A high-resolution spatiotemporal morphological dataset: Port Aransas beach, Texas

Area of Science:

• Coastal geomorphology and dynamics.
• Environmental monitoring and data science.

Background:

• Beach morphology is crucial for coastal management and understanding erosion/accretion.
• High-frequency data on beach elevation and imagery are needed to study coastal processes and inundation.

Purpose of the Study:

• To describe a comprehensive one-year dataset of beach morphology and imagery.
• To provide a valuable resource for studying coastal dynamics and predicting inundation.

Main Methods:

• Collected bi-monthly topographic surveys and daily high-frequency beach imagery (Feb 2023-Jan 2024).
• Integrated topographic data with imagery to derive beach profiles, elevation models, and shoreline data.
• Combined dataset with National Oceanic and Atmospheric Administration metocean measurements.

Main Results:

• Generated a one-year dataset including 18 topographic surveys and 6879 images.
• Created derived products like digital elevation models and daily shoreline delineations.
• The dataset captures seasonal variations and inundation events.

Conclusions:

• The dataset offers a rare combination of high-frequency survey and imagery data.
• It is suitable for analyzing seasonal coastal changes and developing machine learning models for inundation prediction.