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Piloting downstream applications and services of relevance to Coastal Management at local and regional level

Point of contact
Selima Ben Mustapha
Swedish National Space Agency
Hemvärnsgatan 9
SE-17104 Solna
Phone: +46-8-40 90 77 73


The activity aims to raise the awareness and use of Copernicus data and services for municipalities at local level as well as regional authorities. The example of Coastal Management illustrates a good example of an area between land and sea with many cross-sectoral issues as a valuable environment under high pressure from exploitation, tourism, urbanization, maritime activities, erosion due to sea level rise etc.

The user uptake of Copernicus data, products and services has been fairly limited at local and regional level so far. Using coastal management as a demonstration case, pilot applications will be planned and carried out to serve as good examples. The area is caught between economy and sustainable development while embracing high values to biodiversity, ecosystem services and economic activities. The coastal zone is often the area where the impact of climate change is most prominent. The Swedish coast is one of the longest in Europe and Earth Observation applications may be needed depending on specific local circumstances, geographic location and environmental conditions.

An online workshop on coastal zone management was carried out by the Swedish National Space Agency on 15 May 2020. The workshop gathered some 20 different authorities at local, regional and national level with the aim to more precisely define a Copernicus based product that user authorities clearly can benefit from.

Based on the outcome of the workshop held in 2020, it was proposed to develop an EO-based method using Copernicus data to discover physical changes, especially dredging work along the coast and dumping at sea with the help of a trained AI. The long-term objective is to convert the method into a continuous monitoring service to track environmental crimes. Such activities are illegal in Sweden without permission and have increased over the years, especially around the larger cities. Dredging and dumping are serious threats to the marine environment in shallow waters and cause permanent damage to plant and animal ecosystems. With the help of the continuous supply of Sentinel data, it will become rather easy to define dredging activities in time and to reduce costs related to the ‘in situ’ monitoring and control, especially costs of aerial photography.

SNSA established a cooperation with Swedish institutes and universities in order to develop and test the intended product/service. The cooperation took place in form of a pilot project called ‘AI for shallow waters’. This innovative action will give authorities a robust tool to monitor coastal environmental activities using Sentinel data.

Outputs and Results

  • The pilot project: ‘AI for shallow waters’ was conducted successfully. With the Space Data Lab, a national infrastructure for the use of space data is being created to increase the possibilities of developing smart and effective AI solutions - from the storage of space data to the management of satellite constellations in orbit.
  • A novel Artificial Intelligence (AI) method based on Sentinel-2 data was developed to identify physical changes along the Swedish coast, especially physical constructions such as piers and jetties. The derived result will enable municipalities to control unreported or possibly even illegal buildings or activities along the coast, like illegal dredging.
  • Detecting the rate of changes in the coastal zone to support marine and terrestrial planning regarding the dynamics of the coastal zone. Maritime spatial planning using Copernicus data will contribute to the effective management of marine activities and the sustainable use of marine and coastal resources, by creating a framework for consistent, transparent, sustainable, and evidence-based decision-making.
  • The knowledge and AI methods acquired through the project will be distributed to municipalities and national agencies that can benefit from the technology, e.g., the results will be published on the webpage.
  • A Git repository with codes: https://gitlab.ice.ri.se/sdl/shallow-water-sdl . The repository contains readme files an input_data folder with files taken as input for the analysis, a set of Notebooks, and an output folder where the results are saved. The following codes are available: 0-pixel-alignment.ipynb, 1-mock-mechanistic-ts.ipynb, 2-particle-filter-discrete-obs.ipynb, 3-particle-filter-continuous-obs.ipynb. (Prepare time series, create mock data, get MNDWI and NDWI distributions).