1. Use of Remote Sensing Data to Improve FAO Statistics Overview Global Food Security Support Analysis Data @ 30m (GFSAD30) 14-16 July 2015 Madison, WI Fabio Grita FENIX/CountrySTAT Team Leader FAO Statistics Division Michela Marinelli GIS & Remote Sensing Consultant FAO Statistics Division

2. FAO Mandate Strategic Objectives SO1: Eradicate hunger, food insecurity and malnutrition (food insecurity monitoring and alleviation) SO2: Increase and improve provision of goods and services from agriculture, forestry and fisheries (investment & development) SO3: Reduce rural poverty (poverty reduction) SO4: Enable more inclusive and efficient agricultural and food systems at local, national and international levels (capacity building and partnership) SO5: Increase the resilience of livelihoods to threats and crises (disaster risk reduction & emergency response)

3. The Role of Statistics Need for: high quality statistical information to advocate policies/investment and promote development establishing monitoring systems to be able to draw from experience in policy implementation defining and implementing internationally accepted standards and sound methodologies Statistics @ FAO: Responds to the requests of its Member Countries to strengthen national/regional information systems in order to increase data availability Promotes internationally accepted standards, methods and tools to support the collection, analysis and dissemination of agricultural and food security data Provides timely, reliable and internationally comparable statistical information relevant for decision-making

4. The Relevance of RS Agricultural production follows strong seasonal patterns and the production is affected by the physical landscape (e.g., soil type) and climatic parameters All variables are highly variable in space and time and productivity may change within short time periods, due to unfavourable growing conditions Availability of timely information is a major factor for efficiently monitor agriculture Financial and human resources for carry out censuses and surveys are limited and there is a need for investing on innovative methods to lower costs, increase data quality and increase timeliness in delivery information and analyses.

5. What is FENIX Web-based and scalable data and knowledge sharing platform to facilitate management and analysis of environmental and socio-economic information It aims at establishing an integrated network of national and international agencies for sharing knowledge and data, primarily on food security, nutrition and agriculture

6. FENIX Basics Based on Open Source software; no licensing constraints and full redistribution rights Service-Oriented Architecture (SOA) Extensible: ability to plug-in new functionalities and applications (widgets) Facilities to share and link data through web services (APIs) Ability to handle databases, geospatial data (as remote sensing, GIS layers, etc.) and text Diversified data collection/upload methods (online data entry; uploads from csv/xls files; mobile apps) Advanced analytical capacities with the embedded “R” statistical package

7. FENIX and Nearly Real-Time Data Daily Prices and Price Volatility Price indices (FAO and IGC) Daily future prices for wheat, maize, rice and soybeans Daily excessive food price volatility index Stocks and Utilization for the 4 commodities Global stocks (yearly) Stock-to-use ratio (yearly) Stock-to-disappearance ratio Satellite image statistics Vegetation conditions and trends Soil moisture conditions Drought indices Real-time data collection and analyses (under test) Food market prices Animal health Planting/harvest season

8. FAO–USGS Envisaged Programme Objective 1: Improve seasonal estimates of crop density areas using validated MODIS- and Landsat-derived products Objective 2: Develop a system to efficiently disseminate the products and the underlying data to the FAO Member Countries

9. FAO–USGS Envisaged Programme FAO Activities: Select pilot areas (Tanzania, Cameroon) Mobilize government staff and UN Volunteers to ground-truth remote sensing products using mobile apps Develop dissemination system to deliver remote sensing products to national partners

10. FAO–USGS Envisaged Programme USGS Activities: Produce the crop density data Develop and provide the mobile app for collecting field data Refine the model on the basis of the data collected from the mobile apps Make available the model and the data to FAO for internal and external use

11. Thank you