Classification of Atlantic Coastal Sand Dune Vegetation Using In Situ, UAV, and Airborne Hyperspectral Data

Quentin Laporte-Fauret,Patrick Launeau,Manuel Giraud,Bruno Castelle,Richard Michalet,Vincent Marieu,Bertrand Lubac,Cassandra Normandin,Lionel Bombrun,David Rosebery

doi:10.3390/rs12142222

Abstract

Mapping coastal dune vegetation is critical to understand dune mobility and resilience in the context of climate change, sea level rise, and increased anthropogenic pressure. However, the identification of plant species from remotely sensed data is tedious and limited to broad vegetation communities, while such environments are dominated by fragmented and small-scale landscape patterns. In June 2019, a comprehensive multi-scale survey including unmanned aerial vehicle (UAV), hyperspectral ground, and airborne data was conducted along approximately 20 km of a coastal dune system in southwest France. The objective was to generate an accurate mapping of the main sediment and plant species ground cover types in order to characterize the spatial distribution of coastal dune stability patterns. Field and UAV data were used to assess the quality of airborne data and generate a robust end-member spectral library. Next, a two-step classification approach, based on the normalized difference vegetation index and Random Forest classifier, was developed. Results show high performances with an overall accuracy of 100% and 92.5% for sand and vegetation ground cover types, respectively. Finally, a coastal dune stability index was computed across the entire study site. Different stability patterns were clearly identified along the coast, highlighting for the first time the high potential of this methodology to support coastal dune management.

Highlights

The formation and evolution of coastal sand dunes, which back sandy beaches, result from complex interactions between marine and aeolian sediment transport, plant ecosystem-engineering effects, coastal and beach topography, and storms [1,2,3,4,5,6,7]
When not destroyed by human activity, foredunes are formed by an accumulation of wind-blown sand, which is trapped by plant species tolerant to sand burial
The record of the aircraft attitude, with the fast inertia measurement unit (IMU), coupled to the accurate global positioning system (GPS) of POS AV AP50 OEM (IMU-8) from Applanix (Richmond Hill, Ontario, Canada) mounted in the dual wavelength Ligth Detection and Ranging (LiDAR) Titan of Teledyne Optech Incorporated (Vaughan, Ontario, Canada) was provide by the LiDAR Nantes-Rennes university platform, and the trajectory was calculated by GEOFIT Expert Company (Nantes, France)

Summary

Introduction

The formation and evolution of coastal sand dunes, which back sandy beaches, result from complex interactions between marine and aeolian sediment transport, plant ecosystem-engineering effects, coastal and beach topography, and storms [1,2,3,4,5,6,7]. As dunes play an important role in the protection from waves and flooding during storms by acting as a natural barrier, in recent decades, many management plans have been proposed to prevent erosion and promote dune stabilization at the detriment of natural processes These management strategies generally include beach nourishment [13], vegetation planting [14], sand fencing [15], or mechanical reprofiling [16]. Coastal dunes play a crucial role for the future of sandy coasts [21,22] In this context, mapping and monitoring the spatial and temporal distribution of plant communities, together with morphological changes, is critical to improve our understanding of coastal dune changes in response to natural forcing. This is crucial for management strategies, for designing optimal sustainable development of these systems

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