The Neighborhood Exposome

Neighborhoods are vital components of political power, social connectedness, and long-term well-being. The neighborhood in which one is born and raised has been found to strongly influence health and opportunity. However, empirical studies of the relationship between neighborhood environmental factors and health impacts have been constrained by data limitations and methodological challenges, particularly in assessing the interrelationships between nonlinear causal factors and outcomes. The challenge is unpacking the black box of neighborhood effects: we know that neighborhoods matter, but it is still unclear exactly why and how people behave within them. Hyperlocal sensors and participatory data can provide more nuance about actual conditions in neighborhoods that are generally unobserved (like air quality and noise) and can also help us understand how people navigate their neighborhoods, what local services they use, and what public spaces they use or avoid. We address this challenge through our Neighborhood Exposome project.

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Paper
/ Jul 20,2018

Using machine learning and small area estimation

to predict building-level municipal solid waste generation in cities 

by Constantine Kontokosta, Boyeong Hong, Nicholas Johnson, Daniel Starobin
more on: data, environment
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Paper
/ Nov 09,2017

The Resilience to Emergencies and Disasters Index

Applying big data to benchmark neighborhood resilience capacity 

by Constantine Kontokosta, Awais Malik
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