Analysis of coastal erosion between different flights of UAV

Sammanfattning: More than 600 million people are living in coastal areas in the world. According to the trend of population migration, the global coastal area population may increase to more than 1 billion by 2050. In a long term, a series of activities such as sea-level rise due to global warming and unpredictable natural disasters increase the extent of coastal erosion. As coastal erosion continues to intensify, it may cause erosion of soil resources and threaten the safety of coastal buildings and roads. This series of damages to human life and economic property caused by coastal erosion make it important to monitor coastal erosion. Traditional collection methods like peg-lines, total station, Terrestrial Laser Scanning (TLS), airborne LiDAR (Light Detection and Ranging), Global Navigation Satellite System (GNSS) surveys and aerial imagery can obtain high-resolution data. Although the accuracy of the monitoring can meet the requirements, the disadvantage is that the cost is high, and it is difficult to carry out long-term multiple coastal erosion monitoring. Compared to traditional monitoring methods, the use of UAV for images collection is low in cost, easy to operate and has fewer limitations. UAV has the characteristics of low-cost equipment and a high degree of automation, which makes it advantageous when monitoring coastal erosion. Therefore, in this study, a digital surface model (DSM), an elevation difference map, a DSM accuracy map and a slope map were created based on five UAV images at different times. According to the obtained elevation difference map and accuracy map, the degree of coastal erosion can be quantified, and the seasonal pattern and spatial pattern of coastal erosion can be obtained. However, due to the limitation of the error and other uncertain values in the DSM in this project, the elevation difference in the study area does not completely represent the elevation change, that is, the value of coastal erosion. Therefore, it is also necessary to remove or reduce the influence of uncertain values in the research.