You're working on an urban planning project. How can you make sure your models are accurate?

In Urban Planning, it is important to understand, how wide the goal is. When planning a house, the variety of users and hence the goals set for the building, is limited. When having an Urban Planning project, the goal is much wider, you need to conseder the needs of the whole city. And not just the ones living and working there, also the ones visiting there and the ones you would like to live / work there. Also the time scope is longer. And sustainability goals, obviously.

To ensure accuracy in urban planning models, the following steps should be taken: 1. Adopt a comprehensive information management strategy based on users' needs. 2. Prepare the structure and general conditions of the work environment in the users' organization. 3. Create mental preparation at the management level, and improve the level of data analysis awareness among the experts of the users' organization. 4. Improve the technical abilities of the management and expert staff of the users' organization.

Craft precision in your urban planning project by sculpting clear goals and scope, envisioning it as a city skyline. Define the landscape you aim to shape, from the towering skyscrapers of objectives to the intricate streets of project scope. It's not merely planning; it's creating a blueprint where every line has purpose. Consider it a personalized cityscape, ensuring accuracy in your models and coherence in your urban vision. Let your goals be the architects, constructing a city of precision that stands tall in accuracy and resonates with the heartbeat of your planning endeavor.

Cada situação pede uma metodologia diferente. Em alguns casos, será necessário inicialmente se verificar prioritariamente questões imobiliárias, legais, viabilidades documentais. Em outros casos, será mais importante iniciar a análise através de análise de dados de distribuições de necessidades, alcances, abrangências de soluções e intervenções. Em todos os casos as questões financeiras são proeminentes, mas para o Estado, em geral, são de impacto irrisório ou pode ser administrado a longo prazo. Consórcios bancários e processos de projeto, garantias, empreitas, contratos e demais itens amarrando o conjunto podem facilitar enquanto determinam o modelo de financiamento, e quem será o mandante, e quantos bancos estarão envolvidos.

Each situation calls for a different methodology. In some cases, it will be necessary to initially check real estate, legal and documentary feasibility issues as a priority. In other cases, it will be more important to start the analysis by analyzing data on distributions of needs, scope, scope of solutions and interventions. In all cases, financial issues are prominent, but for the State, in general, they have negligible impact or can be managed in the long term. Banking consortiums and project processes, guarantees, contracts, contracts and other items tying the whole together can facilitate while determining the financing model, and who will be the principal, and how many banks will be involved

In my experience, following these steps helps greatly in improving the choice of the right tools: 1. Calibrate Models: Fine-tune model parameters to match real-world observations. Validate model outputs against historical data or field observations to ensure alignment. 2. Compare Against Benchmarks: Benchmark model results against existing literature, established models, or expert opinions to validate accuracy and reliability. 3. Sensitivity Analysis: Perform sensitivity analysis to assess the impact of input variations on model outputs. Identify critical variables and their influence on model predictions.

Approaches begin with clarity of intention, and can, for example, be: 1) Focused only on geographic development 2) Smaller interventions aimed at private companies 3) Interventions with geopolitical impact 4) Urban remodeling with purely aesthetic or local use intentions 5) Remodeling of use and qualities, with local or contextual real estate impact 6) Inevitably, there is the military issue too 7) Rarely, there will be interventions with an isolated conceptual impact, or of a cultural nature, that do not actually have a financial base flowing through the government or in a consortium with banks and/or private companies. 8) Even "ecological" motivations serve seals or guidelines that ultimately serve interests.

You can use softwares like Tableau, SPADA, TransCAD, Urban Footprint, and so on. Or you can even use layers and fill them with maps with colours, and derive the compositions from a superposed self made software, which will do analysis through amount of, lets say, CMYK-Alpha-layer1, and so on. And do it manually if you will. On the other hand, while many people belive it is only a technical issue, maybe the main tool should be Excel, to deal with financial data - because in the end of the day, all that matters for all parts, even for the supposedly impartial government - is financial value. Since there are many parts involved, and often, banks and investors.

Creo que una herramienta importante es la gestión de la base de datos, que nos ayuda a tener modelos predictivos más precisos. Por ejemplo, analizar las interdependencias de los principales productos y servicios que genera una ciudad, nos permitirá saber cuales son las tendencias en el mediano y largo plazo, y en base a ello se puede proponer equipamientos urbanos adeacuados.

