Hawaiian Islands Reef Rugosity Maps from Airborne Imaging Spectroscopy
by Gregory P. Asner / Arizona State University
Available on 1 platform
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Description
January 2019 and January 2020 airborne imaging spectroscopy data from the Global Airborne Observatory was used to create high-resolution seafloor rugosity maps for the Main Hawaiian Islands. The dataset includes two map products, fine and coarse rugosity, covering islands such as Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai, and Niihau, with Hawaii Island data split into quarters. These maps quantify reef habitat complexity, supporting ecological and conservation research.
Use Cases
Assessing coral reef habitat complexity based on fine and coarse rugosity metrics.
Modeling biodiversity and species distribution linked to seafloor structural variation.
Informing marine spatial planning and conservation strategies for the Hawaiian Islands.
Calibrating and validating other bathymetric or habitat mapping products.
Strengths
Provides high-resolution rugosity data derived from airborne imaging spectroscopy, a detailed remote sensing method.
Covers multiple islands across the Main Hawaiian Islands with consistent collection periods in 2019 and 2020.
Includes two specific map product types (fine and coarse rugosity) for different analytical scales.
Limitations
Specific column names, row counts, and file sizes are not provided in the source metadata.
The exact last update date for the dataset is unknown, limiting assessment of data currency.
Data for Hawaii Island is split into quarters, which may require additional processing for island-wide analysis.
Provenance
Source
Global Airborne Observatory (GAO) team at the Center for Global Discovery and Conservation Science, Arizona State University.
Collection Method
Airborne imaging spectroscopy data collection.
Time Range
January 2019 and January 2020
Geography
Main Hawaiian Islands (Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai, Niihau, and Hawaii Island)
Use of the data requires specific acknowledgments and citations to the funding sources and two scientific publications (Asner et al., 2020; Asner et al., 2021).