1. Sentinel 2 Preparatory Symposium 23-27 April 2012, ESA- ESRIN, Frascati, Italia User Consultation AGRICULTURE Sentinel 2 in the framework of MARS Activities

2. Forewords Following official presentation made by MARS (AGRICULTURE S.1) But dropping, to avoid repetition, general information and illustrations –on MARS or on GEOGLAM initiative Focus is kept on 2 main operational programs 1 - Controls With Remote Sensing 2 - MARS crop monitoring and yield forecasting Crop monitoring activities in Africa are not developed here, as addressed by other speakers and present first developments on possible use of S2, and contribute to the Seed Questions of ESA… This includes personal thinking, vision or questions to feed the debate NB: The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission 8 September 20152

3. 1 - Controls with Remote Sensing (CwRS) Verification at parcel + farm level of the claims for CAP subsidies (> 55 Bio Euros in 2011) –Eligibility of land use and cross-compliance with Good Agricultural and Environmental conditions (GAECS) Using both Very High Resolution (<= 1 m) and several High resolution images (5-30 m) A number of options within a EU common framework of standards and technical tolerances managed by JRC CWRS are part on objective On-the-Spots Checks + used to assess the quality of the Digital Reference parcels (LPIS) in 2011: 340 000 Farmers / 430 control zones (Geo. Clusters) 8 September 20153

4. 9 millions Farmers in 27 EU Member states Using 140 Mio reference parcels uniquely identified Reference parcels superimposed on ortho imagery CwRS & Digital Land Parcel System today Min. 5% On the Spot Checks including with EO

5. 2011 Campaign : Control sites and imagery 8 September 20155 Image provision for CwRS today

6. Description20032004200520062007200820092010*2011* HR imagery Planned HR sites 124149183192227244249278286 Total no. images acquired 680690 693657538655671735 VHR imagery Planned VHR sites 3771161181228264285368426 Area (1000km 2 ) acquired 1250126127150160174.7224242 MS participating (HR and/or VHR) 1222242324 2527 Total purchased (Mio Euros) 1,93,35,05,35,65,46,06,77,05 * Including LPIS QA zones X 2,3 X11 X 20 X3,7 Evolution of image acquisitions for the CwRS 6 Image provision for CwRS today

7. CAP reform after 2013 ? Horizontal Regulations “CAP Towards 2020” foresees continuation of CwRS as part of on the Spot Checks (as IACS and LPIS maintenance) EUROPEAN COURT OF AUDITORS (Press Release- 10 Nov. 11) “ For Agriculture and natural resources the estimated error rate was 2.3%. The direct payments covered by IACS, which accounted for almost €40 billion of total spending of €56.8 billion in this area, were found to be free from material error “ 8 September 20157 CwRS Future evolutions 2014 -2020

8. New controls requirements linked to the 3 compulsorily “Greening Payments” –Crop diversification –Permanent Grassland –Ecological focus areas … → Clear increase of HR + multi-date But also –Trend of smaller control sites, Some MS using 2 x VHR –No increase of budget …. Expected decrease of VHR Costs due to competitive market Possibility of increase of HR - Advantage of RedEdge also identifed on World View 2 (G. Peroni, 2010) Warning : Possible CONFLICT with present MARKET 8 September 20158 Riparian forest buffer Filter strip Windbreak hedge Protected isolated trees Protected permanent pasture Area of high natural value CwRS Future evolutions 2014 -2020

9. 3 more promising applications to be developed 1 - Wall to wall Control or pre-control ? (Risk analysis) –Taking benefit of large swath of S2 –More as a tool for risk analysis - targeting control sites Feasible but not in the present “air du temps” (simplification policy) 8 September 20159 Key Contribution of Sentinel 2 Large Swath for wall to wall inventory Multidate to characterise semi natural features ( montlhy?) or capture key management practices ? May allow real rotation control (VS Diversification) - regulatory issues and possible confusion Technical Challenges: none if simple automatic classif/ LPIS vector data volumes and more complex process treatment (buffer, object) Initiative by MS ? More exploratory or focused on spec case? CwRS Future evolutions 2014 -2020

10. 3 more promising applications to be developed 2 - Impact assessment of the CAP and of its greening –Combining both IACS, statistics, EO wall to wall coverage – Addressing both first and second CAP Pillar Technical Challenges: indicators ? Appropriate regional scale? Objective methodologies ? Mapping baseline ( i.e 2013) ! 8 September 201510 Key Contribution of Sentinel 2 Multidate to characterise semi natural features ( monthly?) or capture management practices ? Large Swath for wall to wall for inventory Possible training / validation by IACS Geospatial and CWRS VHR Sample Road Map : Pilot and demonstration in some MS CwRS Future evolutions 2014 -2020

