A Study of Landscape Features in the Coastal Area of the Seto Inland Sea Based on Landscape Paintings

Int J Environ Res Public Health. 2023 Jun 18;20(12):6165. doi: 10.3390/ijerph20126165.

Abstract

Landscape paintings provide an abundant and objective representation of good and distinctive local scenery, which is widely used in local landscape analysis, so the comprehensive research of landscape paintings is fundamental and necessary for the subsequent landscape planning work. Landscape paintings include both planar information and spatial information. However, there has been little previous work on landscape paintings from both a three-dimensional and planar perspective, and the landscape features of landscape paintings have not yet been comprehensively clarified. Therefore, this paper, taking the Seto Inland Sea area as a case study, aims to comprehensively clarify the landscape features of the paintings and provide a valuable index of "good and characteristic landscapes" in this area based on the two planar features of element configuration and color, along with one spatial feature (element arrangement). To deeply clarify the typical landscape features of paintings, we attempt to propose a classification method by combining the similarity of features in different attributions. The results indicate that Sky, Green, and Sea are the most essential landscape elements, and yellow (orange), blue, and green hues are the most used in the paintings. In addition, the paintings were classified into eight typical landscapes, and seascape and field landscapes were the most significant presented in the landscape paintings in this area. This study presents a method to clarify the landscape features from both planar and spatial perspectives, providing more comprehensive guidance and data support for the subsequent landscape planning work and analysis-especially in regional landscape exploration-and for the development of tourism landscape resources in urban planning.

Keywords: cluster; landscape feature; landscape painting; similarity.

Publication types

  • Research Support, Non-U.S. Gov't

Grants and funding

This work was supported by JST SPRING, Grant Number JPMJSP2136.