Relative preferences of 90 images of forest stands, photos and virtual reality images were investigated by the intemet to develop a quantitative model for estimating scenic beauty preferences at the stand level, The r...Relative preferences of 90 images of forest stands, photos and virtual reality images were investigated by the intemet to develop a quantitative model for estimating scenic beauty preferences at the stand level, The relative priority values obtained from the questionnaire of a total of 259 judges were analyzed using regression methods for pairwise comparisons. Two models were developed based on two different groups of stands. Both models indicate that the priority of a forest stand increases with an augment in the number of bushes and trees, and also with the mean diameter of trees. On the other hand, the priority is low with large number of pines and small trees. Stands represented by photos receive better priority values than those represented by virtual reality images. When the background of the judges （gender, country or occupation） was included into the model as additional predictors, no significant improvements are achieved.展开更多
文摘Relative preferences of 90 images of forest stands, photos and virtual reality images were investigated by the intemet to develop a quantitative model for estimating scenic beauty preferences at the stand level, The relative priority values obtained from the questionnaire of a total of 259 judges were analyzed using regression methods for pairwise comparisons. Two models were developed based on two different groups of stands. Both models indicate that the priority of a forest stand increases with an augment in the number of bushes and trees, and also with the mean diameter of trees. On the other hand, the priority is low with large number of pines and small trees. Stands represented by photos receive better priority values than those represented by virtual reality images. When the background of the judges （gender, country or occupation） was included into the model as additional predictors, no significant improvements are achieved.
