Improved understanding of California coastal cliff morphodynamics using airborne lidar and vegetation filtering (2016–2023)
Year: 2026
Type: article
Abstract: Coastal cliffs are widespread along California coastlines, yet their erosion remains difficult to quantify at statewide scales because of (1) limited high-resolution data, (2) intensive processing requirements, and (3) challenges in mapping ground elevations beneath vegetation. This study collected airborne lidar data across the California coast in 2023 and compared it with 2016 lidar to evaluate coastal cliff changes. We developed automated approaches to (1) delineate cliff geometry and cliff top retreat, and (2) quantify erosion volume changes and retreat rates at 5-m spacing alongshore. Using ground filtering algorithms, we reduced vegetation-obscured areas from 70–90% to <20%. The results show that mean cliffs are 38 m tall, 55 m wide, and slope at 37°, with height and width generally increasing northward. ∼34.5% of cliffs showed no measurable cliff face retreat change, while statewide retreat averaged 0.06 m/yr and reached a maximum of 10.2 m/yr. Both cliff top and face retreat rates were highest in Northern California. The maximum erosion rate exceeded 1150 m 3 /m/yr, while the statewide mean erosion and deposition rates were 2.6 m 3 /m/yr and 0.3 m 3 /m/yr, respectively. Although taller cliffs experienced higher erosion rates, a negative trend existed between cliff face retreat rate and cliff height for cliffs <100 m. This study provides a framework for statewide cliff change monitoring for improved understanding of coastal hazards across diverse coastal settings.
Authors: Danghan Xie, Hironori Matsumoto, Zuzanna M. Swirad, Luc Lenain, Adam P. Young
Language: English
Topic: Coastal and Marine Dynamics
Subfield: Earth-Surface Processes
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: gold
Estimated APC paid: $3,550
Award: G2110049615
OpenAlex ID: W7166455651