NDVI & Rainfall Time Series in Google Earth Engine Full Analysis Explained

In this tutorial, I demonstrate how to perform NDVI and rainfall time series analysis using Google Earth Engine for Baton Rouge, USA. The analysis combines: NDVI (Normalized Difference Vegetation Index) derived from Sentinel-2 imagery Rainfall data from CHIRPS The results are visualized as time series charts showing vegetation dynamics and precipitation variability over time. 📊 Interpretation of Results (FROM YOUR CHARTS) 🌿 NDVI Time Series NDVI values are mostly between 0.4 and 0.6, indicating moderate vegetation cover The vegetation pattern is relatively stable with minor seasonal fluctuations A sharp drop in NDVI is visible in the chart 👉 This is NOT real vegetation loss 👉 It is caused by: Cloud contamination Missing satellite observations Data gaps after masking 🌧️ Rainfall Time Series Rainfall shows strong variability across months Peaks exceed 100–120 mm, indicating wetter periods Lower values represent dry conditions The pattern reflects seasonal rainfall cycles 🧠 Key Insight (Very Important for Your Video) There is a clear relationship between rainfall and vegetation: Higher rainfall → Increased NDVI (greener vegetation) Lower rainfall → Reduced NDVI (vegetation stress) SCRIPT: https://code.earthengine.google.com/1...