AI Mapping Risks to Wildlife in Tanzania: Rapid scanning aerial images to flag the changing frontier of human-wildlife proximity

Mapping wildlife and human distributions are critical to mitigating human and wildlife conflict and conserving wildlife, habitat, and human well-being. Aerial surveys are a critical tool, but new methods for these surveys generate massive image archives. The act of scanning these images is time-consuming and difficult, leading to significant delays in converting data into action. To address this Development Seed and the Tanzania Wildlife Research Institute (TAWIRI), developed an AI-assisted methodology, specifically, Tensorflow based image classification and object detection methods that significantly increase the speed of spotting and counting wildlife, human activities, and livestock after aerial surveys. Our AI-assisted survey method to map wildlife and human distributions and to detect potential conflict areas between wildlife and the human-associated activity for Tanzania. Once the training data quality and model performance of AI-assisted workflow mature and stabilize, we foresee the hours spent on getting accurate human-wildlife proximity maps would only take 19% of current human manual workflow, and potentially reduce the cost of identifying and counting objects over 81,000 aerial images from $20,000 to less than $5,000.