Influence of Flight Altitude and Surface Characteristics on UAS-LiDAR Ground Height Estimate Accuracy in Juncus roemerianus Scheele-Dominated Marshes

Abstract

Management and monitoring of vulnerable coastal marshes rely on accurate ground height estimates. However, marsh surface characteristics such as vegetation and water presence complicate aerial remote sensing of the ground. Towards developing an improved understanding and techniques for these remote sensing efforts, this study established relationships among data collection flight altitude, surface characteristics, and ground height estimate accuracy within Juncus roemerianus Scheele-dominated marshes. Uncrewed Aerial System (UAS) Light Detection and Ranging (LiDAR) sampling was conducted at five altitudes for five marsh sites and one local control site. Survey-grade topographic measurements and marsh surface characteristics were recorded at each site for comparison. Root Mean Square Error (RMSE) and linear mixed-effects modeling were used to quantify relationships among vertical error, altitude, and surface characteristics. For low (24–72 m) and high (96–120 m) altitudes Above Ground Level (AGL), the RMSE values were 49 cm and 17 cm, respectively. Despite this appreciable improvement in accuracy with increasing flight altitude, point density values of these datasets limit applications. Linear mixed-effects modeling further emphasized the complex relationships between sensor footprint size, surface characteristics, and ground height estimates. These findings have direct implications for elevation modeling and monitoring efforts of frequently inundated, coastal marshes.