This thesis investigated multispectral detection of the invasive floating macrophyte, European Frog-bit, using Quickbird imagery and fuzzy image classification. To determine if the spectral
signature of European Frog-bit were separable from other wetland vegetation, a species level land cover classification was conducted on a 6km section of the South Nation River in Ontario, Canada. Supervised and unsupervised imagery classification approaches were evaluated using the fuzzy classifiers, Fuzzy Segmentation for Object Based Image Classification (FS) and Fuzzy
C-Means (FCM). Both approaches were sufficiently robust to detect European Frog-bit. User’s and producer’s accuracies for the European Frog-bit class were 81.0% and 77.9% for the FS classifier and 63.5% and 73.0% for the FCM classifier. These accuracies indicated that the spectral signature of EFB was sufficiently different to permit detection and separation from other
wetland vegetation and fuzzy image classifiers were capable of detecting EFB in Quickbird imagery.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/31393 |
| Date | 19 December 2011 |
| Creators | Proctor, Cameron |
| Contributors | Robinson, Vincent, He, Yuhong |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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