A globally operating super major required environmental monitoring and biodiversity checks on and near its infrastructure sites. Applications ranged from land cover characterisation to biodiversity monitoring to invasive species detection.


Support environmental monitoring and habitat restoration efforts via remote sensing and geospatial data analysis.


  • Large-scale processing of satellite remote sensing and other geospatial datasets on local and regional scales.
  • Support development of a habitat suitability and biodiversity model ingesting various geospatial datasets from multiple sources.
  • Develop a robust deep learning model to detect presence and distribution of invasive plant species via very high-resolution drone imagery.
  • Help design a baseline, regular monitoring and change detection scheme for sensitive ecological environments near production sites.
  • Enable and facilitate reporting on new environmental and other compliance efforts.


  • Greatly reduced monitoring effort and cost.
  • Drastically increased processing speed for remote sensing and geospatial datasets.
  • Enabled large-scale observations without the need for additional workload for on-site teams.
  • Enhanced automation of monitoring and reporting.
  • Help fulfilling environmental, safety and biodiversity requirements.


  • Deep learning invasive species detection model
  • Biodiversity and habitat suitability model
  • Baseline for automated yearly reporting

Quick Facts

  • Geospatial data processing speed-up of > 100x
  • Allowing for much faster, more targeted monitoring
  • Reduced compliance and labor cost