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Predicting Food Crises 2020, Dataset for reproducing working paper results

Afghanistan, Burkina Faso, Chad, Congo, Dem. Rep., Ethiopia, Guatemala, Haiti, Kenya, Malawi, Mali, , 2007 - 2020
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Reference ID
WLD_2020_PFC_v01_M
Producer(s)
Bo Pieter Johannes Andree, Andres Chamorro, Aart Kraay, Phoebe Spencer, Dieter Wang
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Jan 16, 2021
Page views
2003
Downloads
173
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  • predicting_food_crises_data

Rainfall Estimates from Rain Gauge and Satellite Observations (CHIRPS) - Anomalies (rain_anom)

Data file: predicting_food_crises_data

Overview

Valid: 183596
Invalid: 0
Minimum: -42.511
Maximum: 80.804
Type: Continuous
Decimal: 0
Start: 161
End: 177
Width: 17
Range: -42.5106506347656 - 80.8044204711914
Format: Numeric

Description

Definition
Anomalies are calculated by substracting the current monthly value from the long-term average for that month.
Source of information
CHIRPS Pentad, processed in Google Earth Engine). Cropland mask (GFSAD), pasture mask (FAO - FGGD)

Others

Notes
Frequency: Raw images (5-day) are aggregated to the monthly level using the average value. Monthly images are summarized to the district level using the average value.
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