Date of Completion


Document Type

Honors College Thesis


Environmental Sciences

Thesis Type

Honors College

First Advisor

Eric Roy

Second Advisor

Chris Koliba

Third Advisor

Gillian Galford


spatial modeling, circular economy, waste management, resource management, planning


Standard linear economic practices of extraction, consumption, and disposal can lead to shortages of non-renewable resources, buildup of waste, and negative impacts to the environment and human health. An alternative is to close the material loops of consumption and production using resource recovery and reuse practices, which are often referred to as a circular economy. To help increase the efficiency and sustainability of such practices, tools are needed to determine potential spatial flows of a recovered material to areas where that material can be reused. A few of these tools have been used in other studies, and in those cases the tools were not designed to facilitate easy application in other analyses. In this project, a general resource recovery and reuse spatial model called the Resource Areal Distribution (RAD) model was developed in ArcGIS Pro to inform resource recovery and reuse across any landscape. This model accepts two inputs: a resource recovery raster and a potential reuse raster. The model first identifies and fulfills demand of areas of potential reuse closest to each recovery location. Distribution is simulated to the next closest areas of potential reuse, and this spatially optimized distribution occurs until every recovery location is depleted. The model produces outputs that show the potential spatial distribution of reused materials. This general resource redistribution model can be applied to big picture questions concerning recovery and reuse at a landscape scale. Modified versions of this model may be used as a screening tool to inform the design of resource management practices in regional and local contexts as well.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.