Cezary Specht

The coastal environment represents a resource from both a natural and economic point of view, but it is subject to continuous transformations due to climate change, human activities, and natural risks. Remote sensing techniques have enormous potential in monitoring coastal areas. However, one of the main tasks is accurately identifying the boundary between waterbodies such as oceans, seas, lakes or rivers, and the land surface. The aim of this research is to evaluate the accuracy of coastline extraction using different datasets. The images used come from UAV-RGB and the Landsat-9 and Sentinel-2 satellites. The method applied for extracting the coast feature involves a first phase of application of the Normalized Difference Water Index (NDWI), only for satellite data, and consequent application of the maximum likelihood classification, with automatic vectorization. To carry out a direct comparison with the extracted data, a coastline obtained through a field survey using a Global Navigation Satellite System (GNSS) device was used. The results are very satisfactory as they meet the minimum requirements specified by the International Hydrographic Organization (IHO) S-44. Both the UAV and the Sentinel-2 reach the maximum order, called the Exclusive order (Total Horizontal Uncertainty (THU) of 5 m with a confidence level of 95%), while the Landsat-9 falls into the Special order (THU of 10 m with a confidence level of 95%).

This publication is aimed at developing a concept of an innovative system for dimensioning and predicting changes in the coastal zone topography using Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs). The 4DBatMap system will consist of four components: 1. Measurement data acquisition module. Bathymetric and photogrammetric measurements will be carried out with a specific frequency in the coastal zone using a UAV equipped with a Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), Light Detection And Ranging (LiDAR) and a photogrammetric camera, as well as a USV equipped with a GNSS Real Time Kinematic (RTK) receiver and a MultiBeam EchoSounder (MBES). 2. Multi-sensor geospatial data fusion module. Low-altitude aerial imagery, hydrographic and LiDAR data acquired using UAVs and USVs will be integrated into one. The result will be an accurate and fully covered with measurements terrain of the coastal zone. 3. Module for predicting changes in the coastal zone topography. As part of this module, a computer application will be created, which, based on the analysis of a time series, will determine the optimal method for describing the spatial and temporal variability (long-term trend and seasonal fluctuations) of the coastal zone terrain. 4. Module for imaging changes in the coastal zone topography. The final result of the 4DBatMap system will be a 4D bathymetric chart to illustrate how the coastal zone topography changes over time.