Harvesting Time Recommendation for maximum crop Yield (HaTRY)

Predicting the best time to harvest crop using remotely sensed data

Duration: 2020–2021
Funder: European Space Agency
Partners: local farmers in Estonia

Planned outcomes:

  • Prototype service for Precision Farming application to predict and recommend the most favorable harvesting time for maximum crop yield.
  • Focus on Northern Europe region and three most common crops: winter wheat, spring barley and winter rapeseed.
  • Learn and collect farmers requirements for a fully operational service.

National Programme for Addressing Socio-Economic Challenges through R&D (RITA). Using remote sensing data in favour of the public sector services

Monitoring the use of agricultural land

Duration: 2019–2020
Funder: This study was financially supported by the European Regional Development Fund within National Programme for Addressing Socio-Economic Challenges through R&D (RITA).
Partners: Consortium team: University of Tartu, Tallinn University of Technology, Estonian University of Life Sciences, KappaZeta Ltd

Planned outcomes:

  • Mature, reliable and tested crop classification methodology development specifically suited for Estonian agricultural, ecological and climatic conditions.
  • Multi-year country-wide testing and error analysis about vegetative seasons 2018–2020.
  • Crop classification model prototype with test datasets.


ESA Business Incubation

Improving our software quality during the incubation phase

Duration: 2018–2019 

Funder: European Space Agency
Partners: University of Tartu (Institute of Computer Science), Sookolli Kaardid OÜ, Elmer SKB OÜ, Codeborne OÜ

  • Satellite imagery model development
  • Software architecture definition and review
  • Software implementation
  • Market analysis and business plan development
  • Improved web map for visualizing our analysis results

Detection of mowing events on grasslands from Sentinel-data

The first nation-wide system for automated monitoring of agricultural practices in EU 

Duration: 2016-2018
Customer: Estonian Agricultural Registers and Information Board (ARIB)
Partners: CGI Estonia, Tartu Observatory

  • Nation-wide fully automated mowing detection system operational in Estonia from 2018
  • Sentinel-1 and Sentinel-2 time-series for operational near real-time monitoring
  • 85% of detection accuracy of the mowing events on grasslands
  • Automated “early warning” reminders to applicants

 An isolated grassland – status “not mowed”

Grassland mowing detection for agricultural subsidy checks with Sentinel-1 and Sentinel-2

Looking over the borders to Denmark, Sweden and Poland 

Duration: 2017-2019.
Customer: European Space Agency, Industry Incentive Scheme (ESA IIS)
Partners: The Danish Agrifish Agency, the Swedish Board of Agriculture, The Agency for Restructuring and Modernisation of Agriculture in Poland, Reach-U Ltd, KappaZeta Ltd

  • Validate the service by performing user trials in Sweden and Denmark
  • Enhance the existing cutting and grazing detection methodology
  • Study Earth Observation Community Platform (EO CP) service providers
  • Perform Viability Analysis

Data Analytics for Optimizing Agricultural Monitoring

Going beyond the mowing detection powered by high-level data analytics expertise 

Duration: 2017-2018.
Funder: Enterprise Estonia, project No. EU48684
Partners: Software Technology and Applications Competence Centre (STACC), KappaZeta

  • Develop a scientifically validated methodology for ploughing and grazing events detection from Sentinel-1 and Sentinel-2 time series
  • Bring to customers a new cultivation and grazing detection product prototype
  • Involve high-level data analytics expertise powered by STACC.

Home page and demo application

KZ branding, home page and demo application

Duration: 2017
Funder: Enterprise Estonia, project No. EU51738; amount of the grant 14,960 €.
Main partners: Reach-U, Kiften, Jon & Pun, KappaZeta
Outcomes: KZ branding, home page and mowing detection demo application