WHY A NEXUS APPROACH?

EarthStat serves geographic data sets that help solve the grand challenge of feeding a growing global population while reducing agriculture’s impact on the environment. EarthStat is a collaboration between the Global Landscapes Initiative at the University of Minnesota’s Institute on the Environment and the Land Use and Global Environment lab at the University of British Columbia.

The Food Systems Dashboard gives a complete view of food systems by bringing together data from multiple sources. It's now possible to compare drivers, components, and outcomes of food systems across countries and regions, gain insights into challenges, and identify actions to improve nutrition, health, and environmental outcomes. 

The Spatial Production Allocation Model is an effective way to map detailed patterns of crop production using much less specific input data. A variety of information sources are used to generate plausible, disaggregated estimates of crop distribution, which are useful for understanding production and land use patterns. Identifying where trends take place is important for understanding why they take place. Using a variety of inputs, SPAM uses a cross-entropy approach to make plausible estimates of crop distribution for 42 crops and two production systems within disaggregated units.

GAEZ v4 is the most ambitious global assessment to date and this Data Portal has been developed to make the database widely and easily accessible for users. It comprises a large volume of spatial natural resources indicators and results of agro-ecological crop analysis. Results are presented in a regular raster format of 5 arc-minute (about 9 x 9 km at the equator) grid cells. Selected maps related to AEZ classification, soil suitability, terrain slopes and land cover are provided at 30 arc-second (0.9 x 0.9 km) resolution. The GAEZ v4 update includes 2010 baseline data comprising land cover, a harmonized global soil database and terrain data, protected areas and areas of high biodiversity value. Climatic conditions are based on a time series of historical data of 1961-2010 and a selection of future climate simulations using recent IPCC AR5 Earth System Model (ESM) outputs for four Representative Concentration Pathways (RCPs).

The Gridded Livestock of the World (GLW) is a peer-reviewed spatial dataset on the global distribution and abundance of livestock species. These data find applications in the fields of food and nutrition security; livelihoods and economic growth; human and animal health and welfare; and natural resources and environment. Several versions of GLW database have been released, reflecting the most recently compiled and harmonized subnational livestock distribution data at each time.

The purpose of Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM) is to increase market transparency and improve food security by producing and disseminating relevant, timely, and actionable information on agricultural conditions and outlooks of production at national, regional, and global scales. It achieves this by strengthening the international community’s capacity to utilize coordinated, comprehensive, and sustained Earth observations.

FEWS NET is a leading global provider of timely, accurate, evidence-based, and transparent early warning information and analysis of current and future acute food insecurity. FEWS NET informs decisions on humanitarian planning and responses in 30 of the world’s most food-insecure countries.

A web-based platform that combines remote sensing data and machine learning techniques for informed decision-making in African food production systems.

A web-based tool kit for measuring the progress of the Comprehensive Africa Agriculture Development Programme (CAADP) and the Africa Agenda 2063.

The World Food Programme (WFP) has unveiled a new tool in its bid to end hunger by 2030: HungerMap LIVE monitors food security in more than 90 countries and issues predictions for places where data is limited. Using the latest metrics on conflict, climate shocks, populations and the weather, HungerMap LIVE aims to identify areas that are currently food insecure or are sliding towards food insecurity. The HungerMap LIVE leverages the power of big data and predictive analytics to track and predict food security in near real-time.

INFER, developed by ESCAP and the WFP Regional Bureau for Asia and the Pacific, with contributions from UNEP and FAO, offers insights into multidimensional risks affecting three critical food system outcomes: human health and nutrition, ecosystem health and sustainability, and shared prosperity. It assesses risks across six dimensions of food security. Building on 96 indicators, INFER enables tracking of risk and comparison of risk drivers over time, within and across countries, contributing to the tools available for food systems monitoring and for ensuring that food systems resilience-building strategies are risk-informed.