Data fusion and classifier ensemble techniques for vegetation mapping in the coastal Everglades

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. This study examined the applicability of data fusion and classifier ensemble techniques for vegetation mapping in the coastal Everglades. A framework was designed to combine these two techniques. In the framework, 20-m hyperspectral imagery collected from Airborne Visible/Infrared Imaging Spectrometer was first merged with 1-m Digital Orthophoto Quarter Quads using a proposed pixel/ feature-level fusion strategy. The fused data set was then classified with an ensemble approach based on two contemporary machine learning algorithms: Random Forest and Support Vector Machine. The framework was applied to classify nine vegetation types in a portion of the coastal Everglades. An object-based vegetation map was produced with an overall accuracy of 90% and Kappa value of 0.86. Per-class classification accuracy varied from 61% for identifying buttonwood forest to 100% for identifying red mangrove scrub. The result shows that the framework is promising for automated vegetation mapping in the Everglades. 1. Introduction The Greater Everglades of South Florida are the largest subtropical wetland in the United States. It has been designated as a World Heritage Site, International Biosphere Reserve and Wetland of International Importance for its unique combination of hydrology and water-based ecology that supports many threatened and endangered species (Davis et al. 1994). However, human activities in the past century have severely modified the Everglades ecosystem, resulting in a variety of a $10.5-billion mission expected to take 30 or more years to complete. The CERP contains many pilot projects, and many of which require accurate and informative vegetation maps, because the restoration will cause dramatic modification of plant communities (Doren et al. 1999). Monitoring changes of vegetation communities can measure the progress and effects of restoration on environmental health (Doren et al. 1999, Griffin et al. 2011). Current vegetation information to support …