In this interactive we develop a typology to help design and improve spatial targeting of food and nutrition security (FNS) interventions.
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Remote sensing and machine learning for food crop production data in Africa post-COVID-19
The world is experiencing an unprecedented health crisis during the spread of COVID-19 (SARS-CoV-2, or Severe Acute Respiratory Syndrome Coronavirus 2).
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.
Policy-making processes in developing countries often continue to operate devoid of evidence.
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)
Atlas politique de la sécurité alimentaire et nutritionnelle et de la résilience: Burkina Faso
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)
Monitoring crop phenology using a smartphone based near-surface remote sensing approach
Using crowdsourced near-surface remote sensing imagery to monitor winter wheat phenology and identify damage events in NW India.