Precipitation rates are derived from satellite-based precipitation estimates of the Rainfall Measuring Mission (TRMM), available on a 0.25-degree geographic grid at three-hourly intervals. Vegetation dynamics are computed based on the Normalized Difference Vegetation Index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 250 m and a temporal resolution of 16 days. As a first step in our analysis, we applied a simple land-cover (LC) classification scheme using thresholds derived from NDVI-based phenologic metrics over ten hydrological years. Then, we delineated areas in which no LC change was detected (i.e., stable LC classes). We then used the stable LC classes for spatial aggregation of phenologic metrics for each TRMM pixel. Finally, precipitation data was aggregated to 16-day precipitation sums and linearly correlated with spatial means of phenologic metrics. Preliminary result show that linear correlation between annual precipitation and annual mean NDVI is between r² = 0.3 and r ² = 0.7, with a lag of 48 to 64 days that depends on both the LC class and the geographic location within the study region.
Our study contributes to a greater understanding of the geoclimatic coherency of precipitation and vegetation at high spatial resolutions. Moreover, our study provides satellite-based information on land cover change in the high Andes, which is important for resource management in this remote and data-sparse region.