Urban Tree Infestation Detection Using Satellite Imagery and Deep Learning

This project teams up the Institut National de la Recherche Scientifique (INRS) and Remote Digital Twin Inc. (RDT) to find a better way to spot sick trees in Canadian cities using satellite images and artificial intelligence (AI). Urban trees are under attack from pests, which hurts air quality and green spaces people love. Today’s methods to check tree health are too slow and can’t keep up with the problem. By using images from satellites like Sentinel-2 and Landsat, combined with smart AI, this project will quickly find infested trees before the damage spreads. For INRS, this boosts their goal of solving real problems with science. For RDT, it creates a new product to help keep urban forests healthy. In the end, this means cleaner air, happier communities, and a fast, affordable way to protect city trees.

Faculty Supervisor:

Saeid Homayouni

Student:

Partner:

Remote Digital Twin Inc.

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

Université du Québec : Institut national de la recherche scientifique

Program: