Landscape is about the relationship between people and place and in 2000 was defined by the European Landscape Commission (ELC) as "an area as perceived by people whose character is the result of natural and human actions and interactions”. In the 70s the reason for studying the landscape was because of the necessity of attributing a value to it. Nowadays the motivations behind managing, conserving and enhancing the landscape is because the landscape is the place where people belong to and, consciously or not, recognise themselves. In addition, people identify different landscapes on the basis of the particular combinations of the elements in the landscape. As a consequence a landscape can be distinguished from another on the basis of its character which, according to the Landscape Character Assessment (LCA) guidance for England and Scotland (C. Swanwick and Land Use Consultant, 2002), is defined as “a distinct, recognisable and consistent pattern of elements in the landscape that makes one landscape different from the other rather than better or worse”. This definition was the starting point of a PhD research project aimed at developing and implementing a methodology able to identify and quantify the character of the Scottish landscape through the application of GIS and statistics. The reason for doing this research was to provide the landscape architects and practitioners with a tool that could help them to define the landscape character types in a more consistent, objective, and scientifically robust way. One of the objectives of the research was to identify the spatial patterns formed by the landscape elements by taking into account the influence of the spatial location. The first law of geography, which states that "everything is related to everything else but near things are more related than distant ones" (W Tobler, 1970), was transposed in the assumption of the presence of spatial autocorrelation amongst the data which contributes to form spatial patterns within the data. Since landscape comprises of many elements, data were also multivariate, thus the analysis required a method of calculation able to deal simultaneously with multivariate and spatial autocorrelation issues. MULTISPATI-PCA, a spatially constrained Principal Component Analysis, was the statistical technique applied for the analysis of the data whose results showed that it was possible to detect the spatial structure of the data and that each spatial pattern corresponded to a distinct landscape. Despite their importance in forming the character of the landscape, aesthetic and perceptual aspects were not inlcuded in MULTISPATI-PCA analysis. It was preferred to test the technique only on data that were quantifiable in a more objective way. Perhaps taking into account the human perception of the landscape can be the starting point for future investigation.

In landscape ecology, it is widely acknowledged that landscape is as much a social and cultural entity as it is biophysical, and that people and place must be jointly considered to fully understand the evolution of spatial pattern. This thesis explores the overlapping biophysical and human dimensions of landscape in the context of an (i) ecological and (ii) ethnoecological classification on the local landscape of the Tayal Mrqwang indigenous people in north central Taiwan. The goal of the ecological classification was to identify ecosystem types for a ~3000 acre landscape by relating vegetation patterns to gradients of physiography, soil, humidity, light, pixel brightness, and human modification across 76 transect sample plots. Using multivariate analyses, seven ecosystem types were identified, ranging from xeric through submesic pine, bamboo, alder, and laurel forests to mesic evergreen broadleaved and mixed coniferous forests. At the broad scale, ecosystems were distributed along gradients of elevation, soil, humidity and human modification, while factors related to local variability in physiography and soil development were more important at the fine scale (i.e., within elevational ecoregions). Within lower elevation sites in particular, patterns of forest variation and soil development were resonant of ancestral practices, including shifting cultivation, terrace farming, arboriculture, and selective extraction. The objective of the ethnoecological classification was to explore whether the Mrqwang people categorize landscape variation according to systematic or multidimensional knowledge structures. Results of interviews and free-listing exercises revealed an unsystematized classification that recognizes a continuum of forest variation through the intersection of three overlapping categories: history of disturbance, topography and substrate, vegetation. These categories are modified through land tenure and toponyms. The classification appears accommodating of personal experience, and it is theorized that this flexibility results in dynamic knowledge that evolves with time, generating variable characterizations of forest variation rather than formalized categories. The thesis concludes that despite the lack of formalization, the Tayal are nonetheless highly cognizant of how current forest variation coincides with the environment and the activities of their ancestors. This knowledge represents immense local expertise and must not be excluded from conservation and co-management projects in the local area. / NSERC CGS-D