Modeling barrier island habitats using landscape position information
Barrier islands are dynamic environments because of their position along the marine–estuarine interface. Geomorphology influences habitat distribution on barrier islands by regulating exposure to harsh abiotic conditions. Researchers have identified linkages between habitat and landscape position, such as elevation and distance from shore, yet these linkages have not been fully leveraged to develop predictive models. Our aim was to evaluate the performance of commonly used machine learning algorithms, including K-nearest neighbor, support vector machine, and random forest, for predicting barrier island habitats using landscape position for Dauphin Island, Alabama, USA. Landscape position predictors were extracted from topobathymetric data. Models were developed for three tidal zones: subtidal, intertidal, and supratidal/upland. We used a contemporary habitat map to identify landscape position linkages for habitats, such as beach, dune, woody vegetation, and marsh. Deterministic accuracy, fuzzy accuracy, and hindcasting were used for validation. The random forest algorithm performed best for intertidal and supratidal/upland habitats, while the K-nearest neighbor algorithm performed best for subtidal habitats. A posteriori application of expert rules based on theoretical understanding of barrier island habitats enhanced model results. For the contemporary model, deterministic overall accuracy was nearly 70%, and fuzzy overall accuracy was over 80%. For the hindcast model, deterministic overall accuracy was nearly 80%, and fuzzy overall accuracy was over 90%. We found machine learning algorithms were well-suited for predicting barrier island habitats using landscape position. Our model framework could be coupled with hydrodynamic geomorphologic models for forecasting habitats with accelerated sea-level rise, simulated storms, and restoration actions.
Citation Information
| Publication Year | 2019 |
|---|---|
| Title | Modeling barrier island habitats using landscape position information |
| DOI | 10.3390/rs11080976 |
| Authors | Nicholas Enwright, Lei Wang, Hongqing Wang, Michael Osland, Laura Feher, Sinéad M. Borchert, Richard Day |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Remote Sensing |
| Index ID | 70203195 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Wetland and Aquatic Research Center |
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Modeling barrier island habitats using landscape position information for Dauphin Island, Alabama
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Modeling barrier island habitats using landscape position information for Dauphin Island, Alabama
Barrier islands provide important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism (Barbier and others, 2011; Feagin and others, 2010). These islands tend to be dynamic due to their location along the estuarine-marine interface. Besides gradual changes caused by constant forces, such as currents and tides, barrier island - Connect