Web scraping and mapping urban data to support urban designdecisions

Cities generate data at an increasing rate, in an increasing volume, and in an increasing variety, all of which is becoming more easily accessible and processed as technology advances. Because of this, the potential for this data to feed back into the city to improve living conditions and the efficiency with which resources are utilised increases. This paper builds on this potential by presenting a study that proposes methods for collecting and visualising urban data with the goal of assisting in the decision-making process for urban design. To collect a variety of publicly available data within the Kadköy municipal boundaries of Istanbul, we used web scraping techniques in conjunction with a visual programming software to map and visualise the information. This method, combined with the superposition of our resulting maps, helps us visually communicate urban conditions, such as demographic and economic trends based on online real estate listings, as well as spatial distribution and accessibility of public and commercial resources, in a clear and concise manner. We believe that this method, as well as the visualisations that result from it, have significant potential for assisting decision-making processes in urban design. With the advancement in Web Scraping Services technology, data has become more widely available and accessible for urban design, and it has also become more widely incorporated into decision-making processes related to urban design and planning.

UIF have witnessed the proliferation of big data, as well as research into its integration into the analysis, management, and decision-making processes. The DJUJFT 8IJMF has generated a lot of information about the urban environment, so academic, civic, and commercial research centres have been established to study the urban environment.

Communication and accessibility to designers, decision makers, and the general public continue to be a major concern for all parties involved. As a result of the diverse set of skills required to access and process the data in order to make it relevant and meaningful, this has occurred.

The purpose of this study is to present a methodology for urban data collection and visualisation that can assist urban designers in producing maps that communicate various urban patterns to stakeholders and decision makers in order to support urban design decisions, as well as to communities in order to better inform participatory processes. We also offer a collection of maps that were created using this methodology, as well as some fundamental geospatial analysis that were done in order to construct them. The following are the questions that we hope to be able to address via the research described in this article.

When it comes to urban planning, how might sources of publically accessible data that include geolocation information be relevant and valuable to them?

The question is, how can this information be obtained and visualised?

In what ways may the display of this data provide information that can be presented to decision makers even before any geostatistical analysis has been completed?

The study is unique in that we present a methodology for compiling a rich dataset, which we propose to be relevant for urban design decision-making processes, consisting of information drawn from multiple sources rather than studying a single source of data and its relevance for a specific urban issue, rather than studying a single source of data and its relevance for a specific urban issue. We also give a visual representation of each data set, as well as some fundamental spatial analysis techniques. We want to do this through facilitating rapid and simple visual analysis of data, as well as improved communication of this data to designers and decision makers. Furthermore, the Kadköy area of Istanbul has never before been the topic of such a thorough research in terms of the range of urban data and data sources that were used, as well as the mapping and visualisation tools that were used to do this. The data scripting, as well as all mapping, visualisation, and visual analysis procedures, were completed using the visual programming language. Our study has uncovered a variety of urban patterns that have been obvious via the maps that we have made using data gathered from a variety of geolocated urban data sources, which we have developed. Through the various maps we present in the following sections, we have identified two particularly significant cases that we believe have the potential to contribute to urban design decision dialogues: the exposition of public and commercial resource distribution, and the presentation of demographic and economic trends. These two examples are illustrated in the following sections.

We want to further enhance this study by including more detailed analysis into our research methodology in the future.