@article {26866, title = {Automated Coastline Extraction Using the Very High Resolution WorldView (WV) Satellite Imagery and Developed Coastline Extraction Tool (CET)}, journal = {Applied Sciences}, volume = {11}, number = {20}, year = {2021}, pages = {9482}, abstract = {The accurate extraction of a coastline is necessary for various studies of coastal processes, as well as for the management and protection of coastal areas. Very high-resolution satellite imagery has great potential for coastline extraction; however, noises in spectral data can cause significant errors. Here, we present a newly developedCoastal Extraction Tool(CET) that overcomes such errors and allows accurate and time-efficient automated coastline extraction based on a combination ofWorldView-2(WV-2) multispectral imagery and stereo-pair-derived digital surface model (DSM). Coastline extraction is performed and tested on the I{\v z}-Rava island group, situated within the Northern Dalmatian archipelago (Croatia). Extracted coastlines were compared to (a) coastlines extracted from state topographic map (1:25,000), and (b) coastline extracted by another available tool. The accuracy of the extracted coastline was validated with centimeter accuracy reference data acquired using a UAV system (Matrice 600 Pro+MicaSense RedEdge-MX). Within the study area, two small islets were detected that have not been mapped during the earlier coastline mapping efforts. CET proved to be a highly accurate coastline mapping technique that successfully overcomes spectral-induced errors. In future research, we are planning to integrate data obtained by UAVs infrared thermography (IRT) and in situ sensors, measuring sea and land surface temperatures (SST and LST), into the CET, given that this has shown promising results. Considering its accuracy and ease of use, we suggest that CET can be applied for automated coastline extraction in other large and indented coastal areas. Additionally, we suggest that CET could be applied in longitudinal geomorphological coastal erosion studies for the automated detection of spatio-temporal coastline displacement.}, isbn = {2076-3417}, url = {https://doi.org/10.3390/app11209482}, author = {Domazetovi{\'c}, Fran and {\v S}iljeg, Ante and Mari{\'c}, Ivan and Fari{\v c}i{\'c}, Josip and Vassilakis, Emmanuel and Pan{\dj}a, Lovre} }