 Hand-in-hand is an evidence-based, country-led and country-owned initiative of the Food and Agriculture Organization of the United Nations to accelerate agricultural transformation and sustainable rural development, to eradicate poverty and end hunger and all forms of malnutrition. Hand-in-hand has brought together FAO experts from across multiple domains, from animal health to trade and markets, resulting in a collaboration of over 20 units. The data has been sourced not only from inside FAO, but also from our partners, as well as public data providers from across the UN, NGOs, private sector and space agencies. So far, we've assembled over a million geospatial layers and thousands of statistics series with 4,000 metadata records. One example of the data sources used is the Water Productivity Open Access Portal WAPR from Aquastat, which uses remote sensing technologies to monitor and report on agricultural water productivity. This includes agricultural systems at risk such as human pressure on land and water, and information on irrigation areas around the world, also made available through FAO's Water Productivity Open Access Portal. Integration of geospatial data from the gridded livestock in the world database, GLW and Empress Eye. This allows you to compare human population density to distribution of cattle from GLW and Rift Valley Fever Disease Events from Empress Eye. Access GLW data to compare the distribution of cattle on the left to chickens on the right. This allows you to easily compare livestock density between two species. Aggregated global production is made available from FAO staff. FAO staff provides free access to food and agriculture data for over 245 countries and territories and covers all FAO regional groups, from 1961 to the most recent year available. Integration with GAZ and MAPSPAN provide disaggregated crop production data, allowing you to view maize production in 2010, using GAZ and MAPSPAN for disaggregated data on your left and FAO stat national data on your right. Access fisheries and aquaculture geospatial information, such as aquatic species distribution, which allow, for example, to predict the extent of fisheries exploiting Caribbean rough shark in red or the Caribbean reef octopus in yellow. The GSOC map is the first global soil organic carbon map ever produced through a consultative and participatory process involving member countries. The Global Soil Partnership then gathered all national maps to produce the final product. Information from National Forest Monitoring Systems has been integrated to visualize distribution of forest resources with other geospatial data such as the road network. This allows separation of undisturbed areas that have high conservation value from accessible areas that are more suitable for restoration or production. Adding geospatial information on further indicators, such as change in forest cover, will support also monitoring of progress towards the SDG-15 life on land. The platform includes integration with data from other organizations, such as the World Wildlife Fund. Here you can view eco-regions. Integration with World Bank data also provides access to many new data sets and information. For example, the Global Roads Inventory Project, which is a harmonized global data set of approximately 60 geospatial data sets on road infrastructure. View changes in infrastructure services from 2008 to 2019. For example, stable lights. The platform also makes available climate data, such as precipitation trend analysis. This is made available from Climate Hazards Group infrared precipitation with station data, 0.05 degree resolution satellite imagery within C2 station data, to create gridded rainfall time series for trend analysis and seasonal drought monitoring. Last but not least, you can view the crop phenology grid data from the Agricultural Stress Index System. This is FAU's Global Agricultural Drought Monitoring and Early Warning System, which simulates the analysis of remote sensing experts and simplifies the interpretation of satellite data for a broader audience. Next steps for hand-in-hand. The initiative aims to bring together the most sophisticated tools available, including advanced geospatial modeling and analytics, to identify the biggest opportunities to raise the incomes and reduce inequities and vulnerabilities of rural populations, who constitute the vast majority of the world's poor. The team is currently working on integrating new data sets and creating country and domain-specific evidence-based case studies to improve targeting and tailoring of policy interventions, innovation, finance and investment, and institutional reform.