This site requires Cookies enabled in your browser for login.
Updating ...
WaterNet Home
WaterNet
for
pour le
Canada
Menu
WaterNet
Home
GWFO
Home
Catalogue
Master Index
Data
Centre
X
Find Data By Variable Find Data By Site, Facility, or Deployable Show Near-realtime Telemetry (7 day)
Collections
X
Defaults
Select All
Websites
X
Global Water Futures Observatories (GWFO) Global Water Futures (GWF) Global Institute for Water Security (GIWS) International Network of Alpine Research Catchment Hydrology
Legacy Research Programs
X
Changing Cold Regions Network (CCRN) Drought Research Initiative (DRI) International Network of Alpine Research Catchment Hydrology (Legacy Site) Improving Processes & Parameterization for Prediction in Cold Regions Hydrology (IP3) The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS)
Legacy sites
Map
Utilities
X
Account Settings Create a New Record Record List Alias List Editor
Edit Data Centre
Data Types
. . .
X
Clear
Select All
Advanced Search
Go to Top⇡
Related items loading ...
Fetching Chart ...
Publication Additional Information Download
Publication Type
Journal Article
Authorship
Rupasinghe, P. A., & Chow-Fraser, P.
Title
Identification of most spectrally distinguishable phenological stage of invasive Phramites australis in Lake Erie wetlands (Canada) for accurate mapping using multispectral satellite imagery
Year
2019
Publication Outlet
Wetlands Ecology and Management, 27(4), 513-538
DOI
https://doi.org/10.1007/s11273-019-09675-2
Citation
Rupasinghe, P. A., & Chow-Fraser, P. (2019). Identification of most spectrally distinguishable phenological stage of invasive Phramites australis in Lake Erie wetlands (Canada) for accurate mapping using multispectral satellite imagery. Wetlands Ecology and Management, 27(4), 513-538. https://doi.org/10.1007/s11273-019-09675-2
Abstract
Phragmites australis (Cav.) Trin. ex Steudel subspecies australis is one of the worst plant invaders in wetlands of North America. Remote sensing is the most cost-effective method to track its spread given its widespread distribution and rapid colonization rate. We hypothesize that the morphological and/or physiological features associated with different phenological states of Phragmites can influence their reflectance signal and thus affect mapping accuracies. We tested this hypothesis by comparing classification accuracies of cloud-free images acquired by Landsat 7, Landsat 8, and Sentinel 2 at roughly monthly intervals over a calendar year for two wetlands in southern Ontario. We used the Support Vector Machines classification and employed field observations and image acquired from unmanned aerial vehicle (8 cm) to perform accuracy assessments. The highest Phragmites producer’s, user’s, and overall accuracy (96.00, 91.11, and 88.56% respectively) were provided by images acquired in late summer and fall period. During this period, green, Near Infrared, and Short-Wave Infrared bands generated more unique reflectance signals for Phragmites. Both Normalized Difference Vegetation Index and Normalized Difference Water Index showed significant difference between Phragmites and the most confused classes (cattail; Typha latifolia L., and meadow marsh) during the late summer and fall period. Since meadow marsh separated out best from Phragmites and cattail in the February image, we used it to mask the meadow marsh in the July image to reduce confusion. The unique reflectance signal of Phragmites in late summer and fall is likely due to prolonged greenness of Phragmites when compared to other wetland vegetation, large, distinct inflorescence, and the water content of Phragmites during this period.
Program Affiliations
GWF: Global Water Futures
Publication Stage
Published
Download Links
https://doi.org/10.1007/s11273-019-09675-2
© 2026 - WaterNet Version 2026-08-10
Global Water Futures Observatories
Powered by
G W F Net
T-2022-12-05-W1W1UhSBXiqUOjiDZbBnu02Q Publication 1.0