Mapping Phragmites cover using WorldView 2/3 and Sentinel 2 images at Lake Erie Wetlands, Canada
December 2020 https://doi.org/10.1007/s10530-020-02432-0
Phragmites australis (Cav.) Trin. ex Steudel subspecies australis is an aggressive plant invader in North American wetlands. Remote sensing provides cost-effective methods to track its spread given its widespread distribution. We classiﬁed Phragmites in three Lake Erie wetlands (two in Long Point Wetland Complex (LP) and one in Rondeau Bay Marsh (RBM)), using commercial, high-resolution (WorldView2/3: WV2 for RBM, WV3 for LP) and free, moderate-resolution (Sentinel 2; S2) satellite images. For image classiﬁcation, we used mixturetuned match ﬁltering (MTMF) and then either maximum likelihood (ML) or support vector machines (SVM) classiﬁcation methods. Using WV2/3 images with ML classiﬁcation, we obtained higher overall accuracy for both LP sites (93.1%) compared with the RBM site (86.4%); both Phragmites users’ and producers’ accuracies were also higher for LP (89.3% and 92.7%, respectively) compared with RBM (84.3% and 88.4%, respectively). S2 images with SVM classiﬁcation provided similar overall accuracies for LP (74.7%) and for the RBM (74.3%); Phragmites users’ and producers’ accuracies for LP were 85.3% and 76.3%, and for the RBM, 69.1% and 79.2%, respectively. Using WV2/3, we could quantify small patches (percentage cover >20%; shoots >1 m tall; stem counts >25) with accuracy >80%, whereas parallel effort with S2 images only accurately quantiﬁed high density ([>60% cover), mature shoots (>1 m tall; Stem counts [>100). By simultaneously mapping young or sparsely distributed Phragmites shoots and dense mature stands accurately, we show our approach can be used for routine mapping and regular updating purposes, especially for post-treatment effectiveness monitoring.