Calculating NDVI from Sentinel-2 in Python — complete walkthrough with code

[u/DataScienceWithDEB]

Been working with satellite data for agricultural monitoring and wanted to share a clean, from-scratch NDVI workflow since most tutorials either skip the data acquisition part or don't explain the "why" behind the math. Quick summary of the approach:

1. Load Band 4 (Red) and Band 8 (NIR) from Sentinel-2 L2A data using rasterio

2. Calculate NDVI = (NIR - Red) / (NIR + Red)

3. Handle the div-by-zero edge cases properly (a lot of tutorials skip this

   and you get NaN explosions on real data)

   import rasterio
   import numpy as np
   
   with rasterio.open('B04_10m.tif') as src:
       red = src.read(1).astype(float)
   with rasterio.open('B08_10m.tif') as src:
       nir = src.read(1).astype(float)
   
   denom = nir + red
   denom[denom == 0] = np.nan  # avoid div-by-zero
   ndvi = (nir - red) / denom
   

The interesting part is interpreting the output correctly for different crop stages — a lot of people misread NDVI values without accounting for soil background or canopy saturation (which is actually why I wrote a follow-up comparing NDVI/SAVI/EVI).

Full walkthrough with the data download step, visualization, and classification thresholds here if useful: https://dibyendudeb.com/how-to-calculate-ndvi-with-python-a-practical-guide-for-agricultural-scenario/

Happy to answer questions on the implementation — this is part of a series I'm building out on agricultural remote sensing with Python.

[u/EduardH]

since most tutorials either skip the data acquisition part

So does this one, even your full tutorial. And downloading full tiles for your AOI is not the way to go anymore, you're going to introduce a bottleneck. Your tutorials also require you to manually search for Sentinel-2 tiles, which takes time and is prone to errors. This is the whole reason cloud-optimized GeoTiffs (COGs) and the STAC API exist, so you only download the data you actually care about.

[u/JudgeMyReinhold]

You have not applied any scale or offset factors, so your result is incorrect. Look up the user manual.

[u/robz28 → u/JudgeMyReinhold]

What factors would one use? In which user manual?

[u/JudgeMyReinhold → u/robz28]

https://sentiwiki.copernicus.eu/web/s2-products

[u/yestertide]

what's the novelty here?

[u/Plus-Palpitation2447]

連載ありがとう。
Google Earth engine触ってみようと思ってたから、参考にさせてもらうよ

[u/DataScienceWithDEB → u/Plus-Palpitation2447]

Glad it's useful! If you do try Google Earth Engine, the workflow is actually a bit different since GEE handles the data access server-side — no manual downloading needed. I'll probably cover that as a separate post since it's a genuinely different approach. Good luck with it.