Semantic Scholar Open Access 2023 2 sitasi

Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan

C. Sylvester Scott L. Spurgeon Sean McGill Lauren Dunkin

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Abstrak

This Coastal and Hydraulics Engineering technical note (CHETN) details a Geographic Information Systems (GIS) methodology to produce advanced lidar-derived datasets for use in a coastal erosion vulnerability analysis conducted by the US Army Corps of Engineers (USACE) and other federal partners for the Great Lakes Restoration Initiative (GLRI).

Penulis (4)

C. Sylvester

Scott L. Spurgeon

Sean McGill

Lauren Dunkin

Format Sitasi

APA MLA BibTeX

Sylvester, C., Spurgeon, S.L., McGill, S., Dunkin, L. (2023). Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan. https://doi.org/10.21079/11681/47079

Akses Cepat

Lihat di Sumber doi.org/10.21079/11681/47079

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 2×
Sumber Database: Semantic Scholar
DOI: 10.21079/11681/47079
Akses: Open Access ✓