Integrating satellite-based forest disturbance alerts improves detection timeliness and confidence

Background

Satellite-based forest monitoring systems are essential for detecting deforestation and supporting climate change mitigation efforts. Multiple alert systems exist, including Global Land Analysis and Discovery (GLAD)-Landsat, GLAD-Sentinel-2, and RADD, each with distinct capabilities and limitations related to sensor type and environmental conditions. Optical systems struggle under cloud cover, while radar systems may miss certain disturbance signals. This creates uncertainty for users and highlights the need for integrated monitoring approaches.

Goals and Methods

This study evaluates whether integrating multiple alert systems improves detection performance. It combines radar and optical alerts across ten sites in the Amazon Basin, representing diverse disturbance types. The analysis applies different confidence rulesets and tests both pixel-based and spatial integration approaches. Detection accuracy, timeliness, and confidence levels are assessed using 2021 observational data and high-resolution validation datasets.

Conclusions and Takeaways

This study finds that alert integration significantly improves detection rates and reduces delays. Combining radar and optical data enhances monitoring reliability across varying environmental conditions. The introduction of a highest confidence alert class improves decision-making without increasing false detections. Practitioners benefit from this more timely and actionable information for enforcement and conservation. Future research should refine integration frameworks and expand operational implementation globally.