VTechWorks staff will be away for the winter holidays starting Tuesday, December 24, 2024, through Wednesday, January 1, 2025, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!

Virginia Tech GIS and Remote Sensing Research Symposium

Permanent URI for this collection

https://hdl.handle.net/10919/88978

Browse

Browsing Virginia Tech GIS and Remote Sensing Research Symposium by Author "Braff, Pamela"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Spatial Data for Agent-Based Wood Supply Chain Modeling
    Kauffman, Joby; Prisley, Stephen P.; Yao, Xiaozheng; Crescenti, Neil; Braff, Pamela (2014)
    The Center for Natural Resources Assessment and Decision Support (CeNRADS) in the College of Natural Resources and Environment at Virginia Tech has been tasked with developing tools, data, and knowledge for analyzing questions about sustainable supplies of wood fiber in Virginia and beyond. An agent-based design provides an appropriate computational model for simulating the actions and interactions of paper mills, saw mills, and energy companies in the procurement of timber resources. The spatial location of timber resources plays a vital role in the decision making process of these wood consuming agents. Distance from the timber stand to the mill relates directly to transportation cost. Other variables that depend on the location of the timber stand, including slope and distance to a road, affect the operations costs of harvesting the resource. Future growth of the resources is related to spatial environmental and human factors such as soils and land use. Precise data is also needed to account for the spatial heterogeneity of the abundance of the wood resources. When modeling there is always a balance between simplicity and realism which is interrelated with the availability of data. This, in turn, creates the need for decisions on what data to use, how to obtain it, and how to use it in the model. The focus will include data requirements and options for the model, analysis tools needed to prepare the data, rationale that have influenced decisions, and factors for making future decisions as the model continues to develop.