Geo-Vegetation Spatial Information Model
This is a small project in Xinformatics at RPI, the project looks at new ways to visualize data. We try to use a spatial information model in a way to analyze agricultural data, specifically trying to see a way if we can match vegetation with precipitation. By doing this, it'll be easier to see the correlation between the two data points in a 3D visualization.
The application includes a legend, checkboxes for enabling and disabling data layers, and a calendar for inspecting a particular date. The data pipeline pulls from NASA, NOAA, and USGS sources.
We hosted all of the data in AWS.