The Interactive Map extracts data from Primary Land Use Tax Lot Output (PLUTO), US Census, NYPD, NYC Open Data (311 Complaints and Street Tree), Google Earth Engine, and MTA for land use, housing units, population, income, education, crime, noise complaints, green space and transport access from the years 2010 to 2017, for each tax lot in New York City.
The data was collected based on interviews with residential and commercial real estate developers who explained what drives the economics of developing an urban parcel.
By visualizing the spatial pattern of the data, the tool could help the policy makers, urban planners and the general public to assess urban evolution at the lot level, thus facilitating more evidence-based urban decision making, and improve the results of future rezoning.
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Land Use
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Housing Units
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Income
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Education
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Population
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Transit
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Noise
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Green
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With the extracted data above, two machine learning approaches were applied:
1. Regression: Build FAR Model
2. Random forest classification: Land Use Model
The result of the predicted land use model was visualized and compared with the rezoning outcome (land use in 2017 from Primary Land Use Tax Lot Output (PLUTO)).