Spatial characterization and analysis of forests in the Mount Bachelor volcanic chain, central Oregon Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/ms35tc04q

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  • Forest spatial pattern is a primary interest of landscape ecology due to the relationships between spatial configuration of biotic components and ecological processes. The spatial pattern must be measured in meaningful ways so that relationships between forests and their environment can be analyzed. Aerial and satellite imageries provide ecologists a variety of scale choices at which the spatial information of forests can be presented in levels ranging form individual trees to landscapes. The high lava plain of central Oregon is characterized by young lava flows of moderate relief interrupted by scattered cinder cones and lava buttes. The regosolic soils developed on pumice support open coniferous forests of nationwide significance. The relationship between forests and the harsh rocky land has not been analyzed, yet large portions of the forest have been logged at various intensities over the last 40-50 years. A better understanding of the relationship between forests and environment is needed for management of healthy forest ecosystems. It is the intent of this study to use remotely sensed data to measure the spatial variability of forest patterns across the lava landscape in Mount Bachelor volcanic chain, and to analyze relationships between forest structural attributes and environmental variables. First, I used aerial photographs to characterize tree point pattern and measure canopy crown closure and density. A step-wise digital approach based on spatial, spectral, and topographic characteristics of the photographic data was developed to measure forest spatial patterns. The method provides a fast and accurate, yet low cost way to characterize tree point pattern and measure canopy crown closure and density. Second, I used Landsat TM imagery to estimate leaf area index (LAI). A new approach using multiple regression analysis was developed to overcome the saturation problems of commonly used vegetation indices at high LAT ranges and improve the performance of Landsat TM data in estimating LAI. Finally, I conducted an analysis using the spatial data developed in this study and supplemented with that obtained from Deschutes Nation Forest. The study documents methods of integrating multiple GIS data layers for spatial analysis and parameterizing relationships between forests and environment.
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