11. 3 more promising applications to be developed 3 - Mapping – monitoring products in support to FAS (Farm Advisory Systems) ? –Contextual info and understanding of rural landscape dynamique –Appropriate recommendations on farm land management –New measures related to 2 nd pillar CC, 8 September 201511 Key Contribution of Sentinel 2 IDEM Multidate to characterise semi natural features ( montlhy?) or capture management practices ? Large Swath for wall to wall for inventory Possible training / validation by IACS Geospatial and CWRS VHR Sample Road Map : Pilot and demonstration in some MS CwRS Future evolutions 2014 -2020

12. Developed since 25 years based on EO + Agromet crop development models Covering both AREA and YIELD components, with schematically –AREA Estimates = (Very) High Resolution + ground survey AFS –YIELD = Low Resolution 10 d + Crop Models wall to wall + GRID Semi- deterministics models + convergence of evidence analysis for Yield + deviation from normal conditions In the European Context (respective contribution to inter-annual variability, other sources of information available, STATS, CAP) –Focus on Yield with Models using Agromet and EO indicators –Area estimate by Trend function or provided by Eurostat. –Little developments on area estimates since 15 Years MARS Crop Monitoring & yield Forecasting 8 September 201512

13. Area Estimates: MARS Regional inventories (1988-1996) Adapting to the EU the USDA method AFS with square segments were cheaper to implement than segments with physical boundaries, for similar quality of estimates Images used for Stratification + Regression estimator i.e classified images (1-2 Dates) as ancillary variable Relative efficiency lower than in the US (more complex landscape). Cost-efficiency with Landsat TM slightly below threshold in the 90’s Expected S2 improvements: Large Swath multi-date ! Ground data + images Estimates MARS Crop Monitoring & yield Forecasting

14. Rapid estimates of crop area change (1992-97) (“Activity B”) Pure remote sensing approach –Sample of 60 sites of 40x40 km –4 images per site every year (mainly SPOT) –Some ground data of the previous years (to train CAPI and/or image classification) Good results for dominant crops: –Ex. <1.5 % error for total EU cereals area, despite rather poor sampling But the margin for subjectivity was around ± 20% Much “weaker” results when the changes were difficult to forecast MARS Crop Monitoring & yield Forecasting

15. Limited role of Remote sensing. Stratification Graphics for ground survey Points that cannot be reached 2001-2003 2006 LUCAS (Land Use / Cover AFS Survey) Main tool for land cover area estimation in the EU. (Eurostat) Ground survey of a sample of points Relative efficiency MARS Crop Monitoring & yield Forecasting

16. Ongoing 2012 Modelling new crops Rye and Triticale Monthly Bulletin Calendar as inputs to AMIS – G20 2013-14 Development of Quantitative Pasture monitoring Possible feasibility study in 2012/13 to implement of methods for quantitative pasture analysis… Need of mapping info describing appropriate typology and management of EU pasture 2020: Towards Global Monitoring capacities ??? GLOBCAST Feasibility study (2010-2011) MARS Crop Monitoring Future requirements

17. General objectives of GLOBCAST Monitor the impact of weather in main grain producing areas Produce short-term forecasts 4 Zones of the world 1.Russia, Black Sea and CIS (wheat, barley, maize) 2. Asia (China, India) & Australia (wheat, rice) 3. South America (wheat, soybean, sugarcane, maize) 4. North America (wheat, barley, soybean, maize, rapeseed) MARS Crop Monitoring Future requirements

18. The EC, Member of the G20, signed the G20 Action plan on Agriculture price volatility DG AGRI strongly supports the 2 Initiatives on market transparency EU timely reporting for AMIS and Improve information on stocks AGRI front line Contribute to GEO –GLAM, by sharing MARS data and model outputs with other stakeholders, in particular FAO GIEWS JRC H04 Position included in the EC Report to EU Council and Parliament (August 2011) GEOGLAM has a strong interest to complete the overall action plan by Capacity Building in countries at risks Uncertainties and challenges linked to budgeting and governance G 20 initiatives GEO-GLAM and AMIS

19. Main outcomes of GLOBCAST Feasibility Definition of various system configurations in term component and level (basic to intermediate) and possible road maps Overall funding and deployment strategies under discussion with DG AGRI (2014-2020) Increase role of EO Low resolution data // ground meteo stations Mainly a analysis / decision support system for yield –Main running costs are related to staff –key requirement of experienced analysts Area Estimates becomes a major component 8 September 201519 MARS Crop Monitoring Future requirements

