ANINTRODUCTIONTOGIS


NDVI maps with Sentinel-2


The Sentinel program of the European Spatial Agency (ESA) gathers several missions that focus on different aspects of Earth observation such as atmospheric, oceanic, and land monitoring. Vegetation monitoring is mainly carried out with the Sentinel-2 mission. Sentinel-2 is composed of two polar-orbiting satellites providing high-resolution optical imagery. In particular, the multispectral aerial images provided by Sentinel 2 can be used to calculate many vegetation indices, including the Normalized Difference Vegetation Index (NDVI), which is commonly used in agriculture. This tutorial shows:

  1. how to download the Sentinel-2 images provided free of charge by ESA
  2. how to create a NDVI map with the open source software QGIS from these data.

It only requires basic knowledge about the use of GIS software (raster and shapefiles visualization…).


I. Download Sentinel 2 multispectral aerial images

On the data download interface of the Copernicus website, first register then follow this procedure:

  1. Manually search the area of interest on the map
  2. Once the area is located, click on the “Switch to area mode” icon at the top right of the map and then select the area of interest
Figure 1 Selection of the area of interest on the Copernicus interface


  1. From the Advanced search criteria, select

    1. Sensing period;
    2. Sentinel 2 mission (for multispectral aerial images);
    3. Do not select any particular satellite (keep both S2A and S2B for more results);
    4. Choose images with a low Cloud Cover rate (e.g. [0 TO 10], for a cloud cover rate below 10%);
    5. Product type: MSI is for multispectral images. Then choose the data that end with 2A (for Level 2A), which corresponds to the reflectance at the bottom of the atmosphere (including atmospheric correction), while the data ending with 1C corresponds to the reflectance at the top of the atmosphere.
      • Until March 2018: choose 2Ap (pilot version);
      • After March 2018: choose 2A (operational version).
Figure 2 Definition of a request with Advanced search criteria


  1. Start a search and look through the results. Before downloading the data, you may check cloud coverage and image extent. Each file size is approximately 600MB (tiles of 100km*100km).


II. Create a NDVI map with QGIS

The following procedure has been performed with QGIS 3.6, but is easily reproducible with previous versions.

Unzip the downloaded file. Inside it, look for the “Granule” folder, then the “IMG_DATA” folder. It contains three sub-folders “R10m”, “R20m” and “R60m” which correspond to three different resolutions (from 10mx10m to 60mx60m per pixel). Sentinel 2 provides reflectance measurements for 13 wavelengths:

Table 1 Spectral bands for Sentinel-2 sensors
Source: The European Space Agency


As shown in Table 1, Sentinel-2 sensors have 4 native 10m bands: B02 (blue), B03 (green), B04 (red) and B08 (near infrared). As only bands B02 and B08 are required for NDVI calculation, maps can be produced with a resolution of 10*10m. Therefore, for the next steps, we will focus on the data in the “R10” folder.

In QGIS, open the two rasters whose names end with…_B04_10m and …_B08_10m (red and near infrared (NIR) reflectance, respectively). You may also open the “True Colors Image” raster (name ending with …TCI_10m. The TCI is an image reproducing the natural aspect from the B02 (Blue), B03 (Green), and B04 (Red) Bands.

If you have not downloaded Sentinel-2 images, you can use a sample of these data (band 4 and 8 available for a small area), which are available in this folder. The Sentinel-2 rasters made available for this tutorial date from March 6, 2021.


NDVI is calculated as follows:
\[ NDVI=\frac{R_{NIR}-R_R}{R_{NIR}+R_R} \]

With QGIS, NDVI can be calculated from the RasterCalculator plugin. This plugin allows to calculate the equation described above from the rasters of the bands B08 (Near InfraRed) and B04 (Red). Procedure is as follows:

Figure 3 Calculation of NDVI with the plugin RasterCalculator


Once the NDVI map has been created a colour legend can be applied from the raster ‘Properties’ tab. In order to better visualize within-field heterogeneities, it is useful to crop the NDVI raster according to the shapefile of field borders (Raster > Extraction > Clip Raster by Mask Layer). The highest NDVI values indicate field zones with the highest vegetation biomass.

Figure 4 Visualization of NDVI values for the whole tile (left picture) or for one field only (right picture)


NDVI is the most commonly used index in agriculture, as it is based on wavelengths related to the photosynthetic activity of plants. However, a large number of other vegetation indices exist.