A Data-Driven and Generalizable Model for Classifying Outdoor Recreation Opportunities at Multiple Spatial Extents (data and code)

Summary:  View help for Summary The Recreation Opportunity Spectrum (ROS) framework spatially delineates a landscape into discrete classes believed to provide relatively unique outdoor recreation opportunities. The framework is an integral component of numerous outdoor recreation and tourism planning efforts. However, the effectiveness of the framework as a management tool has been limited given: 1) its dependence on anecdotal perceptions of managers as opposed to objective and reliable metrics; 2) its application at a singular spatial extent; and 3) its limited ability to provide prescriptive guidance on how outdoor recreation should be managed. We present a data-driven and generalizable model to define and quantify ROS classifications at multiple spatial extents. The model is structured around the three setting characteristics (biophysical, managerial, and social) believed to influence the types of outdoor recreation opportunities provided in a particular place. Each characteristic is quantified using free and publicly available data. The model’s analytical workflow yields discrete ROS classifications unique to the spatial extent at which it is applied (e.g., statewide, across an entire national forest, across just a ranger district, etc.). We demonstrate the flexibility and utility of the model by applying it to three spatial extents (statewide, regional, and local) within Utah (USA). Each application yields meaningful characterizations of the outdoor recreation opportunities provided across the landscape, allowing the decision makers which operate at each of these extents (e.g., state legislatures [state], regional collaborative initiatives [regional], and land management agency line officers [site-specific]) to make decisions informed by data and a transparent analytical process. The model can serve as a catalyst capable of unifying disparate visitor use management frameworks around common data, and a common model, for classifying the distinct types of wildland recreation settings upon which outdoor recreation opportunities depend.

Funding Sources:  View help for Funding Sources Utah State University - Extension

Subject Terms:  View help for Subject Terms outdoor recreation; public land management; open science; big data

Geographic Coverage:  View help for Geographic Coverage Utah, USA

Time Period(s):  View help for Time Period(s) 2006 – 2021

Data Type(s):  View help for Data Type(s) aggregate data; census/enumeration data; event/transaction data; geographic information system (GIS) data