20. Best approach: USDA NASS Cropland Data Layer (CDL) “Census by Satellite” Operational Annually Program - cover US major crops and regions  Provide timely, accurate, useful estimates  Measurable error, Unbiased/independent estimator  State, District, County  Deliver in-season remote sensing acreage estimates  For June, August, September, and October  Official USDA Reports  use of bi-monthly DMC Deimos-1 & UK2 & Landsat 5 & 7 ( see PECORA presentation)  Wide public data dissemination The ideal example, but CDL relies on heavy NASS AF ground surveys 8 September 201520 Potential S2 Development on Area estimates ? Courtesy from Larry Beard

21. DMC Deimos-1 & UK2 & Landsat 5 & 7 2006 NLCD & Derivative products But USDA NASS CDL relies on heavy ground surveys NASS June Agricultural Survey Farm Service Agency: Common Land Unit Unit Slides courtesy from Larry Beard Potential S2 Development on Area estimates

22. Since 3 years, MARS involved in Pilots studies in Ukraine, Spain, Italy, China (with VITO – Geoland2) MALAWI (with GMFS) or MOROCCO –Multi-date hard and soft classification, un-mixing, neural network… – Common evaluation and user utility assessment ongoing Need of a comprehensive EU R&D work program –In Europe: How to use existing point survey (LUCAS,IACS admin data ?) Demonstrate the added value of mapping products and small area estimate –Outside Europe: Light point survey ? Substitution of ground data by VHR data sample? Use of Wiki and Google? Different combination of Satellite and spatial resolution… 8 September 201522 Potential S2 Development on Area estimates

23. Possible image requirements –S2 Resolution OK –S2 Swath = Key Improvement compared to Landsat /SPOT See for DEIMOS USDA NASS ( Pecora ppt) in EU Larger than 300 km raise other issue (climatic gradient) –Likely Improvement by RedEdge for crop discrimination – Level 1 C TBC? Radiometry and geometry a priori less critical –Mutidate ? Basically montly or bi monthly target along cropping campaign … ie circa 10 dates –A Priori Wall to wall coverage of Agricultural Zones ?? But possible sampling if seed for Low Mid- Resolution un-mixing ??? –According to context and dynamic Yearly to 5 Yearly In case of 5 Yearly – Possible light method yearly 8 September 201523 Potential S2 Development on Area estimates

24. Key issues are 1.Overall design and optimisation of “ground data” Field survey design (segments, points) Possible substitution with CAPI- VHR 2.Statistical estimators area (regression or Calibration estimators) Difference indicators in multi annual 3.Cloud cover (not critical) but to be assess // Optimisation of management of single image // compositing products) 4.user assessment for pluri-annual strategy 5.Overall coherency and coordination with UN “GLOBAL STRATEGY to IMPROVE AGRICULTURE and RURAL STATISTICS” ! 8 September 201524 Potential S2 Development on Area estimates

25. Huge potential / expectations from relevant Bio Parameters for crop specific, time profile (5- 10 Days) –Clarify revisit cycle, angle and radiometric issues, Need of Level 2 top of atmosphere, produced with state of the art and agreed by Research + users But DATA VOLUME – COMPUTING TIME for data assimilation / running crop models ! Min x 250 000 factor to pass from present 10 -25 km Grids to 10 - 20 m !! What are the best trade off ? Medium term Feeding present agro met grid models with local crop specific parameters ? Designing ASAP an EU panel site sample? A Global one, links with JECAM ? (Very) Long Term ??? Change of crop monitoring paradigm? +/- complete restructuring: Area and yield components observed on a coherent (same) sample ???? Consolidation of R&D results, need of a minimum archive, lots of S.W.O.T analysis and engineering ….. 8 September 201525 Potential S2 Development on Yield modelling

26. 8 September 201526 Huge technical capacities and potential development for crop monitoring Absolute need of operational ground segment and (pre+ post) processing facilities with Free data policy Historical opportunities to build an EU - US coordination and effective inter-operability S2 – LDCM, and ensure an EU contribution to Global Crop monitoring Capacities, in particular for Africa. AREA Estimates and mapping are the most immediate applications Strong potential to feed present AGROMET GRID MODELS with S2 State variable ( design of sites sample ? ) S2 may open the way to radical change in overall system design in long term … Need to foster present research and further develop vision to prepare possible 3rd generation crop monitoring systems (post 2020 – 30) Summary conclusions

27. Thanks for your attention ! Olivier LEO JRC H04 Unit with inputs from Bettina BARRUTH, Philippe LOUDJANI, Javier GALLEGO, Hervé KERDILES, Paer AASTRAND 8 September 201527 20 years of in support to the implementation and monitoring of Common Agricultural Policy