Digital elevation model generation using UAV-SfM photogrammetry techniques to map sea-level rise scenarios at Cassino Beach, Brazil

Abstract

The Cassino Beach is a low-lying coast with high inundation susceptibility in southern Brazil. To map this vulnerability, a low cost alternative to the increasingly employed fine-scale remote sensing is the employment of a digital camera coupled with unmanned aerial vehicle (UAV). However, this was only achieved through the adoption of photogrammetric principles and computational advances of structure-from-motion (SfM) algorithms. The study objectives were: a topographic reconstruction of the Cassino beach; an accurate digital terrain model (DTM) generation from the dense cloud classification; and inundation maps based on representative concentration pathway (RCP) scenarios from the Intergovernmental Panel on Climate Change using the bathtub approach. The primary input of the inundation model was a DTM with spatial resolution of 0.1294 m and an RMSE elevation of 0.0607 m. The high-resolution and vertical precision were appropriated to the bathtub approach, with the mapping identifying the exposed areas with the drowning potential correctly connected to the source. The inundation maps revealed that: in the 2046–2065 RCP scenario, the urban drowned area has varied between 37 and 41%; in the 2081–2100 RCP scenario, the urban drowned area has varied between 51 and 73%; and in the 2100 RCP scenario, the urban drowned area has varied between 54 and 82%. The bathtub modeling shows that low-lying coasts are highly susceptible to sea-level rise effects, and the use of UAV-SfM technology in the production of topographic data was suitable for the study area.