Projects

Pedestrian Activity & San Francisco's Hills

Kepler.glPythonGIS
Fall 2022
Future Mobility Workshop
Columbia GSAPP

How does San Francisco's terrain — specifically areas with slopes of 20% or greater — correlate with pedestrian behavior? Spatial analysis of AOMA trip data reveals that topography shapes mobility patterns in ways transit maps don't capture.

Scroll
01

Research Question

Method
AOMA trip data
Terrain analysis
Spatial correlation

This research investigates how San Francisco's topography — particularly areas with incline slopes of 20% or greater — correlates with pedestrian trip patterns documented in the AOMA (Activity-Oriented Mobile Application) dataset.

The study examines whether terrain significantly influences user mobility behavior beyond what transit access alone predicts, using Kepler.gl for spatial visualization and Python for data processing.

02

Data Cleaning

Before and after processing the AOMA trip dataset
Raw AOMA trip data before cleaning — noisy GPS traces across San Francisco
RAW DATA
Before cleaning — noisy GPS traces with vehicle and transit trips mixed in.
Cleaned AOMA trip data showing pedestrian activity patterns
PROCESSED
After cleaning — pedestrian trips isolated, revealing terrain-shaped mobility patterns.
03

Analysis

Kirthi Balakrishnan & Lizzie Lee

Instructor: Professor Anthony Vanky