ESA title

EnviNavigator

  • ACTIVITY-
  • STATUSCompleted
  • THEMATIC AREAEnvironment, Wildlife and Natural Resources

Objectives of the service

In the project, forest services based on satellite monitoring that use self-learning artificial intelligence have been developed. Up-to-date information on the current state of forests, their risks, management needs and changes are derived by combining satellite data with other data sets relating to forestlands. The services include automatic notifications on AI detections and possibility to add mobile observations and send feedback on the data quality, which are used for improving the AI models automatically. The results of the AI services are easily accessible via easy-to-use user interfaces.

Users and their needs

Forest owner associations and their customers (forest owners). The pilot participants in the project are MHYP (head organization of Forest owner associations in Finland) and forest owner associations Olpe and Kempten from Germany. The main user needs include:

  • forest experts and forest owners need up-to-date data on forest status, damages and risks, and management needs

  • forest experts being able to focus on most relevant / topical management needs

  • tools for communicating between forest experts and forest owners

Service/ system concept

Self-learning AI engine combines: 

  • Satellite data

  • User data

  • Various GIS data sources

AI models provide accurate & up-to-date data on:

  • Forest attributes

  • Detected changes and damages

  • Forest vitality and areas with increased health risks

  • Urgent forest management needs

Users can access the AI results:

  • By checking them on the map

  • By receiving automatic notifications/messages

Self-learning AI engine learns continuously based on users’:

  • Feedback on correctness of AI detections

  • Feedback on quality of map layers

  • New mobile observations added to map

Space Added Value

Sentinel 1 (SAR) and Sentinel 2 (optic) satellite data are used in change detection service for providing estimates on current forest status, cuttings, damages and damage risks using AI models with various training data sets. A self-learning AI engine has been created, which continuously updates the AI models based on user feedback and mobile observations.

Current Status

The Final Review has been successfully performed in May 2022. The Project has been completed and the implemented services are already used operationally and commercially covering the whole of Finland and parts of Germany.

Prime Contractor(s)

Status Date

Updated: 01 June 2022