GEO GLAM Initiative: National Monitoring Capacity Building (enhancing National Systems)

1. GEO GLAM Meeting Geneva, January 18-20, 2011 GEO GLAM Initiative: National Monitoring Capacity Building (enhancing National Systems) John S. Latham Senior Land and Water Officer Land and Water Division (NRL) Natural Resources and Environment Department (NR) Food and Agriculture Organization of the United Nations (FAO)

2. Moving forward • Improving the statistics ; enhancing the methodology, building local capacity and providing tech assistance; • Increasing linkage proposed between the WB/FAO - Global Strategy for Agricultural Statistics and GEO GLAM - the latter as the provider of remotely sensed data and related services. This could be complemented by additional inputs based on the work we undertake jointly in FAO on several RS programmes at country level and which are a integral part of the global strategy approach. • Build a partnership and governance structure that is engaging of the national entities either through a multilateral interagency mechanism or a intergovernmental body. • Need for GEOGLAM to move from an interest group to a viable implementation mechanism with realistic goals that focus on adding value and not duplicating existing efforts, focusing on the contribution and use of Remote Sensing data to support agricultural statistics. • The Global strategy is a viable platform for this and has considerable momentum, institutional ownership, national review and engagement with global, regional and national elements with a well defined strategy, implementation plan and a R&D component and outputs.

3. What is the Global Strategy and what are the strategic directions? http://www.fao.org/index.php?id=27156 The Global Strategy is an initiative undertaken at international level under the auspices of UNSC with the purpose of providing a framework for statistical systems that enables them to produce and to apply the basic data and information needed to guide decision making in the 21st century. Broadens Scope of Agricultural Statistics Include aspects of Rural households, forestry, fishery Connect farm holding and household to the natural environment--land Provides Conceptual Framework and is built on three pillars Minimum set of core data Integration of agriculture into national system Sustainability through governance, capacity building

4. Pillars • Produce a minimum set of core data (economic-social-environmental) and determine national priorities • Integrate agriculture into National System • Rebuild statistical capacity • Statistical methodology for sampling, survey design, data analysis • Data dissemination—advocacy • Uses of administrative and other data • Implement new methodology and technology to meet emerging data needs • Master Sample frame, integrated survey • Remote sensing, Global Positioning Systems, etc • Continuous feedback from data users

5. National components • Country Assessment • STAGE 1: desk study using a standard questionnaire • STAGE 2: in-depth assessment thru country visits • Research • Frameworks for Ag statistics • Master frame/integrated surveys • Data collection methods • Food security indicators and methods • Market information indicators and methods • Data analysis • Administrative data mechanisms

6. National components • Training • Improve/develop curricula • Strengthen existing training institutions • Promote self-learning • Strengthen real demand for training • Technical assistance • Strengthen institutions of agricultural statistical system • Mainstream agricultural statistics in NSDS • Design Ag censuses, integrated survey frameworks and integrated databases • Improve / use of agricultural administrative data • Validate and analyze agricultural statistics • Compile / disseminate the minimum core data set • Governance (global, regional and national): • National: Existing institutional coordination mechanisms

7. National Strategy • The implementation of the Global Strategy will be country driven and will take into account other ongoing statistical capacity building and development activities. • Vision: Comprehensive, credible, relevant and timely assessments and analyses • Capacity development • Monitoring and in-country assessment • Standards, methods and tools • Statistics information and analyses

8. Notes • Consider what countries want or agree to • Elements from FAO work and the global strategy, which is more comprehensive • Institutionally owned at national level • International partnership: what is ongoing and how this this interlinked and structured • Approaches and needs at national level and how it will move forward Next • how to move forward and what is needed”: • gap analysis, • current capacities assessment at country level,  • current approaches used (list frame, area frame, multiple frames, • relative accuracy of each,  • capacities to implement new approaches and assimilate RS data to enhance development of new multiple frame approaches • sustainability issue on data flows • accuracy of data (resolution suitable for agricultural statistics to be generated). 

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10. National Monitoring Capacity Building: steps in preparation • Determination/grouping of countries in to food surplus/exporter/importer to de made using data from FAO • Producers/Exporters, including G20 Countries (e.g. Argentina, Ukraine, Thailand, Vietnam, Brazil, Pakistan, etc) • demonstration of capabilities, confidence building in RS results, enhancement of current systems • focus on individual national needs and areas where EO offers significant improvement • Developing Country Capacity Building for Production Monitoring (e.g. Malawi, Ethiopia, Uganda, Myanmar, Laos etc ) • Assist in national system design and implementation (cropland mapping, area planted, ground sampling, crop condition, yield forecasting assessment, reporting) emphasis on building sustainable systems • Training, hardware installation and maintenance, decision support information flows • Status of EO based agricultural monitoring to be made based on analysis of current coverage of country under different ongoing programmes.

