Interactive Landscape Design
In Case 1, the optimal results were almost achieved because the average user satisfaction value was 4.2 out of a possible 5, as shown in the questionnaire results in Table . The rate of textures for the first generation was relatively equable as shown in Table . Textures No. 4 and No. 3 were selected with a similar frequency, as shown in Table .
In Case 2, the optimal results were also nearly achieved because the average user satisfaction value was 4.2, as shown in the questionnaire results in Table . In Table, textures No. 7 and No. 1 were selected approximately 40% of the time. However, the selected ratio of textures in the first generation was biased unlike in Case 1 because of the disproportionate rate of textures for the first generation. It is necessary to examine whether the texture that was finally selected was chosen. As shown in Table, the number of evaluations for wall positions was 2.3, for heights was 1.8, and for textures was 1.9. The wall positions evaluated at the beginning were evaluated the most times; thus, it is considered that users may have been too tired or bored to evaluate the urban landscapes as a whole as the number of evaluations increased. That is to say, if the overall number of evaluations was high, the number of evaluations of a given element decreased over time; thus, it is necessary to examine the evaluation order and evaluation method because the evaluation order may have affected the optimal results.
In Cases 2–2 and 2–4, four of the height values (Average, Standard deviation 1, Median value, and Standard deviation 2) were relatively close, as shown in Table . In particular, standard deviation 2 in Cases 2–2 and 2–4 displayed a large difference compared to the other cases. Furthermore, the median values in Cases 2–2 and 2–4 were high. The urban landscape in Cases 2–2 and 2–4 had large differences in height as shown in Figs. and . Many high buildings were selected in Cases 2–2 and 2–4. Furthermore, the height values of Cases 2–7 and 2–9 were relatively close, as shown in Table . The average and median values of Cases 2–2 and 2–9 were also relatively close. However, the standard deviation 1 and 2 in Cases 2–7 and 2–9 showed a large difference compared with Cases 2–2 and 2–4. If the average heights of buildings were close, while, on the other hand, the difference in adjacent buildings was large, users might perceive a different image with respect to their urban landscapes. The urban landscape in Cases 2–7 and 2–9 comprised small height differences and more gradual changes in height, as shown in Figs. and . In Cases 2–2 and 2–6, the difference between the average, standard deviation 1, median value, and standard deviation 2 height values was large, as shown in Table . In Case 2–2, the heights of buildings in the urban landscape were perceived as jagged as shown in Fig. . However, for Case 2–6, the building heights of the urban landscape were perceived as low and their changes were small as shown in Fig. . For heights in Cases 2–9 and 2–10, the average and median values that mean average heights of buildings in Case 2–9 were larger than their values in Case 2–10. However, standard deviations 1 and 2, which mean variation in the heights of buildings in Case 2–10, were larger than their values in Case 2–9, as shown in Table . In Case 2–9, the building heights in the urban landscape were perceived as high and their changes were small as shown in Fig. . However, in Case 2–10, high buildings were also chosen although low buildings were also frequently chosen as shown in Fig. . For this reason, the standard deviations 1 and 2 in Case 2–10 were larger than in Case 2–9.
The questionnaire results showed that both feelings of tiredness and ease of making choices were slightly higher for Case 2. Therefore, while individual evaluations were considered easier than simultaneous evaluations, on the other hand, individual evaluations require many generations to reach convergence. Simultaneous evaluations like Case 1 do not require many generations to reach convergence and it is easy to use the system because three parameters are evaluated simultaneously. The characteristics of each case like usability and ease of making selections were identified.