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Intertidal feature mapping from sentinel and drone (INTREPID)

Intertidal feature mapping from sentinel and drone (INTREPID)


​This research has been carried under the Geological Survey Ireland 2017 Short Call. This call provided funding for researchers in academia or industry on the island of Ireland for projects of less than 12 months duration and less than €25,000. 

Please note that the final report has been redacted to remove staff, financial and sensitive information. Some file sizes have been reduced to allow easier uploading/downloading, higher quality files are available on request. Supplemental information is also available on request in most cases. Please contact research[AT]

Disclaimer:  The views expressed in this report are those of the author(s) and not of Geological Survey Ireland or the Department of Climate Action, Communications and Environment.

Lead Applicant: Dr Seamus Coveney

Host: EnvoGeo Environmental Geoinformatics

Project Title: Intertidal feature mapping from sentinel and drone (INTREPID)

Project Description: A combination of Satellite and Unmanned Aerial Systems (UAS) imagery and UAS Digital Surface Model (DSM) data is proposed for detailed intertidal mapping. The potential for intertidal zone features to be automatically and semi-automatically recognised from Sentinel 2 multispectral imagery and very high-resolution UAS (drone) data will be examined. ESA Sentinel-2 satellite imagery, Sentinel-2 and SNAP Toolboxes and contemporary desktop image processing and classification toolsets will be used to undertake intertidal zone feature recognition. Shoreline definition modelling will be derived from Sentinel-2 image series, utilising recently published SHOREX algorithms developed by the research co-applicant. Very high-resolution intertidal zone feature recognition and shoreline extraction modelling will be carried out using existing GSI UAS (drone) imagery and UAS DSM data. Feature recognition will be carried out using 3D feature recognition algorithms that have been recently developed and tested by the lead applicant. Strong applied research impact is envisaged, including the development of feature recognition algorithms and tools which would provide the basis of larger proposals that optimise the applied research potential of ESA products. Direct peer-reviewed research impact potential is anticipated in the intertidal application of Sentinel-2 data, the evolution of Sentinel-2 shoreline extraction models, UAS-DSM shoreline modelling and feature recognition approaches.