The research was designed to determine the outdoor recreation: activities of 73311 State University students and the reasons influencing their selection. Differences in outdoor recreation activities and the reasons for their selection between male and female students, among freshmen, sophomore, junior, senior, and graduate students, and according to sex and year of attendance in college were investigated.The sample for the study consisted of 625 Ball State University students living in on-campus housing during the Winter Quarter 1976-77. These students were selected using a proportional random sampling design method. An. outdoor recreation activities questionnaire was mailed to each of the students selected and 69% were returned.The findings of the survey revealed that swimming was the favorite outdoor recreation activity for 85% of Ball State University students. The reason for selecting outdoor recreation activities having the most influence for 87% of Ball State University students was "for satisfaction and enjoyment."Data from the study revealed that outdoor recreation activities selected by Ball State University students are those that require a minimum amount of money, require few special skills, require little time, and require few special facilities for participation. / Department of Natural Resources

This study was an effort to identify the reasons for use or under use of neighborhood parks in Fort Wayne, IN and to suggest the solutions for the problems found. Two heavily used parks and two underutilized parks were chosen after an interview with the Director of Parks and Recreation Departments of Fort Wayne. Questionnaires and direct observation were the two major tools used to understand user preferences and tendencies. Each data were analyzed to find out the differences between the heavily and underutilized parks in the categories of age, sex, income and race. The significant differences between under and heavily used parks were found by the quantity and quality of each park's facilities and by the racial characteristic of residents around the each park. Environmental and social factors, and user satisfaction with their neighborhood park are suggested to be the solutions. The solutions may be used as a general recommendation to improve the conditions of neighborhood parks. / Department of Landscape Architecture

This study was designed to address the issues germaine to the land planning and rehabilitation strategy of a surface-mined land area for reuse as a water-based recreational facility. This development, the White River Waterpark, is proposed as a regional level facility.The report is divided into three sections. The first introduces the notion of rehabilitation as a necessary consideration for efficient land use planning. The second section provides background material on the process and methods of sand and gravel excavation and the resultant features which affect rehabilitation and reuse. Section three presents the design process for the Waterpark beginning with the formulation of planning objectives for facilities and activities, an inventory of the existing land base and an analysis of site features. These stages allow the determination of development and land use recommendations and conceptual design plans. Each stage of the planning process is documented in written and graphic form explaining the basis for decisions and proposals articulated in the Land Use Master Plan and supportive documents. / Department of Landscape Architecture

An important requirement of a rational policy for provision of outdoor recreation opportunities is some understanding of natural processes and public concern and /or preferences. Computerized land use suitability mapping is a technique which can help find the best location for a variety of developmental actions given a set of goals and other criteria. Over the past two decades, the methods and techniques of land use planning have been engaged in a revolution on at least two fronts as to shift the basic theories and attitudes of which land use decisions are based. The first of these fronts is the inclusion of environmental concerns, and the second is the application of more systematic methods or models. While these automated capabilities have shed new light on environmental issues, they, unfortunately, have failed to develop sufficient intelligence and adaptation to accurately model the dynamics of ecosystems.The work reported proceeds on the belief that neural network models can be used to assess and develop resource management strategies for Mounds State Park, Anderson, Indiana. The study combines a photographic survey technique with a geographic information system (GIS) and artificial neural networks (NN) to investigate the perceived impact of park management activities on recreation opportunities and experiences. It is unique in that it incorporates both survey data with spatial data and an optimizing technique to develop a model for predicting perceived management values for short and long term recreation management.According to Jeannette Stanley and Evan Bak (1988) a neural network is a massively parallel, dynamic systems of highly interconnected interacting parts based on neurobiological models. The behavior of the network depends heavily on the connection details. The state of the network evolves continually with time. Networks are considered clever and intuitive because they learn by example rather than following simple programming rules. They are defined by a set of rules or patterns based on expertise or perception for better decision making. With experience networks become sensitive to subtle relationships in the environment which are not obvious to humans.The model was developed as a counter-propagation network with a four layer learning network consisting of an input layer, a normalized layer, a kohonen layer, and an output layer. The counter-propagation network is a feed-forward network which combines Kohonen and Widrow-Hoff learning rules for a new type of mapping neural network. The network was trained with patterns derived by mapping five variables (slope, aspect, vegetation, soil, site features) and survey responses from three groups. The responses included, for each viewshed, the preference and management values, and three recreational activities each group associated with a given landscape. Overall the model behaves properly in learning the different rules and generalizing in cases where inputs had not been shown to the network apriori. Maps are provided to illustrate the different responses obtained from each group and simulated by the model. The study is not conclusive as to the capabilities of the combination of GIS techniques and neural networks, but it gives a good flavor of what can be achieved when accurate mapping information is used by an intelligent system for decision making. / Department of Landscape Architecture