28 August 2021 Object-based random forest wetland mapping in Conne River, Newfoundland, Canada
Jean Elizabeth Granger, Masoud Mahdianpari, Thomas Puestow, Sherry Warren, Fariba Mohammadimanesh, Bahram Salehi, Brian Brisco
Author Affiliations +
Abstract

The Conne River watershed is dominated by wetlands that provide valuable ecosystem services, including contributing to the survivability and propagation of Atlantic salmon, an important subsistence species that has shown a dramatic decline over the past 30 years. To better understand and improve the management of the watershed, and in turn, the Atlantic salmon, a wetland inventory of the area is developed using advanced remote sensing methods including field-collected data, object-based image analysis of Sentinel-1, Sentinel-2, and digital elevation model Earth observation data. The resulting classification maps consisted of bog, fen, swamp, marsh, and open water wetlands with an overall accuracy of 92% and a kappa coefficient of 0.916. Among wetland classes, user and producer accuracies range between 84% and 100%. Results show the dominance of peatland wetlands such as bog and fen, and the relative rareness of marsh wetlands.

© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2021/$28.00 © 2021 SPIE
Jean Elizabeth Granger, Masoud Mahdianpari, Thomas Puestow, Sherry Warren, Fariba Mohammadimanesh, Bahram Salehi, and Brian Brisco "Object-based random forest wetland mapping in Conne River, Newfoundland, Canada," Journal of Applied Remote Sensing 15(3), 038506 (28 August 2021). https://doi.org/10.1117/1.JRS.15.038506
Received: 6 April 2021; Accepted: 16 August 2021; Published: 28 August 2021
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Image classification

Data modeling

Remote sensing

Vegetation

Image segmentation

Visualization

Accuracy assessment

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