asmikumar/poverty-prediction

Predicting poverty in Rwanda with nightlights, daytime satellite imagery, and survey data # Poverty Prediction by Combining Satellite Imagery, Survey Data, and Machine Learning Is it feasible to estimate the standard of living based on nighttime satellite imagery? Key Steps ------- 1. Download satellite night lights images from NOAA 2. Download DHS data for Rwanda 3. Test whether night lights data can predict wealth, as observed in DHS 4. Download daytime satellite imagery from Google Maps 5. Test whether basic features of daytime imagery can predict wealth 6. Extract features from daytime imagery using deep learning libraries 7. Replicate final model and results of Jean et al (2016) 8. Construct maps showing the predicted distribution of wealth in Rwanda A night time satellite imagery: ----- ![alt text][logo] [logo]: eoimages.gsfc.nasa.gov "night time satellite imagery" # Download nightlights images - **RESULT**: - `F182010.v4d_web.stable_lights.avg_vis.tif`: Single image file giving nightlights intensity around the world Go to the DMSP-OLS website and download the satellite nighttime luminosity data (roughly 400MB). Here we are using the file F182010.v4d_web.stable_lights.avg_vis.tif. # Download Rwandan DHS and construct cluster-level aggregates - **FILE INPUT**: - `rwanda_clusters_location.csv`: Coordinates of the centroid of each cluster - **RESULT**: - `rwanda_cluster_avg_asset_2010.csv`: Comma-delimited file indicated average wealth of each cluster Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition. For this assignment, you will need to download the 2010 Rwandan DHS data. **This requires registration.** Do not forget to request for the GPS dataset. The immediate goal is to take the raw survey data, covering 12,540 households, and compute the average household wealth for each survey cluster (think of a cluster as a …