In this interactive we develop a typology to help design and improve spatial targeting of food and nutrition security (FNS) interventions.

The U.S. Department of Agriculture (USDA) publishes monthly Ending Stocks projections, providing an estimate of the end-of-marketing-year inventory of a particular commodity, which effectively summarizes its supply and demand outlook.

We combine nationally representative data from Nigeria with spatiotemporal data from remote sensing and other sources to study how young migrants respond to observable characteristics of potential destinations, both in absolute terms and relative

Since Amartya Sen's famous work on Poverty and Famines, economists have understood that the impacts of food market shocks on the poor depend much more on their impacts on households’ incomes and access to food than on overall food availability, an

Extreme weather causes substantial damage to livelihoods of smallholder farmers globally and are projected to become more frequent in the coming decades as a result of climate change.

Extreme weather events cause considerable damage to the livelihoods of smallholder farmers globally.

This paper applies a recurrent neural network (RNN) method to forecast cotton and oil prices. We show how these new tools from machine learning, particularly Long-Short Term Memory (LSTM) models, complement traditional methods.

This paper discusses the feasibility of applying a near-surface remote sensing approach in the index insurance component of the R4 Rural Resilience Initiative in Ethiopia.

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable.

This report is the final outcome of various knowledge products and training material, usually labelled as “printed eAtlas”, which have been developed and shared with Civil Society Organizations (CSOs) under the Voice for Change Partnership (V4CP)

This report is the final outcome of various knowledge products and training material, usually labelled as “printed eAtlas”, which have been developed and shared with Civil Society Organizations (CSOs) under the Voice for Change Partnership (V4CP)

This report is the final outcome of various knowledge products and training material, usually labelled as “printed eAtlas”, which have been developed and shared with Civil Society Organizations (CSOs) under the Voice for Change Partnership (V4CP)

Ce rapport a été élaboré à partir de divers produits de connaissance et matériels de formation regroupés sous l’appellation « eAtlasimprimé », qui ont été développés et partagés avec les organisations de la société civile (OSC) dans le cadre du pr

This report is the final outcome of various knowledge products and training material, usually labelled as “printed eAtlas”, which have been developed and shared with Civil Society Organizations (CSOs) under the Voice for Change Partnership (V4CP)

Since Amartya Sen’s famous work on Poverty and Famines, economists have understood that policy responses to food market shocks should be guided by changes in households’ incomes and access to food, rather than by overall food availability.

This paper examines two new methods to generate gridded agricultural Gross Domestic Product (GDP) and compares the results with a traditional method.

Spatial interactions are essential drivers of price transmission mechanisms and may significantly affect any food’s policy outcomes. However, spatial aspects seem to be generally overlooked when analysing price transmission.