GEOGLAM. JECAM Collaborative Priorities : Pierre Defourny (UCLouvain) and Andrew Davidson (AAFC) Co-leads of JECAM

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1 G20 Global Agriculture Monitoring Initiative GEOGLAM JECAM Collaborative Priorities : Pierre Defourny (UCLouvain) and Andrew Davidson (AAFC) Co-leads of JECAM

2 Origins The GEO Agricultural Community of Practice established JECAM in 2009 to enhance international R&D collaboration around agricultural monitoring towards a better use satellite Earth Observation. JECAM achieves this by: Beijing, 2009 Network of voluntary research sites distributed across the world Share standards, time series from EO satellites and in-situ data Supporting methods inter-comparison of mapping, monitoring and modeling

3 Network Global network of over 30 voluntary JECAM sites long-term network of widely distributed sites collecting each year different EO time series and corresponding in situ data on a voluntary basis to embrace the global diversity of croppings systems

4 Principals Develop common standards in definition, reporting methods and field protocols. Collect and share time-series datasets from a variety of Earth observing satellites and in-situ crop and meteorological measurements The Committee on Earth Observing Satellites (CEOS) and member agencies support with the acquisition and timely provision of data. Catalyze R&D activities across JECAM sites to establish a common understanding of the scientific state of the art Support the scaling up and the transition from research to operational monitoring system as key R&D component of GEOGLAM 4

5 guidelines and reference documents JECAM guidelines building on best practices of the community and collectively endorsed: - Field data collection and sampling strategy - Validation protocol - Definition of annual cropland, typology for crop types and associated management - In situ measurements for biophysical variables

6 guidelines and reference documents ISO Land Cover Meta Language

7 guidelines and reference documents 7

8 site requirements Minimum Data Sets (MDS) for both satellite and in-situ data : JECAM recommends to follow at least the JECAM guidelines or better Three types of in-situ data are expected to be annually collected during the main growing season Crop mask (cropland and non-cropland) Crop type (main and possibly minor); Crop biophysical variables (e.g.biomass, LAI, fcover, or/and yield) Min satellite data requires a combination of optical, and Synthetic Aperture Radar (SAR) time series 8

9 site requirements Site configuration with the implementation of the minimum dataset concept it is necessary to impose a predefined site configuration In order to encompass the diversity of regional crop types and crop development, a typical JECAM site will cover an area of 25 x 25 km (625 sq. km) and be representative of one or several cropping systems with a spatially nested core zone of 10 x 10 km (100 sq. km) Area of 25 x 25 km representative of the cropping system 10 x 10 km for most intensive field measurements 9

10 supported by a CEOS Ad how WG JECAM Request to CEOS Agencies JECAM has received a significant number of datasets from CEOS Agencies and has made great progress toward understanding the use of satellite data for agriculture monitoring. Improved access and coverage + early access to new mission datasets are needed to address the highlighted areas. From the 2014 JECAM document JECAM Guidelines: Definition of the Minimum Earth Observation Dataset Requirements 10

11 supported by a CEOS Ad how WG Great CEOS support providing coordinated EO Data access for JECAM sites and a Datacube on-going experiment Examples: SPOT-4 Take 5 and SPOT-5 Take 5 time series acq. Radarsat-2 multi-year acquisition and the MURF license Pléiades imagery Harmonized Landsat-Sentinel-2 time series Radarsat Constellation Mission acq. RADARSAT- Constellation 11

12 annual reporting and science meetings Past years science meeting 2011 Calgary - Training workshop hosted by AAFC 2014 Ottawa (Canada) hosted by AAFC (AAFC support) 2015 Brussels (Belgium) hosted by UCLouvain (ESA Sen2-Agri support) 2016 Kiev (Ukraine) hosted by SRI (FP7-SIGMA support) 2017 Rome (Italy) hosted by FAO (FP7-SIGMA support) Forthcoming - JECAM AsiaRice joint science meeting ~ Sept Taichung (Taiwan) hosted by Taiwan Ag. Res. Inst. (TARI support) Brussels 2015 Rome,

13 JECAM Experimental achievements 3 cross-sites experiments published (6 papers) 5 on-going cross-sites experiments

14 14 large field experiment <<<<<<<<<<<< JECAM benchmarking of 5 cropland methods over 5 sites Large diversity Crop Calenders Landscape Pattern/Fragmentation Argentina Brazil China Russia Ukraine

15 large field experiment <<<<<<<<<<<< JECAM benchmarking of 5 cropland methods over 5 sites 5 partners to map cropland over 5 sites using the same 250 m MODIS time series and same in situ cal/val datasets CHINA UKRAINE MODIS compatible with 20 ha field for cropland map Similar method accuracies for all 5 methods for a given site Differences (~9 %) according to ag. landscape patterns Influence of the data quality variable according to site

16 crop type experiment <<<<<<<<<<<< JECAM cropland and crop types methods benchmarking over 12 sites in 2013 over 6 sites in 2015 SPOT 4 TAKE 5 FEB. TO MAY 2013 JECAM ARGENTINA SPOT 5 TAKE 5 APR. TO AUG. 2015

17 cross-site cropland method assessment <<<<<<<<<<<< JECAM cropland mapping method development 4 JECAM sites to test an innovative cropland classification method ARGENTINA UKRAINE CHINA BELGIUM

