Aerial Imagery and AI for Wildlife Population Monitoring

Wildlife Mapper leverages cutting-edge aerial imagery combined with deep learning algorithms to monitor and conserve the world’s dwindling wildlife populations. This innovative approach offers accurate, efficient, and wide-scale surveillance of species like the African bush elephants and Steller sea lions, ensuring timely and effective conservation efforts.

The primary objectives of the Wildlife Mapper project were to:

• To utilize satellite imagery and aerial photography for efficient wildlife monitoring.
• To develop and refine deep learning models for accurate animal counting, even under challenging conditions.
• To inform conservation policies and actions based on real-time and accurate data.
• To provide a holistic view of ecosystem health and mitigate human-animal conflicts.
• To advance the integration of technology in the realm of wildlife conservation and offer a replicable model for other endangered species.