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.

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

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

This dataset consists of half-degree resolution simulated land use/land cover projections (in hectares) for the entire globe for the years 2005 and 2050.

تعرض هذه المذكرة المتعلقة بالسياسات مثالين عن كيفية استخدام بيانات الاستشعار

This policy note showcases two examples on how remote sensing data can be used for monitoring agricultural production and economic activities.

The world is experiencing an unprecedented health crisis during the spread of COVID-19 (SARS-CoV-2, or Severe Acute Respiratory Syndrome Coronavirus 2).

Ethiopia has made efforts to tackle the challenges of low crop and livestock productivity and degradation of land resources through various rural development strategies.

Based on experiments to bring about comprehensive crop insurance coverage over the last 50 years, the Indian government introduced a new crop insurance program, called Pradhan Mantri Fasal Bima Yojana (PMFBY), in April 2016.

Advancing Research on Nutrition and Agriculture (AReNA) is a 6-year, multi-country project in South Asia and sub-Saharan Africa funded by the Bill and Melinda Gates Foundation, being implemented from 2015 through 2020.

Policy-making processes in developing countries often continue to operate devoid of evidence.

HarvestChoice began in 2006, when detailed and readily accessible data on agriculture, human welfare, and the environment were scarce for Africa South of the Sahara (SSA).

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.

The food system community sees a huge potential for big data in agriculture to lift farmers out of poverty (Patel, 2013), and ensure that parents can feed their children nutritious, diverse foods (Lung’aho, 2018).