Integrating multispectral ASTER and LiDAR data to characterize coastal wetland landscapes in the northeastern United States

Abstract

This study integrates data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Light Detection and Ranging (LiDAR) to map the spatial configuration of coastal wetland landscapes. We test data sources in their ability to capture marsh features and sources are combined to improve wetland characterizations. The complex ecosystem characteristics of the Wells Maine National Estuarine Research Reserve marshes and surrounding areas provide an ideal study site. The results of this study suggest that ASTER visible, near and shortwave infra red spectral bands combined with LiDAR last return signals provide accurate wetland cover maps categorized in broad cover classes. LiDAR contributions are important in areas of elevation and structure variability where multispectral data are unable to distinguish fine scale variations in vegetation and water signals. ASTER's cost effectiveness and spectral range offer a data-rich alternative to expensive high spatial resolution imagery typically used in multispectral and LiDAR combined studies.

Keywords:

• wetland mapping
• ASTER
• LiDAR
• Wells National Estuarine Research Reserve
• northeastern United States

Acknowledgements

This research was funded by a grant from the Maine Space Grant Consortium, and we acknowledge their support. The University of Southern Maine is an affiliate of the Maine Space Grant Consortium. We acknowledge the support of scientists and staff at the Rachel Carson National Wildlife Refuge, Maine and the Wells National Estuarine Research Reserve, Maine.