Following on from the article \u201cHow to increase the resolution of Sentinel 2 images from 10 to 1m,\u201d let’s look at a concrete example of how to use it.<\/p>\n\n\n\n

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Work plan<\/a>
- Step 1: Prepare the environment<\/a><\/li>
- Step 2: Install S2DR3 and define the study area<\/a><\/li>
- Step 3: Start processing<\/a><\/li>
- Step 4: View and compare<\/a><\/li>
- Step 5: Scientific validation<\/a><\/li><\/ul><\/li>
- Google Colab: S2DR3 \u2013 Sentinel-2 Super Resolution (Blue Bay \/ \u00cele aux Aigrettes)<\/a><\/li>
- Results in Google Drive<\/a><\/li>
- Visual comparison<\/a><\/li>
- Best practices<\/a><\/li><\/ul><\/nav><\/div>\n\n\n\n\n
  \n\n\n\n
  <\/span>Work plan<\/span><\/h2>\n\n\n\n
  <\/span>Step 1: Prepare the environment<\/span><\/h3>\n\n\n\n
  - Open Google Colabhttps:\/\/colab.research.google.com<\/a><\/li>\n\n\n\n
  - Mount your Drive to store the results<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>Step 2: Install S2DR3 and define the study area<\/span><\/h3>\n\n\n\nThe script will contain:<\/p>\n\n\n\n\nThe installation of the s2dr3 package<\/li>\n\n\n\n The coordinates of the area of interest<\/li>\n\n\n\nThe Sentinel-2 acquisition date (ideally cloud-free)<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>Step 3: Start processing<\/span><\/h3>\n\n\n\nThe script will automatically download the Sentinel-2 scene closest to the date, then apply super-resolution at 1 m\/pixel.<\/p>\n\n\n\n The products will be saved to your Drive, in an output\/ subfolder.<\/p>\n\n\n\n \n\n\n\n<\/span>Step 4: View and compare<\/span><\/h3>\n\n\n\nWe will see:<\/p>\n\n\n\n\nhow to display a 10 m vs. 1 m RGB composition directly in Colab;<\/li>\n\n\n\n how to open and compare GeoTIFFs in QGIS + SCP (for classification, NDVI, coral indices, etc.);<\/li>\n\n\n\nwhich bands to use to observe corals (mainly B2-B3-B4, B8, B11, B12).<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>Step 5: Scientific validation<\/span><\/h3>\n\n\n\nFinally, we will see:<\/p>\n\n\n\n \nhow to check whether the details generated are plausible (avoiding confusion between artifacts and real structures);<\/li>\n\n\n\n how to quantitatively compare indices (e.g., NDWI, BSI) between standard Sentinel-2 and S2DR3.<\/li>\n<\/ul>\n\n\n\n \n\n\n\nThe Blue Bay\/\u00cele aux Aigrettes area is perfect for observing the coral reefs of Mauritius, and the date of October 14, 2025 is recent, so it is likely to be covered by a Sentinel-2 acquisition without too many clouds.<\/p>\n\n\n\n Below is your complete and annotated Colab notebook, ready to copy and paste into https:\/\/colab.research.google.com.<\/p>\n\n\n\n It will allow you to generate Sentinel-2 images at 1 m resolution with S2DR3, save them to your Drive, then open and compare them in QGIS + SCP.<\/p>\n\n\n\n In Collab, link your notebook to your Google Drive.<\/p>\n\n\n\n <\/a><\/figure>\n\n\n\nNow, to ensure that processing does not take too long, you need to enable a GPU in the runtime environment. Look in the lower right corner of your notebook, you will see something like \u201cPython 3\u201d with a chip icon. Click on it and select Change Runtime Environment Type. A window will open where you will need to search for Hardware Accelerator and select GPU T4. Save the changes and the notebook will automatically restart with the new configuration.<\/p>\n\n\n\n<\/a><\/figure>\n\n\n\n<\/p>\n\n\n\n \n\n\n\n<\/span>Google Colab: S2DR3 \u2013 Sentinel-2 Super Resolution (Blue Bay \/ \u00cele aux Aigrettes)<\/span><\/h2>\n\n\n\nCopy this code into a new cell in your notebook (you can do this in one or more code cells) and run it:<\/p>\n\n\n\n <\/div>S2DR3 - Super-r\u00e9solution Sentinel-2 \u00e0 1 m<\/div><\/div><\/div><\/strong><\/p>\n\n\n\n# =========================================================\n# S2DR3 - Super-r\u00e9solution Sentinel-2 \u00e0 1 m\n# \u00c9tude des coraux \u00e0 Blue Bay \/ \u00cele aux Aigrettes\n# =========================================================\n\n# --- 1. Monter Google Drive ---\nfrom google.colab import drive\ndrive.mount('\/content\/drive')\n\n# Cr\u00e9e un dossier pour les r\u00e9sultats\n!mkdir -p \/content\/drive\/MyDrive\/Sentinel2_Coraux_S2DR3\/output\n\n# Lien symbolique pour un acc\u00e8s rapide\n!ln -s \/content\/drive\/MyDrive\/Sentinel2_Coraux_S2DR3\/output \/content\/output\n\n# --- 2. Installer le paquet S2DR3 ---\n!pip -q install https:\/\/storage.googleapis.com\/0x7ff601307fa5\/s2dr3-20250905.1-cp312-cp312-linux_x86_64.whl\n\n# --- 3. Importer le module principal ---\nimport s2dr3.inferutils\n\n# --- 4. D\u00e9finir la zone d'int\u00e9r\u00eat (Blue Bay \/ \u00cele aux Aigrettes) ---\n# Coordonn\u00e9es approximatives du centre de la zone (longitude, latitude)\nlonlat = (57.73, -20.44)\n\n# --- 5. D\u00e9finir la date Sentinel-2 ---\ndate = '2025-10-14'\n\n# --- 6. Lancer le traitement ---\n# Cela t\u00e9l\u00e9charge la sc\u00e8ne Sentinel-2 la plus proche de cette date\n# et g\u00e9n\u00e8re une version super-r\u00e9solue \u00e0 1 m\/pixel.\ns2dr3.inferutils.test(lonlat, date)\n\n# Les r\u00e9sultats sont enregistr\u00e9s dans \/content\/output\/\n# (li\u00e9 \u00e0 ton Google Drive : MyDrive\/Sentinel2_Coraux_S2DR3\/output)<\/code><\/pre>\n\n\n\n <\/div><\/div><\/p>\n\n\n\n <\/a><\/figure>\n\n\n\nAt the end of processing, you will see: <\/p>\n\n\n\n<\/a><\/figure>\n\n\n\n \n\n\n\n<\/span>Results in Google Drive<\/span><\/h2>\n\n\n\nOnce processing is complete, you will find:<\/p>\n\n\n\n\n1 m GeoTIFF files (per band or composites),<\/li>\n\n\n\n sometimes an RGB preview,<\/li>\n\n\n\nand the original Sentinel-2 metadata.<\/li>\n<\/ul>\n\n\n\n<\/a><\/figure>\n\n\n\nYou can then:<\/p>\n\n\n\n\nOpen these files in QGIS;<\/li>\n\n\n\n Install or activate the Semi-Automatic Classification Plugin (SCP);<\/li>\n\n\n\n Load the S2DR3 bands into SCP (as multispectral rasters) to calculate NDVI, NDWI, BSI, or coral indices (B3\/B2, B11\/B8, etc.);<\/li>\n\n\n\nCompare with the original Sentinel-2 version (10 m) that you can download via Copernicus Hub or SCP Download.<\/li>\n<\/ol>\n\n\n\n \n\n\n\n<\/span>Visual comparison<\/span><\/h2>\n\n\n\nAt the bottom of the code window, you will find an initial comparison between the 10 m and 1 m resolutions.<\/p>\n\n\n\n<\/a><\/figure>\n\n\n\nClick on the blue link to access a more detailed comparison.<\/p>\n\n\n\n<\/a><\/figure>\n\n\n\n\nUse the RGB composition (B4 = red, B3 = green, B2 = blue).<\/li>\n\n\n\n Overlay the 10 m version and the 1 m version: you will see more detail on the reefs, sandy bottoms, and grassy areas.<\/li>\n\n\n\n For a rigorous comparison:\n\ncalculate NDWI or NDVI on both images,<\/li>\n\n\n\n then evaluate the differences in SCP (Band calc or Raster Calculator tool).<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>Best practices<\/span><\/h2>\n\n\n\n\nCheck cloud cover: the S2DR3 model does not correct for clouds.<\/li>\n\n\n\n Fine details are inferred by the model (not measured), so use them as a visual cue rather than an absolute measurement.<\/li>\n\n\n\n For publication or scientific projects, always cite the use of S2DR3 (Sentinel-2 Deep Resolution 3.0) and mention that it is an AI reconstruction.<\/li>\n<\/ul>\n\n\n\n \n\n\n\nIn the next article, we will see how to continue this work in QGis with the SCP (Semi-Automatic Classification Plugin).<\/p>\n\n\n\n \n","protected":false},"excerpt":{"rendered":"Following on from the article \u201cHow to increase the resolution of Sentinel 2 images from 10 to 1m,\u201d let’s look at a concrete example of how to use it. 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<\/span>Work plan<\/span><\/h2>\n\n\n\n<\/span>Step 1: Prepare the environment<\/span><\/h3>\n\n\n\n\nCreate a folder on your Google Drive: MyDrive\/Sentinel2_Coraux_S2DR3<\/code><\/li>\n\n\n\n

<\/span>Step 1: Prepare the environment<\/span><\/h3>\n\n\n\n\nCreate a folder on your Google Drive: MyDrive\/Sentinel2_Coraux_S2DR3<\/code><\/li>\n\n\n\n

<\/span>Step 2: Install S2DR3 and define the study area<\/span><\/h3>\n\n\n\nThe script will contain:<\/p>\n\n\n\n\nThe installation of the s2dr3 package<\/li>\n\n\n\nThe coordinates of the area of interest<\/li>\n\n\n\n

<\/span>Step 4: View and compare<\/span><\/h3>\n\n\n\nWe will see:<\/p>\n\n\n\n\nhow to display a 10 m vs. 1 m RGB composition directly in Colab;<\/li>\n\n\n\nhow to open and compare GeoTIFFs in QGIS + SCP (for classification, NDVI, coral indices, etc.);<\/li>\n\n\n\n

<\/span>Results in Google Drive<\/span><\/h2>\n\n\n\nOnce processing is complete, you will find:<\/p>\n\n\n\n\n1 m GeoTIFF files (per band or composites),<\/li>\n\n\n\nsometimes an RGB preview,<\/li>\n\n\n\n