Pilot Project 1 - Drought in Mälardalen

2019-09 to 2019-12

Funding: SMHI

Partners: Länsstyrelsen Västmanland, RISE

Use case owner: Country administration board

AI-based method for analysis of season variations

Sentinel 2 data

  • Vegetation index NDVI
  • Stress index MSI

Pilot Project 2 - Water levels Vänern

2019-09 to 2019-12

Funding: SMHI

Partners: Länsstyrelsen Västa Götaland, Metria

  • Monitor shoreline variations
  • Reduce variation of water levels in lake Vänern
  • Reduce overgrowth of beaches

Pilot Project 3 - Marine Habitats

2020-09 to 2020-12

Funding: Länsstyrelsen Västerbotten

Partner: Länsstyrelsen Västerbotten/DHI

Use the Swedish Space Data Lab as a platform for mapping of marine habitats

Pilot Project 4 - Coastal Zones

2020-09, ongoing

Funding: SMHI

Partner: SMHI

  • Test of the Swedish Space Data Lab as a platform for water quality analysis
  • Implementation of PyTROLL for data management and analysis

Pilot Project 6 - API

2021-01 to 2021-06

Funding: TBD

Partners: Hav och Vatten, Skogsstyrelsen, Jordbruksverket

Implement Open Data Cube (ODC)

  • Ready components for an API


Testing from different sites

  • Jordbruksverket
  • Skogstyrelsen
  • Havs och vattenmyndigheten


Prepare for OpenEO study

Pilot Project 7 - Water Dynamics

  • Water mapping with Sentinel-1 and Sentinel-2 with deep learning models
  • Data management of Sentinel-1 data
  • Enable mapping of water dynamis and season variations
  • Test of functionality for production of “Nationella marktäckedata” (NMD) ref. the Swedish Environmental Protection agency

Pilot Project 8 - AI Areal

2020-12, ongoing

Funding: Vinnova

Partners: RISE, Jordbruksverket

  • Change detection e.g. if grassland has been harvested or if pastures have been grazed during the season
  • EU propose use of satellite data for follow up on Agriculture support (CAP)

Pilot Candidate 9 - AI Shallow Water

2021-03, ongoing

Funding: SNSA

Partners: RISE, SNSA, LTU

  • Change analysis of coastal zones
  • Spatial planning and follow up on factors having impact on coastal zones

Pilot Candidate 10 - "Grunda bottnar"



Havs och vattenmyndigheten

SGU Sveriges geologiska undersökning

Marine mapping and AI

  • Machine learning
  • 50+ predictors
  • Swedish coastlines and the Baltic Sea
  • High resolution