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Coastal erosion threatens infrastructure and communities along the California coast. This paper examines how the amount and location of coastal cliff erosion changed across survey periods along approximately 13 km of the Big Sur coastline using 27 publicly available USGS M3C2 point-cloud datasets covering 2017 to 2023. These data were created from photographs taken with a plane-mounted camera rather than a low-cost drone; however, as part of this project, a Crazyflie drone equipped with an AI Deck was built from scratch and configured for autonomous flight as a prototype for future coastal-monitoring studies. A workflow was created to inspect the clouds, create representative samples, measure statistically significant surface change, and divide the coastline into 250 m segments. The largest sampled 95th-percentile erosion distance was 4.161 m for the period from March to July 2020, while 82.54\% to 100\% of points were classified as significant change depending on the survey interval. The analysis also identified 62 candidate erosion hotspot cases across different coastal segments and time periods, demonstrating that both erosion magnitude and hotspot location varied considerably between surveys. These results show that repeated cloud surveys can reveal important spatial and temporal patterns in coastal erosion and provide a practical baseline for evaluating whether low-cost autonomous drones can produce accurate and affordable coastal-monitoring data. View the project repository at github.com/PeskyPenguin13/Big-Sur-coastal-erosion-analysis.
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Aravind Acharya (2026) studied this question.
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