Principal Component Analysis (PCA) in Smart Growth Theory
- Qingqing Zhang
- Corresponding Author
- Qingqing Zhang
Available Online June 2017.
- https://doi.org/10.2991/ammee-17.2017.96How to use a DOI?
- Smart growth index, Principal Component Analysis.
- Today, smart growth theory is playing an important role in urban development. In order to help implementing smart growth theories into city design around the world, we select Bendigo in Australia and Galway in Ireland as the objects of study. We define a smart growth index to evaluate the success of the smart growth of a city. The higher the index is, the higher the level of urban smart growth will be. To build an evaluation system, we select 10 indicators of 6 similar mid-sized cities in Australia and Ireland respectively according to ten principles for smart growth and three E's. To eliminate the correlation among different factors, we use Principal Component Analysis to calculate the principal components of collected data and their contribution rate, then linearly combine the value of them to get smart growth function. Put the indicators 'data of Bendigo and Galway into the smart growth function to calculate smart growth index. We find that Bendigo's smart growth index is higher, but it is lower than the average level in selected cities of Australia.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Qingqing Zhang PY - 2017/06 DA - 2017/06 TI - Principal Component Analysis (PCA) in Smart Growth Theory BT - Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ammee-17.2017.96 DO - https://doi.org/10.2991/ammee-17.2017.96 ID - Zhang2017/06 ER -