Spatial Modeling & Forecasting

layers
Publications
chronometer
Research
document6
In the news
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Consulting

Agriculture, Land-Use,
Natural Resources, Energy
Complex Problems : Clever Solutions

Spatio-Temporal
Modeling
Data Visualization
Data Analysis
25231

Machine Learning
Bayesian Modeling
R
Python


In the follow example I use data from SafeGraph to generate an estimate of the % of time spent at home that cannot be explained by employment status. Blocks colored red have a high percentage of time spent away from home, that is not accounted for by their employment. Where job status is categorized as ‘full-time’, ‘part-time’ or ‘delivery/Uber/Lyft/etc’, and is derived by the day-to-day activity of each cellphone user. Blocks colored green are doing a good job staying home, controlling for whether or not persons leave home for work.