Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** in the forestry industry,…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** in the forestry industry, existing risk assessments are complex and time consuming, limiting the ability of forest management professionals to accurately and quickly perform risk assessments in real time. Visimo proposes to develop a risk mitigation software application which uses a combination of machine learning (ML) and subject-matter expertise (SME) to reduce environmental degradation during forestry operations. Visimo's tool will predict the impact of specific forestry operations on user-specified landscapes using environmental variables related to soil, water, and residual stand quality and predict the immediate impact of land use decisions on the environment, providing mitigation strategies to reduce degradation in real time.visimo's proposed solution builds on our commercialized job safety analysis (JSA) tool for the construction industry, which visimo also successfully adapted to predict risk on small and midsize farms. Visimo's primary objective for phase i is to prove that our established risk prediction model can be adapted to forestry while maintaining similar predictive accurary.success in creating the proposed solution, and developing beyond phases i and II, will allow visimo to supply foresters (both private and public), land managers, extension agents, and other forestry stakeholders with an efficient, intuitive tool to support tactical and strategic planning in land use decision-making. This will reduce environmental degredation through an increased ability to accurately and quickly know whether forestry operations adhere to forestry best management practices.