GRS documentation

GRS (Glint Removal for Sentinel-2-like sensors)

The GRS algorithm Harmel et al., (2018) was specifically developed to handle and correct for the direct sunlight reflected by the water surface and potentially reaching the sensor (i.e., sunglint signal) of Sentinel-2-like mission, that is nadir or near-nadir viewing sensor with SWIR bands. The GRS processor consists of three main modules to correct for:

• gaseous absorption,

• diffuse light from sky and its reflection by the air-water interface and

• the sunglint signal in order to retrieve the water-leaving signal at the water surface level.

Getting started:

• Usage
  • Installation
    • Download the LUT files
    • Installation with conda environment
  • Testing

Tutorials

• Basics
  • Simple use of GRS API
• Auxiliary Data
  • Download necessary CAMS data
• Advanced
  • Development example for GRS step-by-step application to Landsat images
  • absorbing gases correction
  • Water mask
  • L2A to L2B
• Visualization
  • L2A GRS image

API reference

grs.acutils	Atmospheric Correction utilities to manage LUT and atmosphere parameters (aerosols, gases)
grs.auxdata	Module dedicated to auxiliary data management.
grs.cams	Module dedicated to handle CAMS data with link to Copernicus API.
grs.data	Where the LUTs are.
grs.grs_process
grs.mask	Module dedicated to pixel classification.
grs.output	Module to set output product and format.
grs.product	Module to build GRS object from input image.
grs.run	Executable to process Sentinel-2 L1C images for aquatic environment

Interactive data manipulation

Please see the GRS Toolbox package grstbx

Indices and tables

• Index

• Module Index

• Search Page

Funding

• Supporting institutions