11. National Monitoring Capacity Building: steps in preparation • Identification of trainer/trainee communities (countries and institutions) • Tapping of available sources of funding and creation of additional source as a part of GEOGLAM (Financial, in-kind and or intellectual all support to be identified and accepted) • Identification of trainee institution- Institutions which are responsible/mandated in the country for agriculture statistics creation and its supply. • Design of training programme-need based for each country, use of available best practice for the situation • Identification and arrangement for un-interrupted supply of EO data- data specification, source etc. • Identification of HW, SW and other resource needed for carrying out national monitoring programme • Phasing of implementation- In phase-I implement in few countries in each continent followed be expanding to other countries in next phase.

12. National Monitoring Capacity Building: steps in preparation Phase 1 - Selection of countries for demonstration based on existing projects and new funding– additional countries can be added based on national and bi-lateral funding - better coordination needed. For in situ observations - the goal is also to establish one or two sites at the national level for: • developing improved methods, testing and validation to include systematic collection of ground based observations • focus new and experimental EO data acquisition (building on and augmenting JECAM). These sites can be used to demonstrate new capabilities of EO

13. Tab 1: Food surplus and deficit countries

14. Enhancing National Capacity for Agricultural Monitoring • For priority targeted * countries (TBD) and • Up-to-date cropland area mapping • Robust area frame sampling design • Improved rainfall estimation and soil moisture conditions • Improved estimation of area planted • Crop type and condition monitoring?? • Improved yield estimation • The timely and transparent dissemination of monitoring results and statistics • For interested national entities - capacity building by request * e.g. countries with poor reporting system and countries with larger year-to-year fluctuation in cropped area and/or production – feasibility,

15. Improving availability, access to, timeliness and use of EO data for agricultural monitoring • Satellite observations ( working with CEOS and Private Industry) • Examples of coordination activities • Coordinated International Moderate Resolution acquisition strategy • Coordinated International Fine-resolution sampling strategy • Coordinated global network of Geostationary sensing systems • Examples of improved products and services • Global crop type mapping • Timely global information on crop condition • Improved rainfall, soil moisture, reservoir height data • Improved Near Real-Time data access • Improved Inter-use of multi-source data • Standardization of pre-processing and products • Free and open data policies for GEO-GLAM data

16. FAO Global Strategy to improve agricultural and rural statistics • Setting up of a Global Office (GO) at FAO and a Global Strategy Steering Committee. • Regional coordinating offices and regional steering committees will be established as well. • Africa has established both its Regional Steering Committee and Regional Office located at AfDB • In Asia, a Regional Steering Committee has also been established • Additional criteria: • Importance of agriculture. • Level of statistical development.

17. Strategic perspective Data and information • Creating/strengthening a network of primary sources of information • Create country/regional teams with varied expertise • Broaden information base and analysis to include staple crops other than cereals (such as potatoes, cassava, beans etc.) • Identify and/or develop additional indicators (amenable to relatively easier monitoring) that relate to access and vulnerable population • Strengthen partnership with private sector At country level • Build local capacity : • advocacy for investment in food security monitoring work • technology transfer (such as remote sensing) and training of local experts and strengthening relevant institutions • Assist the development of user friendly monitoring tools

18. Techniques and Tools for National Monitoring • More than 20 years of time-series statistics together with background information • Data on food production, trade, food aid, stocks, consumption • Continuously updated and is constantly analysed

19. Remote Sensing Satellite data are mainly used for the following purposes: • Monitor the state of vegetation in cultivated and rangeland areas • Normalized Difference Vegetation Index (NDVI) from the European Satellite SPOT, 1km resolution • Monitor the rainy season and identify areas which are likely to have suffered from or might be affected by, drought or excessive rainfall. • Interpolated Estimated Rainfall IER or RFE from FAO/ARTEMIS from CPC of NOAA, 4.5-5 km resolution • RFE in comparison with last season and long term average • Estimate/Forecast yields of major crops • Estimate the extent of cultivated land: • Sat images at different time, reference period, planting dates • other info

20. Agricultural Area Estimation • Development of current procedures, list frames and multiple frames; • Consistent and harmonized approach, using standards and protocols, built with optimum methods; • Utilization of consistent global high resolution data on timely basis coincident with system requires • A set of recommendation needed on yield and area estimated; • Review of Institutional framework and methodological approach (list area, multiple frames); • Assessment of accuracy (precision and bias) of current approaches and results, cost effectiveness, timelines; • Definition of the interventions needed, based on the above • Implementation and strategy, capacity building, data flows, statistical approach, validation

