Dr. Rakesh Mishra, Head of Research-Remote Sensing & AI, is a leader in AI, remote sensing, and scientific research, with over 15 years of experience. He holds a Ph.D. in Remote Sensing & Photogrammetry from the University of New Brunswick (UNB). Dr. Mishra leads interdisciplinary research in AI, quantum computing, and satellite data analytics, tackling climate change, resource management, and forestry. Also an Adjunct Professor at UNB, he excels in fostering innovation, securing research funding, and collaborating with diverse stakeholders. His expertise spans AI modeling, machine learning, and geospatial analytics, with applications in precision forestry and environmental sustainability. _________________________________________________________________ Presenting: Modernizing Forest Inventories with AI and Remote Sensing _________________________________________________________________ New Brunswick’s forests are a vital part of the province’s economy, environment, and way of life. They provide jobs, support biodiversity, and offer essential ecosystem services like clean water and soil protection. However, managing these forests efficiently and sustainably has become increasingly challenging due to costly and outdated forest inventory methods. Traditional approaches rely on expensive and time-consuming field surveys, aerial photo interpretation, and expensive LiDAR acquisitions that quickly become obsolete as forests continue to grow, change, and respond to natural and human influences. This presentation will showcase NHRI’s precision digital forest inventories solutions (PFIS) initiative. The PFIS utilizes advanced Artificial Intelligence (AI), deep learning, machine learning, and remote sensing technologies, creating a faster, accurate, and cost-effective way to collect and analyze forest inventory data. This modernized approach empowers decision-makers at all levels—forestry professionals, policymakers, Indigenous communities, and small woodlot owners—by providing high-frequency and accurate insights into the types of cuts (clear cuts, partial cuts), regeneration characterization, tree species, basal area, tree vigor, and growth rates.