Akademik Veri Yönetim Sistemi
APPLIED GEOGRAPHY, cilt.83, ss.130-140, 2017 (SSCI)
Landscape is a product of interactions between human and nature that bring multiple characteristics to discrete geographic settings. Landscape character assessment (LCA) is a process of describing, mapping and evaluating distinct characters in the landscape. The aim of this study is to integrate objective and subjective assessment in landscape classification in the case of Side district in Antalya, Turkey. The methodology of the study is based on a holistic approach to combine map-based biophysical information and on-site visual landscape characteristics into the LCA process. Principal component and cluster analysis were used to understand relationships and spatial patterns between 29 landscape character areas and types which were previously defined by previous work. The main source of data was landscape characters, and 35 character attributes was processed as variables. Cluster analysis showed that landscape character areas and types in Side were gathered into two main cluster groups and five sub clusters. The majority of landscape character areas tended to constitute separate subclusters, while character types appeared to form large groups of clusters in which recognisable land-use patterns were the main activity. According to the cluster dendrogram, it was possible to interpret spatial linkages between the clusters of character areas and types and to delineate geographic classification of the main landscapes in Side. Scaling relations for LCA in a pattern-process-product framework provided an explicit understanding of the data layers in landscape classification and where the clustering can function. Biophysical characteristics comprised the pattern of the landscape, while visual characteristics demonstrated the condition of the landscape as a product. The process depends upon transformation between the objective and the subjective as a link between pattern and product. Further steps would be to conduct semi structured surveys to assess local perceptions and preferences about landscape characters for landscape quality objectives. (C) 2017 Elsevier Ltd. All rights reserved.