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Models are located here: https://nextcloud.inrae.fr/s/DEy4PgR2igSQKKH

Models

All models use Sentinel-2 and Sentinel-1 images as inputs. The inputs/output of each model architecture are presented below.

CRGA OS2

CRGA OS1

Merunet: Meraner U-Net

Monthly synthesis S2/S1

Monthly synthesis S2

Inputs

  • Sentinel-1 SAR images, pre-processed using the S1Tiling OTB Remote Module
  • Sentinel-2 optical images (L2 level), can be from the THEIA Land Data Center or from ESA scihub
  • DEM: Digital Elevation Model, 20m resolution

How to run a model

Time series processor

This is the highest-level way of running the inference of a model. For example, you can run a CRGA model on a time series like this:

python production/crga_timeseries_processor.py
        --s2_dir  S2_PREPARE/T31TCJ
        --s1_dir  S1_PREPARE/T31TCJ
        --model   crga_os2_occitanie_pretrained/
        --dem     DEM_PREPARE/T31TCJ.tif
        --out_dir reconstructed_timeseries/
# Optional arguments:
        --write_intermediate --overwrite
        --start 2018-01-01 --end 2018-12-31
        --ulx 306000 --uly 4895000 --lrx 320000 --lry 4888000

Processor

For instance, we use crga_processor.py to perform the inference of the crga models. This program not only performs the inference, but also takes care of preparing the right input images to feed the model, and also the post-processing steps (like removing inferred no-data pixels). It is built exclusively using OTB application pipelines, and is fully streamable (no limitation on images size).

Below is an example of use :

python production/crga_processor.py \
--il_s1before \
  /data/s1b_31TEJ_vvvh_DES_139_20201001txxxxxx_from-10to3dB.tif \
  /data/s1a_31TEJ_vvvh_DES_037_20200930txxxxxx_from-10to3dB.tif \
  /data/s1b_31TEJ_vvvh_DES_110_20200929t060008_from-10to3dB.tif \
--il_s1 \
  /data/s1b_31TEJ_vvvh_DES_139_20201013txxxxxx_from-10to3dB.tif \
  /data/s1b_31TEJ_vvvh_DES_110_20201011t060008_from-10to3dB.tif \
  /data/s1a_31TEJ_vvvh_DES_037_20201012txxxxxx_from-10to3dB.tif \
--il_s1after \
  /data/s1b_31TEJ_vvvh_DES_139_20201025txxxxxx_from-10to3dB.tif \
  /data/s1a_31TEJ_vvvh_DES_037_20201024txxxxxx_from-10to3dB.tif \
  /data/s1b_31TEJ_vvvh_DES_110_20201023t060008_from-10to3dB.tif \
--il_s2before \
  /data/SENTINEL2B_20200929-104857-489_L2A_T31TEJ_C_V2-2 \
  /data/T31TEJ/SENTINEL2B_20200926-103901-393_L2A_T31TEJ_C_V2-2 \
--il_s2after \
  /data/SENTINEL2B_20201026-103901-924_L2A_T31TEJ_C_V2-2 \
  /data/SENTINEL2A_20201024-104859-766_L2A_T31TEJ_C_V2-2 \
--in_s2 /data/SENTINEL2B_20201012-105848-497_L2A_T31TEJ_C_V2-2 \
--dem /data/DEM_T31TEJ.tif \
--savedmodel /path/to/saved/model/ \
--output SENTINEL2B_20201012-105848-497_L2A_T31TEJ_C_V2-2_FRE_10m_reconstructed.tif