In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual reviews of satellite images taking multiple months, land-use change can today be monitored in near-real time.
In an article featured in Reuter’s portal, the author mentioned that some artificial intelligence-enabled tools are even allowing authorities to intervene before forest-loss happens, deploying scarce manpower and equipment to areas where they can have the most impact.
“The trend today is moving from retrospective measurement to proactive prediction,” explains Juan Lavista Ferres, chief data scientist and corporate vice president at Microsoft.
AI has been the “game-changer” in the development of predictive technology, according to Jorn Dallinga, programme manager at WWF. WWF’s Forest Foresight model, developed with partners including Amazon Web Services and Wageningen University, aims to predict illegal deforestation up to six months before it takes place, and with 80% accuracy.
An advanced machine learning model is trained on datasets including historic satellite imagery, and topological data on roads construction and population density. Once trained, it reads real-time satellite images, detects early deforestation predictors (such as expanding roads), and alerts local authorities, who can then take appropriate action and prevent the area from being illegally deforested.
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