Illegal mining: a global threat to our planet

#ArtificialIntelligence is beginning to play a promising role in addressing this growing problem by analyzing satellite data to uncover illicit mining sites.

The @Amazon Mining Watch platform is a fascinating example that demonstrates how the combination of these technologies can drive real change. Launched in 2020 by the @Pulitzer Center and @EarthGenome, with the support of @Mozilla, the model scans satellite imagery of the Amazon rainforest to detect and monitor unlawful mining. Every four months, the system processes more than 326 million image analyses using Sentinel2 data, identifying open-pit illegal gold mining sites with over 99% accuracy.

However, identifying illegal mining sites and predicting potential future ones is a difficult task. It requires highly advanced AI models capable of detecting and tracking even subtle changes within environments characterized by dense vegetation and complex, varied terrain. For these models to be effective, they need vast amounts of diverse and accurately annotated satellite imagery for training.

Herein lies the key challenge. Collecting this training data is resource-intensive and often difficult to obtain, especially in the most inaccessible and geographically complex landscapes on Earth, like the Amazon rainforest or the Congo Basin.

This is where #SyntheticData for Earth Observation could make a real difference.

With synthetic training data it is possible to generate unlimited pixel-perfect satellite imagery, even for the most remote regions. These precisely labeled datasets, which include change detection, enable models to be trained faster, more accurately, and at a fraction of the cost and time required when using real-world datasets.

Synthetic Data can be a game changer in scaling the impact of AI’s role in protecting global ecosystems, without scaling the cost of using it.🚀

What do you think? Share your ideas on how we can build smarter models, for a healthier planet.🌱🌎

#AIforGood #EnvironmentalProtection #IllegalMining #EarthObservation  #Geospatial