Japanese university creates AI map to predict bear encounter risks

Researchers at Tokyo's Sophia University have launched an innovative artificial intelligence system designed to forecast bear encounter risks across Japan, responding to an unprecedented rise in fatal bear attacks this year.

AI-Driven Wildlife Risk Assessment

The research initiative, led by data science expert Associate Professor Yusuke Fukazawa, has developed a sophisticated prediction tool that analyzes multiple data streams to assess bear-human interaction probabilities. The system examines historical bear sighting reports from the past one to three years while incorporating environmental factors including forest conditions, roadway patterns, and local population density. This comprehensive analysis enables the AI to identify high-risk zones with remarkable precision.

High-Risk Areas and Vulnerable Populations

The university's analysis has identified specific geographical features that correlate with increased bear encounter risks. Mountain foothills, river corridors that provide concealed movement paths for bears, and isolated valley roads emerged as particularly hazardous areas. The research also highlighted that aging rural communities face elevated risks, possibly due to reduced capacity to respond quickly to wildlife threats. These findings underscore the complex intersection of environmental and demographic factors in human-wildlife conflicts.

Color-Coded Risk Mapping System

The research team publicly launched their interactive prediction map on October 20, featuring a color-coded system that divides each square kilometer into five distinct risk levels. The map categorizes areas from low to very high risk based on calculated probabilities of bear presence, ranging from 0-20% likelihood to 80-100% probability zones. This development comes as Japan's Environment Ministry reported 13 bear attack fatalities between April and November 5—the highest number recorded in recent history—prompting urgent solutions for community safety.