EnviNavigator - self-learning solution for sharing AI enriched mobile and earth observation data

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Objectives of the service

In the project, forest services based on satellite monitoring that use self-learning artificial intelligence are being developed. Up-to-date information on the current state of forests, their risks, management needs and changes 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

The target users are forest owner associations and their customers (forest owners). Forest organizations are currently lacking easy-to-use tools for monitoring forest status and activating forest owners to manage their forests. 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:

  • 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 with easy web and mobile applications:

  • By checking them on the map (the relevant AI detections are highlighted)
  • By receiving automatic notifications as messages in the application

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. We will create the self-learning AI engine, which will continuously update the AI models based on user feedback and mobile observations.

Current Status

Requirements definition and architectural design work packages are about to be finalized. Several workshops with forest owner associations for defining the user needs have been held in Finland and Germany.

Prime Contractor(s)

Status Date

Updated: 29 March 2021 - Created: 29 March 2021