LandCoM: Land cover mapping
Simon Ricard
Researcher
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:
- micro-scale: the collection and analysis of digital photos taken using smart phones;
- mesoscale: the collection and analysis of high-resolution spatial multispectral images obtained by a drone;
- 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
This may interest you
Cost-benefit analysis of proposed actions to reduce the phosphorus load entering Missisquoi Bay from the Rivière de la Roche watershed
The Rivière de la Roche sub-watershed has one of the highest phosphorus and sediment export rates of the entire Missisquoi Bay watershed—a particularly challenging situation for the local agricultural sector.
Researchers: Aubert Michaud, retraité Luc Belzile
Validation of soil health indicators as a nitrogen uptake prediction tool
The objective of this project is to develop a prediction model for soil nitrogen supplies based on biological soil health indicators.
Researcher: Christine Landry
Economic analysis of agronomic practices that prevent soil degradation
Economic analysis of a three-year project aimed at testing methods of reducing and correcting surface soil compaction.
Researcher: Luc Belzile