Dynamic Land Use

  • Michael Ulm (Speaker)

    Activity: Talk or presentation / LecturePresentation at a scientific conference / workshop


    In order to better allocate scarce resources for long term development projects, more information is needed on how residents move through and use a city. Traditional data sources such as zoning regulations and travel surveys are often idiosyncratic, expensive, and infrequently updated. Mobile phones offer a far richer data source to measure the urban environment. Using anonymized location data for millions of phone events within a city, we use machine learning techniques to classify zoning across the city with high rates of accuracy.
    Period4 Nov 2011
    Event titleMIT HumNet Seminar
    Event typeOther

    Research Field

    • Former Research Field - Mobility Systems