Quantitative Analyses of Urban Topography

Faculty: Dr. Steve Koonin

Assisted by Bartosz Bonczak

Teams: 1 & 2

Room: Director's Conference Room


Problem Statement

Given an observation point anywhere in the city, what can you see? What proportion of your view is sky, or water? Does the skyline include famous landmarks? How can you route your morning walk to stay on the sunny side of the street, or route the New York Marathon to keep runners cool in the shade? Where should urban scientists put cameras and other light­based sensors to capture representative information on buildings, energy use, and heat and chemical plumes? These questions are related by the concept of an intervisibility function and they rely on accurate surface model of the city.


The availability of LIDAR data sets for urban areas opens the possibility for case-specific and statistical exploration of the topography. Our starting point will be the 15 billion ­point NYC LIDAR dataset from 2010 that covered all five boroughs with roughly 1 ft horizontal and vertical resolutions. Students will build upon codes, data, and knowledge generated by a USI project from the last cohort [Varshavsky, Medina] to pursue a variety of questions depending upon their interests, capabilities, and the time available.


Sample questions include:

  • Verify the equivalence between the CUSP-rasterized and NYC Open Digital Elevation Model
  • Generate a heat-map over the city of statistical properties of the topography (rms variation, power-law of the height histogram, ???) and correlate with various demographic variables (income, property values, business / residential mix, …)
  • Use Monte Carlo methods to calculate the a) the height two-point function (i.e., probability that there is a given height difference as a function of separation) and b) statistical intervisibility function (probability that two randomly chosen points are intervisible as a function of their separation) both over various regions of the city
  • For some potential Urban Observatory sites, calculate the number of buildings visible and the fractions of their facades visible
  • For some potential pairs of Urban Observatory sites viewing the same neighborhood, calculate the additional coverage provided by the second site

Data


Additional Resources