URBAN ANALYTICS AND MODELLING TRENDS – 2020

Urban Analytics is essentially one of the most powerful tools that will end up benefiting both urban planners and the world in itself. These urban analytics are not just what planning executioners can act upon but something that can be taught in courses like Bachelor of Urban Planning, wherein bright minds can change the urban landscape in influential ways. This involves understanding the desires and requirements of the residents – these trends are definitely an insight into how people utilize and benefit from cities.

This does not include every potential expectation for city modelling, infrastructure, analytics and/or associated technologies. The salient points that we are about to illustrate are the ones which stand out to create the most impact.

  1. Using More Data Extracted From Participatory Design Efforts
  2. Participatory design includes the key stakeholders in the project who actively seek to improve via public input while the phases of planning and development are in progress.

    Inculcating participatory design to urban analytics eradicates the workflow being based upon previous data sets. Instead, surveys and constant feedback supply developers with up-to-date groups of information.

    A report published in 2019 also listed the options for working with high-end technology in the execution of participatory design. An example suggested, instead of assessing the city in its current state to envision possibilities, residents can utilize mixed reality technology to view virtual representations of proposed plans.

    Participatory design has showcased positive results, and interest in the concept is peeking as a result. Urban planners of 2020 and beyond, do strive to look at user feedback differently and see it as more than a data set. Students too, whether they are in the final year of their Master of Urban Planning course or just starting out their careers, should take notes and read up on how this can be transformed into a profitable activity.

  3. Usage of Analytics Platforms and Modeling to Address Pollution Levels

Air pollution or any kind of pollution is not at all a new challenge, but city dwellers are now becoming increasingly vocal of these issues that plague us. Urban planning professionals will need to take that into consideration as they chalk out their ambitions.

City planners should consider health as a priority, and not overlook the connection between air quality and health. In a 2018 opinion piece, Dr Maria Neira, the World Health Organization’s director for the Department of Public Health, Environmental and Social Determinants of Health, mentioned how more than 80% of cities around the world exceed air quality targets set by the World Health Organization.

Numerous campaigns across the globe in subsequent years have stressed how important it is to retain the quality of our natural elements and how to restrict pollution of the same.

Skip to today, data analytics and models can assist with cleaning up and all air quality issues. In Dublin, Ireland, automatic air quality monitors collect data that eventually gets compiled into reports. Those documents show the concentrations of known pollutants, and how far the levels are from European Union targets.

Google also has an air pollution mapping tool that allows people to see air quality levels on a street-by-street basis. The company initially made the resource available to users in the United States but has since expanded availability to several European cities.

3D Scanners and Modeling Tools

3D scanners and modelling tools can come as a brilliant aid to assist city planners by capturing physical layouts with utmost precision, showing future residents what they have to look forward to with a project. 3D scanners are available in abundance and in different varieties, included in these are resourceful, handheld models that have a five-meter range and tripod-style scanners boasting up to a 1,000-foot range.

3D models are as useful for residents as they are for the stakeholders in planning. From a  purely planning outlook, these models make it easier to demonstrate how all the pieces of a new project will come together to minimize the risk of unpleasant surprises. They also help build up some anticipation about what’s ahead.

3D scanners and models will continue to be a big player in the city planning process. Scanners being used in this manner will aid with the help of the resultant models to keep everyone informed and able to access the details they need about projects.

An Emphasis on Public Transportation Models in City Planning

City planners mostly come under the unfavourable side when it comes to any mention in the news. The mistakes of a city planner our illuminated with the brightest of spotlights there for the eyes of the public to see. This, however, is a practise which unforgivably misses out on the successes they’ve had in making city life easier.

The number one area with regards to urban development that has a full complaints box is public transportation. Commuters generally express grief about buses being late or inadequate transportation as per their needs.

Prescriptive analytics models could prove as a means to a solution to that hurdle. Prescriptive analytics models give planning professionals the convenience to input data associated with a set of problems, then let the platforms suggest solutions for solving them. On the other hand, predictive analytics help planners project how many people would be interested in utilizing a newer bus route or take joy in an extended weekend service.

Planning officials make use of public transportation-related modelling and have been practising the same long before 2020. However, in lieu of everything that has transpired this year and could transpire in the ones that follow, this technology should become more renowned.

If a city planner historically only gets a few residents’ feedback at very specific times—such as during public information nights and city council meetings—participatory design may represent a drastically new way of interacting with people. Being open to these analytics and model-based methods could help teams work more efficiently and achieve satisfying results, benefiting everyone involved.