Web scraping and mapping urban data to support urban design decisions

Cities generate data in increasing speed, volume and variety which is more easily accessed and processed by the advance of technology every day. Consequently, the potential for this data to feed back into the city to improve living conditions and efficiency of utilizing resources grows. Departing from this potential, this paper presents a study that proposes methods to collect and visualize urban data with the aim of supporting urban design decisions. We employed web scraping techniques to collect a variety of publicly available data within the Kadıköy municipal boundaries of Istanbul and utilized a visual programming software to map and visualize this information. Through this method and superposition of our resulting maps, we visually communicate urban conditions including demographic and economic trends based on online real estate listings as well as spatial distribution and accessibility of public and commercial resources. We propose that this method and the resulting visualizations present valuable potential in supporting urban design decision-making processes.

Geospatial data, Urban data, Urban design decision support, Web scraping.