The most efficient models have 3 things in common: 1- Comprehensive data collection (including relative studies, initiatives, plans..) 2- Well structured roadmap for data analysis and gaps identification (preferably building on lessons learnt from similar planning projects) 3- Clear baseline assumptions and estimates for the model (These should be validated by Subject Matter Experts, as well as stakeholders) For this model to be resilient, it needs frequent check / update plan, to align with relative local and regional changes.

What most folks tend to underweight early on is the interaction between available data, methods, and cleanup labor. Some methods are more or less sensitive to noisy and nonlinear data. If you are using any form of linear modeling and public planning data, that’s a hard mix. In contrast, methods like random forest regression may be much less sensitive to outliers and include feature selection functions Dealing with this on novel data and tight timelines can be stressful, so consider dong a pilot to estimate data quality and required cleanup efforts. Also, private data vendors tend to be underused in public sector applications, but they can save you a tremendous amount of time in generating analysis ready or model ready data.

A coleta e validação de dados são essenciais para garantir que o planejamento urbano seja baseado em informações precisas, refletindo as necessidades da comunidade e levando as intervenções eficazes e sustentáveis no ambiente urbano. Além de lhe proporcionar uma decisão embasada, possibilitando através das informações: identificar necessidades; avaliar impactos e otimizar recursos.

Each situation calls for a different methodology. In some cases, it will be necessary to initially check real estate, legal and documentary issues as a priority. In other cases, it will be more important to start the analysis by analyzing data on distributions of needs, scopes, coverage of solutions and disciplines. In all cases, financial issues are prominent, but for the State, they are generally of negligible impact or can be managed over the long term. Banking consortiums and project processes, guarantees, contracts, contracts and other items linked to the set can facilitate the determination of the financing model, and who will be the principal, and how many banks will be involved.

Having correct urban data is vital for effective decision-making and planning across various domains. Accurate data provides insights into demographics, cultural diversity, and societal needs, enabling policymakers to design inclusive and equitable policies and services. For example, correct urban data is essential for urban planning, infrastructure development, and resource management, ensuring sustainable and resilient cities.

Testing the data and overlaping the model with real points is the way to prove your accuracy. You have to sekect a benchmark aa real point to overlap and compare it with the model to get zero tolarance.

Once the whole context of basic information is fulfilled, now it is time to sketch. Obviously, this is a task for architect urbanists, but they must not work alone. Not due to technical reasons only, but because colective spaces need many voices, to at least, spend some wasted opinions. And this is the starting model test: analysis, in a human level, that machines can not do. Discussions, exaustive discussions. After that, if you are lucky enough to find a ready made software to do another technical analysis - generally in the volumetric level - then you can resize some things like lanes, stairs, heights, areas, wagons, and so on.

Finalmente, el modelo puede ser probado cuando puede convertirse en una proyecto que se pueda ejecutar de acuerdo a la normatividad vigente de cada país. Los proyectos pueden ser: redes de vías para transporte público, espacios públicos verdes, equipamientos urbanos que complemente el desarrollo económico, etc

Design visualization and spatial referencing your models is key to testing functionality and efficiency of your system. In my practice I have picked that geo-modeling provides real time testing of your models this is an essential to urban design

Over my experience as a BIM Modeler, having an accurate digital model in urban design and planning is essential. Firstly, it enables effective visualization of proposed developments, aiding in understanding their impact on existing infrastructure and aesthetics. Secondly, digital models allow for quantitative analysis of factors such as traffic flow, pedestrian movement, and environmental impacts, facilitating informed decision-making. Thirdly, digital models promote collaboration among stakeholders and serve as communication tools for engaging the public.

Com o uso da Metodologia BIM no planejamento urbano, garantimos a precisão dos modelos a partir de um modelo federado e colaborativo. Modelos BIM passam por auditorias a cada fase de planejamento e coordenação.

Models are generally historical in nature, but a lot of them went out the window in the last three years. Living patterns, transit patterns and working patterns have all changed. And they aren't done changing yet. The safe thing might be to sit around for 10 years or so and see what models develop, but that's not realistic. What might make sense is to focus on shorter term initiatives while patterns are evolving. Some trends seem to be solidifying: Reduced commuter traffic Increase of mixed use A return to polycentric design Remote and hybrid work as the norm Less traffic to cities for work and more for entertainment and tourism Green and 15 minutes cities

By really knowing what the people in that area need. Urban planning is for the people and the livability of a certain area. Only real communication and mutual understanding will result in the best outcome.

It should be practical and most times self explanatory... A working plan or proposed plan should be eligible and be understandable by anyone who comes across it.