Improving Machine Learning Classifications of Phragmites australis Using Object-Based Image Analysis. - Anderson, Connor J.; Heins, Daniel; Pelletier, Keith C.; Knight, Joseph F. (Remote. Sens., 2023)

Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis. - Anderson, Connor J.; Heins, Daniel; Pelletier, Keith C.; Knight, Joseph F. (Remote. Sens., 2023)

Multi-Source EO for Dynamic Wetland Mapping and Monitoring in the Great Lakes Basin. - Battaglia, Michael; Banks, Sarah N.; Behnamian, Amir; Bourgeau-Chavez, Laura L.; Brisco, Brian; Corcoran, Jennifer; Chen, Zhaohua; Huberty, Brian; Klassen, James; Knight, Joseph F.; Morin, Paul; Murnaghan, Kevin; et al. (Remote. Sens., 2021)

Mapping Invasive Phragmites australis Using Unoccupied Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar. - Anderson, Connor J.; Heins, Daniel; Pelletier, Keith C.; Bohnen, Julia L.; Knight, Joseph F. (Remote. Sens., 2021)

The Effects of Point or Polygon Based Training Data on RandomForest Classification Accuracy of Wetlands. - Corcoran, Jennifer; Knight, Joseph F.; Pelletier, Keith C.; Rampi, Lian P.; Wang, Yan (Remote. Sens., 2015)

An object-based image analysis approach for mapping and monitoring flooding and topographic change near Duluth, Minnesota, USA. - Pelletier, Keith C.; Knight, Joseph F. (2014)