The lack of timely, high-resolution data on agricultural production is a major challenge in developing countries where such information can guide the allocation of scarce resources for food security, agricultural investment and other objectives.

This paper combines panel data from nationally representative household-level surveys in Nigeria with long-term satellite-based spatial data on temperature and precipitation using geo-referenced information related to households.

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.

More than one billion people worldwide receive cash or in-kind transfers from social protection programs.

The management of forest commons requires coordination within a community and between communities. This coordination is usually challenging given the incentives for free riding.

Spatially explicit global cropping system data products, which provide critical information on harvested areas, crop yields, other management variables, are imperative to tackle current grand challenges such as global food security and climate cha

Measuring empowerment is both complicated and time consuming. A number of recent efforts have focused on how to better measure this complex multidimensional concept such that it is easy to implement.

Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies’ programming.

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

Data on global agricultural production are usually available as statistics at administrative units, which does not give any diversity and spatial patterns; thus they are less informative for subsequent spatially explicit agricultural and environme

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.

Information on global cropland distribution and agricultural production is critical for the world's agricultural monitoring and food security.

Remotely sensed actual evapotranspiration (AET) may help fine-tune hydrological models in data-scarce regions to improve water-management interventions.