Remote Sensing | |
Supervised Classification of Benthic Reflectance in Shallow Subtropical Waters Using a Generalized Pixel-Based Classifier across a Time Series | |
Tara Blakey1  Assefa Melesse1  Margaret O. Hall2  Alisa L. Gallant3  Deepak R. Mishra3  | |
[1] Department of Earth and Environment, Florida International University, Miami, FL 33199, USA; E-Mail:;Florida Fish and Wildlife Research Institute, St. Petersburg, FL 33701, USA; E-Mail:;Department of Earth and Environment, Florida International University, Miami, FL 33199, USA; E-Mail | |
关键词: benthic reflectance; supervised classification; Landsat; Florida Bay; seagrass landscapes; long-term monitoring; | |
DOI : 10.3390/rs70505098 | |
来源: mdpi | |
【 摘 要 】
We tested a supervised classification approach with Landsat 5 Thematic Mapper (TM) data for time-series mapping of seagrass in a subtropical lagoon. Seagrass meadows are an integral link between marine and inland ecosystems and are at risk from upstream processes such as runoff and erosion. Despite the prevalence of image-specific approaches, the classification accuracies we achieved show that pixel-based spectral classes may be generalized and applied to a time series of images that were not included in the classifier training. We employed
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190013405ZK.pdf | 5868KB | download |