Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Session 3: Processes modeling Crop Monitoring for Food security: Contribution of Remote sensing & future challenges Olivier LEO, Felix REMBOLD, Michel MASSART, Oscar ROJAS Agriculture and Fisheries Unit, IPSC Potentialities and limitations in the use of remote-sensing for detecting & monitoring environmental change in the Horn of Africa Expert workshop, Nairobi, June 2007

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Outline 1. General background 2.Crop monitoring systems Place of remote sensing On going and future developments 3 Conclusions Links with sustainable development

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 MARS = Monitoring Agriculture with Remote sensing MARS STAT started 20 years ago – Support to EU Common Agricultural Policy (DG AGRICULTURE) – Focus on EU Member States and 7-10 crops of interest – Various actions covering areas estimates, agromet models, area frame surveys, crop monitoring, rapid estimates, etc… MARS FOOD started in 2000 – To address Food Security in support to DG DEV, AIDCO, RELEX, ECHO… – The EC is a main international donor FS budget-line 500 Mio €/ year since 1996 (cf. Reg. EC N° 1292/96). Reinforced by Food Security Thematic Program (COM 2006/21). – Adapt MARS STAT crop monitoring system, in collaboration with FAO – DG AIDCO involve MARS-Food as technical advisor Participation in CFSAM and ENA missions by UN institutions FAO / WFP… General Background

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 A rather mature application, facing new Global challenges Medium term ( ) Increase of prices and volatility of Food products – Bio fuel policies – Climate change or frequency of extreme events – Development of emerging countries (China, India) Longer term (2050) (cf FAO World Agriculture towards ) – Population increase 8,9 Bio in 2050 (+ 45%/ 2000) – increased Food global demand to achieve 1st MDG – New pressure on land use – Effects of climate change... Strategic importance – of monitoring both crop areas and yields – In vulnerable zones and for the main producers General Background

Crop Monitoring – SWALIM Workshop - Nairobi June / Mars STAT Mars FOOD During the 7th FWP ( ), MARS intent to enlage its AOI To EU neighbouring countries and Black sea Region + emerging countries ( MARS STAT) To whole Sub saharan AFRICA + Central America (MARS FOOD) Shared global data sets and capacities MARS regions of interest 7 th FWP Mars STAT Mars FOOD ? MARS FOOD Horn of Africa - 6 countries 8 regional monthly bulletins 4 x (36) national 10 day bulletins 2- South & East Mediterranean countries 11 countries – 6 Bi monthly bulletins 3 - Russia & central Asia 15 countries, 6 bi-monthly bulletins 4 - South America MERCOSUR + Bolivia 5 countries, 11 2 wks /Monthly Bulletins

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Agricultural statistics Production (Crop, Region) = Total area (C, R) x mean Yield (C, R) Crop monitoring – Near real-time activity along the campaign – to regularly provide information Qualitative (status of the crop, planting dates, etc) Then quantitative (crop yield forecasts) – for appropriate, timely, decision taking Actions on the market and stocks Request of Food Aid (Early Warning Systems)... Crop monitoring answer only to 1 / 3 component of Food Security FS focus on total production or Yield – Areas are considered as rather constant – Crop Monitoring use total area planted – Mean yields forecasted by agro-meteo. models integrate areas with null-yield (due to drought or adverse climatic conditions) Crop monitoring Crop Production & Food Supply Market & macro economic context Vulnerability & Food Needs

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Types of RS information used in Crop monitoring Crop monitoring

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 ECMWF global daily + reference data (ERA 40) + Ground stations Crop monitoring and Analysis SPOT Vegetation daily data + Archive Rainfall estimates (MSG) Real time acquisition and Pre-processing Remote sensing METEO Crop models Statistics Expertise Overall Processing chain Regional / national Crop Bulletins & forecasts Global 10 days products and indicators

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 MARS-FOOD Bulletins Quantitative Yield estimate end of campaign Maize Yield Estimate (t/ha) Regular Quantitative crop monitoring

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Contribution of Remote sensing 3 main levels of Crop monitoring systems – Level 1: data (pre) processing – Level 2: Crop development modelling – Level 3: Statistical analysis (Regression, etc) and/ or interpretation by experts Present contribution of RS in the whole process – 30 % of the whole tasks – < 20 % of the operational costs – Much higher but variable weight on the final outputs (use by Analyst use of the various sources)

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 MAY 2007APRIL 2007 Rainfall anomalies in Somalia Monthly rainfall anomaly (difference with 1974 – 2003 normal ), based on ECMWF data

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Current situation in Somalia Crop cycle progress index ( percentage) for the main Sorghum regions at the end of May 2007 Sorghum Water Satisfaction Index up to the end of May 2007

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 CNDVI profiles Crop development profile clearly above average in Bay and Bakool, close to average in the Shabelle regions

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Future Developments Main identified or on going developments Use of MSG rainfall estimates Ensemble approaches Updated and improved crop masks Ingestion of EO at level 2 – Readjust calendar / crop Phenology – LAI, fAPAR, DMP… Direct use of EO indicators at level 3 Standardisation of VPI,VCI, etc

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Zooming for the 2 main Localities inside the state (Sennar and Singa) Spatial Level of CNDVI analysis EX in Sudan: SENNAR state Sorghum mean CNDVI : below average performance detected in 2006 In fact, 2006 season was very good for the mechanized South of the state (Singa locality); below average for the traditional agriculture in the North of the State (Sennar locality)

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Case of rangeland monitoring RS more used than Agromet models Specific requirements – Information on complex land covers (perennial+grassland) & landforms – Calibration between RS indicators and usable biomass, feeding value Models integrating Livestock information – Cf. PHYGROW (TAMU) Extra informations of interest – Water points, Small water bodies – Migration roads More rapid / regular information with direct involvement & Feed back to Pastoralists – “ Feed” security – Management of the ressource – Conflict prevention... Courtesy of Robert KAITHO Courtesy of Job ANDIGUE

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 More a complete system than a model – Number of optimization / compromises between the different info. – Near real time processes, regular back up/ consolidations – Development & tests in parallel, before implementation with reprocessing of the whole archive… Some SWOT considerations – Strengths: RS provides an unique, very valuable, wall-to-wall info. – Good consensus on state of the art approaches – Access, processing and storage capacities not limiting factors (LR,MR) – Weaknesses: Noise in complex landscapes/ saturation & clouds in equatorial areas, still short time series – Opportunities: AMESD Program and VGT4 Africa Portfolio – Threats: “in situ” information (crop phenology, biomass measurements, etc) becomes rare and crucial Continuity of VGT program: Intercalibration or use of standard non sensor specific indicators In summary …

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Sustainable development From yearly crop-monitoring to medium-longer term analysis and inputs in the “LBRRD” ? – Trend analysis, – identification of Hot Spots, – Prevention, mitigation and coping strategies… Agricultural / Rural Development Policies requires reliable estimates on the 2 components of production – Cropped areas  Margins of extension // Pressure on environment / land… – Mean yields  margins of progress Agricultural statistics are crucial for Policy making – Land-cover maps do not provide accurate/ unbiased areas estimates – RS can support AFS with Ground survey and VHR (satellite or aerial) imagery “LBRRD” Crisis Post-Crisis Relief Rehabilitation Development EmergencyLong term Prevention

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Thanks you for your attention ! To know more PPT of the recent CRAM workshop (Nairobi, March 07) Web sites of AGRIFISH, MARS Bulletins and products

Crop Monitoring – SWALIM Workshop - Nairobi June / 19 Evapo transpiration Some of the global products Dry Matter productivity Water Satisfaction index Maize Near real time, 10 day