21. Crop Assessment reports • Bulletins (monthly) issued by SUPARCO and FAO in collaboration

22. National land cover mapping • FAO is implementing and/or assisting with technical advices, methodologies and tools, several mapping activities for the production of standardized and harmonized land cover baseline. • The updated databases can be a valid support for many environmental applications but also for: • National agricultural analysis • Strengthening National Capacity for handling and processing data (e.g. Remote sensing data) • Strengthening National Capacity for agricultural monitoring • Monitoring countries and region risks • Ethiopia • Afghanistan • Pakistan • Sudan • Lebanon • Fouta Djalon - Western Africa countries • Malawi

23. Stratification • Stratification of a project area is one of the most effective ways of increasing the efficiency of a sample-based estimate of crop area. Stratification is also one of the most effective ways of utilizing remote sensing data. • Provides a revision of the project area in a more efficient way. • Project areas are frequently defined by political boundaries or other geographic reference points that do not correspond with the location of the agricultural area. • The agricultural area can generally be delimited quite accurately in remote sensing data. • Result: fewer sampling units would be required to estimate crop area with a given level of precision using a refined, smaller and more homogeneous stratum of agricultural land. • The effectiveness of this type of agricultural stratification has been shown in previous efforts to monitor illicit crop area in both Afghanistan and in Lebanon - Lebanon, for example, the project area was reduced by 21% by simply defining the agricultural area within the political boundaries which were initially selected as the project area. • In Afghanistan, the reduction in project area (and sampling variance) was even greater.

24. Cost-effectiveness The most expensive system is not always the most cost-effective; however, if two systems provide the same data, then the one that is least expensive is most cost-effective. Cost Efficiency / Evaluation Whether the previously-discussed “optimal” system is the most cost-effective system is not clear, since operational costs and cost/benefit are difficult to quantify with the present state of knowledge. Among the factors expected to affect costs and benefits are: • the degree to which stratification using remote sensing and/or ancillary data can reduce the area of interest; • the degree to which stratified variance is less than unstratified variance; • the cost of acquiring and processing remote sensing data, which is affected by the type of data and number of acquisitions; • the cost of acquiring field data; • the correlation between remote sensing estimates and field estimates.

25. Sustainability Can the system be maintained by local staff? Implications for human and financial inputs. set-up costs recurrent (operational) costs Ability to detect change The idea of permanent plots is a concept that seems to make sense for this criterion. If you measure something at one period and then come back and follow the same procedures and measure the exact same thing, and there is a difference, then you say we measured change and I add that you can detect small amounts of change.

26. Main Challenges encountered Lack of sustained and adequate support (overstretched officers, lack of resources to maintain contact in countries) Information Dissemination • Availability and type of Information is not homogeneous for all countries • Varied statistical sources within a country • Lack of information in some countries • Ensuring information quality and reliability • Instability of sources • Difficult liaison with national/local counterparts • Inadequate feed-back mechanism • Need for continuously evolving and dynamic reporting mechanism and adjusting to evolving client/customer requirements • Balance between the need for concise briefs for decision makers and more elaborate reports • Broader accessibility of available information to local levels

27. Technical Challenges: Capacity development – team building – Time Project Management – emulation Making timely estimates given complexity of approach - Phasing Crop identification not yet experimented with in Sudan – Phasing/startup? Robustness of Algorithms with Regional Application Methodology for yield estimation Information Fusion and Information Mining Attention to Standardization – LCCS Extraction of Meaningful Information to Support Actions – Info. access and Distribution/Outreach Development of User-Acceptable System Interfaces for data dissemiantion Evaluation Process / Cost of the New Technologies Institutional Challenges: New Partnerships and Collaboration - Nat Re-engineering/accommodating new approaches New Services Based Upon IT New Business Models to Justify Investment in parallel/complementary approaches – Prov commitment/govt lead Value of the New Technologies – to Institutional partners – conviction What are Some of the Challenges?

28. Knowing our users (local to global) Participatory, consultative and inclusive process to encourage cross-sectoral communication, and be based on inter-disciplinary management approaches Learn from “best practice” procedures, and facilitates the possibility of procedural convergence – partnership approach nat and international. Country-driven capacity development efforts, with regard to both tools and information management Parnership-oriented Key success factors

29. Governance issues Spatial data infrastructures Application of standards Harmonization - adjustment of differences and inconsistencies among different measurements, methods, procedures, schedules, specifications, or systems to make them uniform or mutually compatible Consistency – degree of firmness or agreement Data access policy Quality indicators Networks Combination of remote sensing with in-situ data validation Sustainable development Utilization of information products Awareness raising Community of practice Key lessons

30. Thank you for your attention! John Latham FAO 48