LandCoM: Land cover mapping

Simon Ricard

Researcher

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Description

The LandCoM project aims to develop an automated method for evaluating by remote sensing the percentage of soil cover by crop residues and cover crops.

Objective(s)

Develop and validate a method for analyzing satellite remote sensing images to distinguish and quantify in the early spring period the percentage of soil cover by grassland, cover crops and crop residues on a return of annual field crops.

Carried out in collaboration with INRS-ETE, the analytical approach of CarTéCoS is based on a three-scale methodology:

  1. micro-scale: the collection and analysis of digital photos taken using smart phones;
  2. mesoscale: the collection and analysis of high-resolution spatial multispectral images obtained by a drone;
  3. macro-scale: the analysis of multi-source and multi-temporal Sentinel 2 and Landsat-8 (optical) and Sentinel 1 radar images by automatic deep learning algorithms in the Google Earth Engine © cloud platform.

From 2021 to 2023

Project duration

Field crops

Activity areas

Partners

  • MAPAQ, PRIME-VERT, Sous-volet 2.2 Approche interrégionale
  • INRS-ETE
  • Opticonseils
  • GestrieSol
  • ProConseil

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