Visual Preferences Assessment of Landscape Character Types Using Data Mining Methods (Apriori Algorithm): The Case of Altinsac and Inkoy (Van/Turkey)


Asur F., Deniz S. S., Yazici K.

JOURNAL OF AGRICULTURAL SCIENCE AND TECHNOLOGY, cilt.22, sa.1, ss.247-260, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 1
  • Basım Tarihi: 2020
  • Dergi Adı: JOURNAL OF AGRICULTURAL SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database
  • Sayfa Sayıları: ss.247-260
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

Nowadays, in environmental planning and management, the approach to protect visually diverse landscapes has been an important component in planning decisions. Visual quality analysis is a method to determine the visual quality and visual preferences of the landscape, by correlating its physical characteristics with perceptual parameters, whereby it is possible to demonstrate the visual potential of a field by converting qualitative definitions into quantitative data. The visual quality of the landscape is widely considered as an important resource worth preserving. Despite making a great effort to determine the factors that guide aesthetic preferences, the consensus in the judgments of people is neglected in most of such surveys. This study examines various types of landscape characters in Altinsac and Inkoy Regions (Gevas/Van) with spatial heterogeneity, because of the region's topographic structure and location. The characteristic structure of the region consists of mountains, lakes, forests, natural vegetation landscapes, and wildlife as natural landscapes. Also, road, rural settlement, agricultural landscapes, and historical structures are considered as cultural landscapes. In order to determine the participants' visual preferences of various landscape types with perceptual parameters, this study focused on consensuses through the Apriori algorithm, which is a data mining tool. Giving reference to define perceptual parameters, a survey with 202 participants was conducted using 9 different landscape character types selected. With questions about the appreciation of the beauty of the landscape scene, the consensuses on the landscape and its relationship with perceptual parameters, such as mysteriousness, typicality, vitality, safety, impressiveness, silence, perspective, degradation, and worth being protected, were examined. It was proven that the higher the visual quality of the landscape, the higher was the observers' consensus rate. Some suggestions and objectives are presented, based on the data derived from this study.