwan Using 1982–2012 NDVI3g Data

This research aims to improve our understanding of vegetation dynamics and associated climate variables in Taiwan by utilizing mean-variance analysis (MVA), relative directional persistence analysis, and Pearson's product moment correlation analysis on the Advanced Very High Resolution Radiometer (AVHRR)-derived NDVI3g data from 1982 to 2012. The results indicate a slightly increasing mean-normalized difference vegetation index (NDVI) value with a relatively higher variance during the 1990s and lower variance during the 2000s, which may be explained by the observed fluctuation in precipitation. Additionally, NDVI patterns are identified as increasing in the first half of the year and decreasing in the second half of the year. Spatially, decreasing patterns are observed in all regions except that the northern counties exhibit an increasing NDVI pattern supported by the observed increase in precipitation. Moreover, sunshine duration and temperature are positively correlated with NDVI, whereas precipitation and cloud amount exhibit a negative correlation with NDVI in Taiwan. In the context of global environmental change, this research highlights the utility of applying a combined spatial-temporal approach to remote sensing products. This is an approach with potential applications such as landscape management, conservation practice, and water resource management for policy makers and stakeholders in and beyond Taiwan.