Detecting forest clearcuts year-round with radar and AI.
Qamcom is proud to contribute to an exciting project in collaboration with the Swedish Forest Agency (Skogsstyrelsen) and Spacemetric. Monitoring clear-cuts is critical for sustainable management, but traditional optical satellite methods face challenges from weather and seasonal changes. To address this, Qamcom together with Spacemetric are developing an AI-driven solution using radar satellite data for consistent and accurate forest monitoring year-round.
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Qamcom is proud to contribute to an exciting project in collaboration with the Swedish Forest Agency (Skogsstyrelsen) and Spacemetric.
Monitoring clear-cuts is critical for sustainable management, but traditional optical satellite methods face challenges from weather and seasonal changes. To address this, Qamcom together with Spacemetric are developing an AI-driven solution using radar satellite data for consistent and accurate forest monitoring year-round.
Challenges
- Optical satellite limitations – cloud cover, low light, and seasonal changes hinder consistent forest monitoring.
- Radar data complexity – radar imagery is affected by soil moisture, snow, and undergrowth, making interpretation challenging.
- AI integration need – successfully using radar data requires advanced algorithms and data processing.
- Scalability – reliable, year-round monitoring demands solutions adaptable to diverse conditions and regions.
What Qamcom did
Qamcom has taken a significant step forward in forest monitoring by using radar data and advanced AI algorithms. This approach addresses the limitations of traditional methods, offering precise, year-round insights into forest clear-cuts and changes.
Innovative data integration. Qamcom’s machine learning models analyze the radar data enabling all-weather imaging with hitherto unprecedented accuracy.
Precision dating of clear-cuts. Algorithms enable accurate identification and dating of clear-cutting events, even under challenging conditions.
Seasonal adaptability. Special emphasis has been placed on detecting changes in deciduous forests, which exhibit pronounced seasonal variability, ensuring reliable performance year-round.
Enhanced forest management. By overcoming environmental and technical challenges, Qamcom’s solution provides actionable insights for compliance, conservation, and sustainable forestry practices.
What's next?
Validated across multiple regions in Sweden – including Jönköping, Skåne, Västmanland, and Norrbotten – the system has demonstrated its ability to detect the majority of clearcuts while maintaining a low rate of false alarms, even when optical data is unavailable. The results support a scalable, deployment-ready capability for continuous forest monitoring, with straightforward adaptation to new regions through model fine-tuning.
With Qamcom’s expertise, this innovation is poised to support forestry’s role in combating climate change, preserving ecosystems, improving productivity, and ensuring compliance with forestry regulations.
For the latest results and technical details, read our white paper.
This white paper presents Qamcom’s operational clearcut detection system using Sentinel-1 SAR data and a radar-optimized neural network. The system detects forest clearcuts year-round, independent of weather or lighting. Validated across four Swedish regions, it achieves an 85% detection rate with a 10% false alarm rate for operationally relevant harvest sizes.