ITERATIVE NEW YORK
ABSTRACT
A SCIENTIFIC APPROACH TOWARDS URBAN PLANNING
In a world flooded with information, both high and low quality, there is a new potential for developing sub-urban and urban areas. We collect every bit of information generated by humans and the environment, then processed and stored by machines.
These strings of information can allow as to take a deeper and finer look into our built environments, analyze in precise detail and arrive to several planning iterations generated by input data.
Altough in architecture there is always a political & ideological component, a data driven plan reduce significantly the dogmas of the human intellect. Allowing us to reach a more just, fair and precise result.
​
New York City, trough its plataforms like NYCopendata, CoredataNYC, and the federal site census.gov, provide a large database open for public use.
This project attempts to get to the precise results previously mentioned.
Relying on this amount of data is fundamental for it to happen.
KEY PERFORMANCE INDICATORS BASED RESEARCH & URBAN DEVELOPMENT
DATA DRIVEN RESEARCH AND PLANNING
SCIENCE INSTEAD OF DOGMAS
This project is based on indicators provided by UN’s habitat III, as well as the SDG’s 11 & 12, also proposed by the UN to transform the city and make it more inclusive, energy efficient, more productive and cleaner.
SDG 11 talks about social issues, as well as making cities resilient to both social and physical changes. While SDG 12 addresses the economic factors, production and climate change.
Only by looking at as many layers as possible; the physical elements, the statistic layers, the social layers and the untangible layers it is possible to see the city as a whole, as a living organism, a game, that must be approached to taking into account all of this factors. As the world gets more and more complex, diverse, unequal and polluted, the proper way to address city and building planning is a data based approach.
​
The thesis proposes: Take the indicators of a city and make it a project. As the project's success is only measurable by their Key Performance Indicators.
The first part of the project (and its process) deals with data scraping, data vizualisation in order to identify critical areas. Further on, the planning requieres a Predicitive Analytics process, in which by using Machine Learning tools such as Non-Linear Regression, Neural Network and K-means clustering algoirthms its possible to assess, what area, which indicator and what program to address planning wise.
Prosperity
With an estimated population of 8.55 million inhabitant, the New York City Metropolitan Area is one of the most populous urban agglomerations in the world. New York City lies in the State of New York which is bordered by New Jersey and Pennsylvania to the south and Connecticut, Massachusetts, and Vermont to the east; And it is the state's most populous city and its economic hub.
New York City is a global city, exerting a significant impact upon commerce, finance, media, art, fashion, research, technology, education, and entertainment. Being the home of the United Nations Headquarters, New York City is an important center for international diplomacy and has been described as the cultural and financial capital of the world, as well as the world's most economically powerful city. Many landmarks in New York are well known to both international and domestic visitors, with New York State hosting four of the world's ten most-visited tourist attractions in 2013: Times Square, Central Park, Niagara Falls, and Grand Central Terminal.
New York is home to the Statue of Liberty, a symbol of the United States and its ideals of freedom, democracy, and opportunity. In the 21st century, New York has emerged as a global node of creativity and entrepreneurship, social tolerance, and environmental sustainability. New York's higher education network comprises approximately 200 colleges and universities, out of which some have been ranked among the top 35 in the world
