Evaluation of Spatial Generalization Characteristics of a Robust Classifier as Applied to Coral Reef Habitats in Remote Islands of the Pacific Ocean

作     者：Gapper, Justin J. El-Askary, Hesham Linstead, Erik Piechota, Thomas 

作者机构：Chapman Univ Schmid Coll Sci & Technol Computat & Data Sci Grad Program Orange CA 92866 USA Chapman Univ Ctr Excellence Earth Syst Modeling & Observat Orange CA 92866 USA Chapman Univ Schmid Coll Sci & Technol Orange CA 92866 USA Alexandria Univ Fac Sci Dept Environm Sci Alexandria 21522 Egypt Chapman Univ Machine Learning & Assist Technol Lab MLAT Orange CA 92866 USA 

出 版 物：《REMOTE SENSING》 (Remote Sens.)

年 卷 期：2018年第10卷第11期

页      面：1774-1774页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1002[医学-临床医学] 070801[理学-固体地球物理学] 07[理学] 08[工学] 0708[理学-地球物理学] 0816[工学-测绘科学与技术] 

基　　金：Microsoft Corporation Amgen Inc 

主　　题：coral detection classification spectral signature expansion benthic habitat mapping Landsat 8 

摘      要：This study was an evaluation of the spectral signature generalization properties of coral across four remote Pacific Ocean reefs. The sites under consideration have not been the subject of previous studies for coral classification using remote sensing data. Previous research regarding using remote sensing to identify reefs has been limited to in-situ assessment, with some researchers also performing temporal analysis of a selected area of interest. This study expanded the previous in-situ analyses by evaluating the ability of a basic predictor, Linear Discriminant Analysis (LDA), trained on Depth Invariant Indices calculated from the spectral signature of coral in one location to generalize to other locations, both within the same scene and in other scenes. Three Landsat 8 scenes were selected and masked for null, land, and obstructed pixels, and corrections for sun glint and atmospheric interference were applied. Depth Invariant Indices (DII) were then calculated according to the method of Lyzenga and an LDA classifier trained on ground truth data from a single scene. The resulting LDA classifier was then applied to other locations and the coral classification accuracy evaluated. When applied to ground truth data from the Palmyra Atoll location in scene path/row 065/056, the initial model achieved an accuracy of 80.3%. However, when applied to ground truth observations from another location within the scene, namely, Kingman Reef, it achieved an accuracy of 78.6%. The model was then applied to two additional scenes (Howland Island and Baker Island Atoll), which yielded an accuracy of 69.2% and 71.4%, respectively. Finally, the algorithm was retrained using data gathered from all four sites, which produced an overall accuracy of 74.1%.