The Use of Ultra-High Resolution UAV Lidar Infrared Intensity for Enhancing Coastal Cover Classification

Abstract

Coastal areas gather increasing hazards, exposures, and vulnerabilities in the context of anthropogenic changes. Understanding their spatial responses to acute and chronic drivers requires ultra-high spatial resolution that can only be achieved by UAV-based sensors. UAV lasergrammetry constitutes, to date, the best observation of the xyz variables in terms of resolution, precision, and accuracy, allowing coastal areas to be reliably mapped. However, the use of lidar reflectivity (or intensity) remains poorly examined for mapping purposes. The added value of the lidar-derived near-infrared (NIR) was estimated by comparing the classification results of nine coastal habitats based on the blue–green–red (BGR) passive and BGR-NIR passive–active datasets. A gain of 4.14% was found at the landscape level, while habitat-scaled improvements were highlighted for the “salt marsh” and “soil” habitats (4 and 4.56% for producer’s accuracy, PA, and user’s accuracy, UA; and 8.95 and 9.48% for PA and UA, respectively).

Keywords

• salt marsh
• lidar near-infrared intensity
• DJI L1