Establishment of mangroves on a new mud bank by a combination of UAS SfM photogrammetry and LiDAR monitoring

Abstract. Understanding how mangroves respond to sea level rise is critical for coastal management and conservation. This study investigates the feasibility of two remote sensing techniques, Light Detection and Ranging (LiDAR) and Structure-from-Motion (SfM) photogrammetry, to monitor changes in mud elevation that are critical to mangrove establishment dynamics. SfM photogrammetry can provide low-cost 3D modeling from imagery, while LiDAR provides high-precision elevation and vegetation data. Our analysis shows that SfM photogrammetry provides reasonably accurate surface elevation data with a root mean square error (RMSE) of 0.14 meters and a significant correlation coefficient (r = 0.74) compared to LiDAR measurements. This highlights the complementarity between the two, as the effectiveness of SfM photogrammetry is in the early stages of colonization, and then the need to use LiDAR with dense vegetation as the mangroves mature. This shows that a simple method of photogrammetry can remain effective until the vegetation reaches a certain threshold, and this can be particularly useful in the perspective of using mud elevation as a first low-cost diagnosis for potential mangrove rehabilitation project to assess the colonization suitability of mudflats.