期刊
INTERNATIONAL JOURNAL OF REMOTE SENSING
卷 37, 期 3, 页码 516-536出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2015.1131869
关键词
Bathymetry; lidar; seagrass; mapping; hyperspectral imagery
资金
- National Science Foundation [EAR1339015]
- airborne lidar acquisition
- Directorate For Geosciences
- Division Of Earth Sciences [1339015] Funding Source: National Science Foundation
We compared hyperspectral imagery and single-wavelength airborne bathymetric light detection and ranging (lidar) for shallow water (<2m) bathymetry and seagrass mapping. Both the bathymetric results from hyperspectral imagery and airborne bathymetric lidar reveal that the presence of a strongly reflecting benthic layer under seagrass affects the elevation estimates towards the bottom depth instead of the top of seagrass canopy. Full waveform lidar was also investigated for bathymetry and similar performance to discrete lidar was observed. A provisional classification was performed with limited ground reference samples and four supervised classifiers were applied in the study to investigate the capability of airborne bathymetric lidar and hyperspectral imagery to identify seagrass genera. The overall classification accuracy is highly variable and strongly dependent on the classification strategy used. Features from bathymetric lidar alone are not sufficient for substrate classification, while hyperspectral imagery alone showed significant capability for substrate classification with over 95% overall accuracy. The fusion of hyperspectral imagery and bathymetric lidar only marginally improved the overall accuracy of seagrass classification.
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