The application of spatial data analysis and visualization in the development of landscape indicators to assess stream conditions

The main theme of this research is the application of geographic techniques in a study involving environmental monitoring and analysis of the associations between landscape and in-stream characteristics in the Pacific Northwest. The geographic techniques used in this study include (1) geographic information systems (GIS) coupled with statistical analysis and (2) geographic visualization. The study area comprised 44 stream sampling sites and their respective watersheds in the Willamette River Basin of western Oregon.;The first paper in this dissertation is a literature review of scientific visualization relative to the field of geography. Integrating more traditional techniques of cartographic lineage with new methods of geographic visualization, this chapter introduces terminology related to geographic visualization as well as a variety of methods for the visualization of multivariate spatial data.;The second paper describes the use of scientific visualization to generate a composite indicator of landscape stress (i.e., a robust metric that represents multiple integrated characteristics of landscape disturbance). Through a unique approach, the power of the human visual system was used to synthesize multiple attributes of the landscape in mean ranks of watershed stress. Participants in this study were consistently able to distinguish between sites, and they were generally in agreement on how to rank sites.;The final paper describes the more traditional "lumped landscape" approach to indicator development and examines inherent scale properties of spatial data that may affect the generation of landscape indicators as well as the outcomes of statistical and GIS analyses in which they are used. In this study, grain (the finest level of resolution), extent (the area under consideration), and level of generalization in classification were systematically manipulated to determine effects of varying spatial scale properties on the generation of landscape metrics. Resolution of the data sets and differences between sites accounted for most of the variation in the landscape indicators generated.;Together these three papers describe and demonstrate the important role that geographic techniques, in particular GIS coupled with statistical analysis and visualization can play in better understanding our environment.