Exploring a combination of objective and subjective assessment in landscape classification: Side case from Turkey. (June 2017)

• Record Type: Journal Article
• Authors: Atik, Meryem; Işıklı, Rabia Canay; Ortaçeşme, Veli; Yıldırım, Emrah
• Is Part Of: Applied geography. Volume 83(2017:Sep.)
• Page Start: 130
• Page End: 140
• Publication Date: 2017-06
• Subjects: Landscape character -- Landscape character assessment (LCA) -- Cluster analysis; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2017.04.004
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: 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 semistructured surveys to assess local perceptions and preferences about landscape characters for landscape quality objectives. Highlights: Landscape consists of both biophysical layers and visual qualities of an area. LCA is a tool to understand distinct characters and territorial dynamics of the landscape. Different statistics are used to extrapolate important characteristics into spatial framework. Cluster analysis can help to define spatial dimension and ongoing discourse in the landscape. Cluster added LCA can function as a holistic entity that to separate geographical areas.