09:45 〜 10:00
[HSC06-04] A Study on Look up View’s Evaluation: A Case of Takao Quasi-National Park
キーワード：landscape, photographs, GIS, GPS
In natural recreational site, visitors experience a variety of landscapes. Visitor’s satisfaction comes from not only a superb landscape but also an accumulation of many landscape experiences. Hence, identifying pattern of landscape experience leads to better planning and management. In this study, focusing on the Look up View (LUV), we aimed to clarify its features through comparison with other landscape types. A survey was conducted with 60 respondents, and the Inariyama trail of Takao Quasi-National Park was selected as a site. The respondents were instructed to take over 15 photographs of landscapes which respondents prefer. They were also instructed that carrying GPS. Immediately after walking the site, respondents selected 15 photographs, and noted down 15 photographs profile (contents of photographs). Each 15 photographs were evaluated into five measures, 1) aesthetic, 2) naturalness, 3) rareness, 4) atmosphere, and 5) total evaluation, on a scale of one to five. 900 photographs were collected and categorized into 12 types. To compare four major landscape types (LUV, Prospect, Surroundings, Spatial trees) MANOVA with Tukey HSD post-hoc test was used. GIS analysis also conducted to examine spatial features of LUV.
The result of GIS analysis, LUV’s distribution was sparse, and spatial features were undetected. In the measure of aesthetic, mean value of LUV was the largest (4.15). It highly scored as well as Prospect (4.11) than Surroundings and Spatial trees (3.64, 3.76) in 99 % confidence. In the naturalness, LUV also scored the largest (4.11) as well as prospect and Spatial trees (4.03, 3.76), was higher than Surroundings (3.64). In the total, LUV scored 3.85 was equal to prospect (4.01) which is the best landscape type on the site. In the rareness, however, LUV was low scored (3.00) than Prospect (3.50). These showed that Look up View was a landscape type that had visitors feel deep impression despite being familiar with it. The findings lead us to conclude that variety of landscape experiences should be taken in account for landscape planning and management.
The result of GIS analysis, LUV’s distribution was sparse, and spatial features were undetected. In the measure of aesthetic, mean value of LUV was the largest (4.15). It highly scored as well as Prospect (4.11) than Surroundings and Spatial trees (3.64, 3.76) in 99 % confidence. In the naturalness, LUV also scored the largest (4.11) as well as prospect and Spatial trees (4.03, 3.76), was higher than Surroundings (3.64). In the total, LUV scored 3.85 was equal to prospect (4.01) which is the best landscape type on the site. In the rareness, however, LUV was low scored (3.00) than Prospect (3.50). These showed that Look up View was a landscape type that had visitors feel deep impression despite being familiar with it. The findings lead us to conclude that variety of landscape experiences should be taken in account for landscape planning and management.