Grant: College & Community Social Innovation Fund
Sir Sandford Fleming College of Applied Arts and Technology
$120,000.00
Advancing Automation in the Detection and Surveillance of "Canada's Worst Invasive Plant"
EF 2024-25
Résumé
Phragmites australis (P. australis), a tall perennial grass also known as the common reed or Phragmites, or “Canada’s worst invasive plant”, is highly prevalent and considered a threat to Canada’s wetlands, as it aggressively takes over by killing or hindering the growth of native vegetation. P. australis can be seen in community parks, in ditches along roadways and highways, and infringing on agriculture fields. The plant spreads through forming dense patches that impact habitat quality, especially for fish and birds.
For conservation authorities, community groups, and environmental organizations such as the Nature Conservancy of Canada (NCC) and Ducks Unlimited Canada (DUC), battling the spread of P. australis has become an unwanted focus of their activities. Conservation projects now have the added expense and challenge of removing the invasive plant from areas of interest, which may already face other conservation challenges and remediation needs. This additional challenge is increasing project budgets and extending project timelines.
To appropriately manage invasive plant species in a sustainable and efficient manner, early detection and rapid response is critical. Not having the ability to quickly map, identify, classify, and capture the distribution of P. australis is a significant challenge facing wetland conservationists and policy makers. Traditional detection methods involve physically accessing the site and finding and identifying the correct species. There is a growing need for cost-effective tools to identify, map, and monitor invasive plants, as well as developing standardized methods to facilitate a coordinated response across organizations in Ontario and across Canada.
In this collaborative project led by Fleming College, researchers will leverage machine vision algorithms and remote sensing data to develop a platform to use drones to automatically identify and document the presence of P. australis and catalog the location. The project seeks to overcome the limitations of traditional manual methods used to manage invasive species by offering a solution for rapid and comprehensive monitoring. Ultimately, it is expected that this project's outcomes will provide NCC’s and DUC’s conservationists and resource managers with valuable tools for effectively combating the spread of invasive plants and preserving the biodiversity and ecological integrity of wetland habitats in Ontario, and across Canada.
Programme
College & Community Social Innovation Fund
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
CCSIF-2024-00238
Name nom
Diba, Fereydoon
Department département
Applied Research and Innovation - Fleming College (Sir Sandford Fleming College of Applied Arts and Technology)
Organization id
4915
Institution établissement
Sir Sandford Fleming College of Applied Arts and Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
120000
Program id
CCSIF
Program name en
College & Community Social Innovation Fund
Program name fr
Programme d'innovation dans les collèges et la communauté - Fonds d'innovation sociale
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
CCSIF-2024
Committee name en
CCSIF Review Committee
Committee name fr
Comité d’évaluation FISCC
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Non disponible
Research subject en
Not available
Research subject fr
Non disponible
Field of research list codes
RDF1050811
Field of research list names en
Wildlife and habitat management
Field of research list names fr
Gestion de la faune et de l’habitat
Socioeconomic objective list codes
RDS10299
Socioeconomic objective list names en
Environment protection, n.e.c.
Socioeconomic objective list names fr
Protection de l'environnement, n.c.a.
Application title
Advancing Automation in the Detection and Surveillance of "Canada's Worst Invasive Plant"
Keywords
Machine Vision; Remote Sensing; Drone Surveillance ; Unmanned Aerial Vehicles; Invasive Plant; Wetland; Conservation; Phragmites; Ecology; Ecosystem Management
Application summary
Phragmites australis (P. australis), a tall perennial grass also known as the common reed or Phragmites, or “Canada’s worst invasive plant”, is highly prevalent and considered a threat to Canada’s wetlands, as it aggressively takes over by killing or hindering the growth of native vegetation. P. australis can be seen in community parks, in ditches along roadways and highways, and infringing on agriculture fields. The plant spreads through forming dense patches that impact habitat quality, especially for fish and birds.
For conservation authorities, community groups, and environmental organizations such as the Nature Conservancy of Canada (NCC) and Ducks Unlimited Canada (DUC), battling the spread of P. australis has become an unwanted focus of their activities. Conservation projects now have the added expense and challenge of removing the invasive plant from areas of interest, which may already face other conservation challenges and remediation needs. This additional challenge is increasing project budgets and extending project timelines.
To appropriately manage invasive plant species in a sustainable and efficient manner, early detection and rapid response is critical. Not having the ability to quickly map, identify, classify, and capture the distribution of P. australis is a significant challenge facing wetland conservationists and policy makers. Traditional detection methods involve physically accessing the site and finding and identifying the correct species. There is a growing need for cost-effective tools to identify, map, and monitor invasive plants, as well as developing standardized methods to facilitate a coordinated response across organizations in Ontario and across Canada.
In this collaborative project led by Fleming College, researchers will leverage machine vision algorithms and remote sensing data to develop a platform to use drones to automatically identify and document the presence of P. australis and catalog the location. The project seeks to overcome the limitations of traditional manual methods used to manage invasive species by offering a solution for rapid and comprehensive monitoring. Ultimately, it is expected that this project's outcomes will provide NCC’s and DUC’s conservationists and resource managers with valuable tools for effectively combating the spread of invasive plants and preserving the biodiversity and ecological integrity of wetland habitats in Ontario, and across Canada.