Data Preprocess

This section explain preprocessing guideline in this project for each dataset.

The data used for development consists of image data from 3 satellites. Sentinel-1, Sentinel-2 from ESA and GEDI from NASA. Sentinel-1 and Sentinel-2 serve as predictor variables and GEDI serves as a ground truth reference,

Sentinel 1

  • Input of the model : Model will inference AGB from pattern and relation in each band.​

  • Using raw Band : Relation of the band related to ​ AGB will extract from model in training process.​

  • Use in training and inference process​

  • Stack with sentinel 2​

  • Temporal coverage for 6 month to keep seasonal information consistent.

  • Interferometric Wide Swath ​

  • Ascending : VV + VH total 2 layer​

  • Median Composite​

  • Thermal noise removal

Sentinel 2

  • Input of the model : Model will inference AGB from pattern and relation in each band.​

  • Using raw Band : Relation of the band related to ​ AGB will extract from model in training process.​

  • Stack with sentinel 1​

  • Use in training and inference process​

For Training ​

  • Temporal coverage for 6 month to keep seasonal information consistent.

  • Filter cloud < 50 %​

  • Median Composite​

For Inference​

  • Use sentinel2 image with minimum cloud coverage ​

GEDI

  • Target reference of the model. Use L4A layer to represent above ground biomass density .​