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High Negative NVDI Anomaly (%) shaded orange / red
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Morocco 2016 Protest Map
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Food Crisis Zone Sous Valley and Conflict Events
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Red Areas = Decline in Light Consumption
Inspiration
We wanted to help solve the problem of optimizing delivery routes in troubled areas
What it does
We first forecast areas vulnerable to food security crisis if they meet two criteria:
(1) High Normalized Difference Vegetation Index (NDVI) Anomaly rates;
(2) Rate of population growth exceeding national average
How I built it
Step 1: Create Raster files of areas with high HDVI anomaly rates( negative)
Challenges I ran into
Getting Data from poorly organized and documented government sources, connecting to Descartes API
Accomplishments that I'm proud of
Working hard to solve major humanitarian issues
What I learned
Great geospatial data and analytic techniques
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