KnowWhereGraph for Land Use Optimization: Achieving Sustainability and Efficiency

This research aims to enhance land utilization for agricultural and renewable energy projects by optimizing the identification process of suitable locations. The challenge of finding appropriate land, influenced by factors such as soil quality, terrain, and pollution, necessitates sophisticated tools and specialized knowledge. This study utilizes SPARQL queries against the KnowWhereGraph (KWG) and data from the gSSURGO dataset, processed through ArcGIS, to streamline this task. Through the integration of these resources, this research seeks to simplify the access and interpretation of critical data dispersed across various entities, enabling the achievement of efficient land use. The outcomes of this research are anticipated to contribute to enhanced food security, economic growth, and increased access to renewable energy, aligning with local and global sustainability goals. Focusing initially on Ohio-where the funding university is located-the methodologies developed could be adapted for broader geographical applications, making this approach a scalable solution for future land use planning.