Predicting Food Crises 2020, Dataset for reproducing working paper results

Afghanistan, Burkina Faso, Ethiopia, Guatemala, Haiti, Kenya, Mali, Mozambique, Mauritania, Malawi, Niger, Nigeria, Sudan, Somalia, South Sudan, ..., 2007 - 2020

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Reference ID

WLD_2020_PFC_v01_M

DOI

https://doi.org/10.48529/bwmq-rh91

Producer(s)

Bo Pieter Johannes Andree, Andres Chamorro, Aart Kraay, Phoebe Spencer, Dieter Wang

Collection(s)

Fragility, Conflict and Violence

Metadata

Documentation in PDF DDI/XML JSON

Created on

Nov 02, 2020

Last modified

Apr 26, 2021

Page views

20783

Downloads

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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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