1 Introduction In order to help us understanding river landscape better and create value as urban river landscape resources, we need more objective and quantitative cognition. Therefore in previous studies, we dedicated to make a synthesis evaluation system(SES) of Urban Planning·Physical evaluation·Psychological evaluation (Up·PHe·PSe), and confirmed validity of physical quantitative evaluation indexes(PHqi), then tried to make a predicting model to forecast satisfaction of landscape by PHe values. In this study, we try to confirm CG pictures, whether validate to landscape evaluation, both for PHe and PSe. Also, land cover data is sorted out, for making an assay of the relationship of 2D urban planning data and 3D space data.
2 Method of the study In this study, a city river space of Ota river in Hiroshima city was investigated as a case. At first, we took 312 photographs of the scenes of river-scape toward the opposite bank, by which all scape over of Ota river are covered, then 49 samples were selected, considering greenery and buildings. Then CG pictures, with same viewpoints, visual fields, shooting directions of photograph samples were created by GIS to simulate river landscape, based on actual 2D data. PHe values and PSe values of Photographs and CG pictures were acquired respectively. Also, land cover in prospective area of these samples were investigated and sorted out, and correlation coefficients among the three parts were analyzed of SES to confirm the validity of CG pictures for river landscape evaluation.
3 Conclusion Major findings are as follows:
1) We created the CG pictures of river landscape based on 2D data, by providing the floor height of the GIS building data, defining the viewing area, and adding green information. By calculating the area ratio of the landscape elements as the physical evaluation from the obtained CG pictures and comparing it with the actual landscape photograph, the validity of CG pictures was verified.
2) We confirmed the validity in PHe of CG images created from the GIS data. In particular, the proportion of the dominant factors (sky, buildings and trees, etc.) that had an enormous influence on the PHe, showed a significant correlation with the actual landscape values of about 0.9.
3) According to the comparison of results of PSe, the correlation coefficient between the items concerned with four factors of the previous report showed that the psychological evaluation had certain validity. However, as for the easy-to-judge landscape elements such as quantity of architecture and green plants, the lack of detail in the performance of the CG images was particularly ineffective for the comprehensive evaluation.
4) Judging from the correlation between PHe and PSe, CG pictures and landscape photographs had the same evaluation structure especially in terms of green-visibility.
5) We also organized the land cover of the prospective area and defined the building area shielding by greenery. The relationship between 2D urban planning data and 3D spatial data were suggested that utilization of prospective area had maintenance affection on PHe and PSe of the river landscape.
In the future, we will continue to study the impact of buildings and greenery on river landscapes, propose effective PHqi to explain the complexity and openness and plan to improve the comprehensive applicability of synthesis landscape evaluation systems.
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