| dc.description.abstract | The land cover of the urban area has changed rapidly due to human activities. As the urban population keeps increasing, some cities, especially cities in East Asia, start to grow vertically to create more available space in the limited land. Taipei city, the capital city in Taiwan, can also find this phenomenon. In recent years, many construction companies and high-tech companies have entered Neihu and Nangang, two districts in the east of Taipei, and developed tall buildings that reshape the urban structure significantly since 2000.
In this research, to analyze and model the vertical urban growth in Neihu and Nangang from 2002 to 2017, this study produced the building data using 1/1000 scale topographical maps to calculate the building area and total floor area and class the building height into three categories to find out the growth trend in the two districts. Then, the random forest (RF) algorithm is selected to model the building growth based on the three-building height classes, and the outcomes were verified by topographical maps. The results show that the total floor area and the tall buildings had increased both in Neihu and Nangang since 2002, showing the urban growth in the vertical direction is significant. The RF generates the probability maps of the potential distribution and change of tall buildings in the study area, and the modeling outcomes were assessed by AUC values in the tested years which are all higher than 0.9. About 70% of changed building height in 2007-2012 are correctly predicted by the RF model. The model reveals that the natural environmental factors and traffic factors are more important to affect the distribution of buildings with different heights. However, when predicting future building height, the AUC decreases to 0.8 when the predicting year is more than 10 years. This study gives an example indicating the applicability of RF to predict future urban structure in the vertical dimension which can greatly help the decision-making of land development for government and urban planners. | en_US |