This design proposal explores the role of algorithms in order to mine, analyse, visualise, and design with large datasets to create innovative urban environment called City Mountain. This approach was developed in response to the complex, large scale issues that affect cities globally. Firstly, the designers collected data on the geological composition, building heights, borehole distribution, etc. in central London. Then based on the data visualisation and data overlay map, they decided to zoom in to Canary Wharf, which has significantly higher data density, as the design site. For the next step, the designers gathered various data related to the ground, adding up to 21 categories by 40,000 grids covering the whole site. At the same time, they further analysed the dataset by using Principal component analysis (PCA) and K-means clustering methods. Finally, based on data analysis, the designers proposed a design scheme aiming at creating urban underground public spaces and increasing greening.