18 calibration dataset experiment <<<<<<<<<<<< JECAM source and density of calibration data (8 sites) Comparison of in-situ, crowd- and land cover-derived data sources to understand their applicability for large scale cropland mapping over JECAM sites across the globe 18 JECAM experiment to assess the impact of the sampling strategy for cropland and crop type mapping Impact of different sampling schemes on cal./val operations - 5 JECAM sites enlarged to 4 Landsat-8 scenes - Investigation for windshield survey impact

19 smallholder cropping system experim. <<<<<<<<<<<< JECAM crop type mapping in 2 contrasted cropping systems in Mali and Bangladesh Mali Bangladesh 5 main crop types (cotton, maize, millet, peanut, sorghum) 1.45 ha±0.86 average field size High heterogeneity level 2-3 crops per year (rice, lathyrus, mungbean, maize, jute, etc) Very small fields (~ 0.05 ha) Very homogeneous fields

20 in situ data model and data license STAC a data model to capitalize in situ over multiple years and sites (tested by JECAM Argentina) Open data license to share JECAM data 20

21 SAR experiments JECAM SAR Cross-Sites Inter-comparison Crop type mapping 18 sites sharing in situ data and AAFC pre-processing all data i. Applying Operational SAR and Optical Classification Methods to Multiple Regions: a) Applying Agriculture and Agri-Food Canada (AAFC) Earth Observation Crop Inventory Method to other JECAM Sites b) Applying JECAM Member Sites SAR and Optical, OR SAR only (single frequency) Classification Methodologies to Multiple Regions ii. Reducing the Impact of Cloud Cover on Operational Crop Inventories iii. Multi-frequency SAR imagery for Crop Type Mapping iv. Compact polarimetry and/or polarimetric decomposition variables for Crop Type Mapping. Led by Andrew Davidson, Laura Dingle-Robertson (AAFC)

22 SAR experiments JECAM SAR Cross-Sites Intercomparison Biomass mapping 10 sites sharing in situ data and AAFC pre-processing all data i. Enhance models using available data over Canadian and international JECAM sites ii. Compare the WCM model with other models have been used by other JECAM sites iii. Extend the model to other interested crop types such as rice iv. Adapt the model to multi-frequency and Compact-Pol SAR. Led by Heather McNairn, Mehdi Hosseini (AAFC) 22

23 impacts JECAM allows to Involve JECAM partners in a fully international framework Establish common standards to be able to dialog, to crosscompare and exchange on results Raise the research standards and best practices for the JECAM partners Mutually improve EO methods and in situ practices through exchange and sometimes field visits Attractive network for various initiatives JECAM leverage resources from ESA Sentinel-2 for Agriculture, BMGates Foundation, FP7-SIGMA, FP7- Imagines, AAFC SAR inter-comparison, and link to AsiaRice

24 RESEARCH NEEDS and COLLABORATIVE PRIORITIES Priorities and opportunities from JECAM and USDA-AAFC perspective

25 research priorities Short term priorities from JECAM (within the year) o SAR on-the-job training for the JECAM SAR Inter-comparisons: - in situ data collection (SAR specific protocols) - SAR time series exploitation by each JECAM team (Radarsat-2, Sentinel-1, possibly TerraSAR-X) - SAR-optical synergy for crop type mapping and biomass o Sentinel-2 time series exploitation using Sen2-Agri system versus alternative strategy : - Training session for the JECAM teams starting with Sen2-Agri - On-going experience sharing through Sen2-Agri webinars - Exploitation using a virtual machine on cloud computing - Targeting marginal crop mapping in various contexts (limits and feasibility) o Assessment of the HLS time series in different contexts o Development of quantitative metrics for yield assessment To be completed by the JECAM network members

26 research priorities Mid-term priorities from JECAM (0 to 2 years) o In situ yield measurements : protocols and standards compatible with EO time series to discuss and recommend o Yield estimation from EO and/or crop modelling, including the use of new ancillary datasets like IMERG, SMAP level 4 products, etc. o Field delineation algorithm to be tested in different cropping systems o Algorithm benchmarking for machine learning, phenometrics, and practices management across sites and geographies TBD at the annual science meeting

27 research priorities Opportunities for LTAR sites to join the JECAM network according to the mandate of the LTAR sites? o Compare his/her own in situ and EO practices with regards to existing JECAM standards and exchange with others about these practices o Get access to EO time series specifically of interest for agriculture monitoring o Get exposed to globally distributed colleagues, challenges and get trained thanks to a very open and focused atmosphere o Partner with scientific team to exploit long term archive across sites with shared methods

28 research priorities Opportunities for JECAM through a USDA-NASA-AAFC-SIAP partnerships o Assessment of various new products in different cropping systems wherever they are available ou could proposed: o Evaporative Stress Index (ARS), o soil moisture product (USDA-NASA), o Wetness index (AAFC) o Greensat for Nitrogen management (SAGARPA-SIAP) o Canadian Crop Yield Forecaster (AAFC - N.Newland) o JECAM sites to be considered for the NISAR mission Cal/Val o UAV exploitation to support in situ data measurements and scaling up

29 About Becoming a JECAM Member Simple process: - Fill a questionnaire to document the site - Complete an annual report describing their research - Attend the annual science meeting - Be willing to share their science and data with other sites in the network The value sites get from JECAM in proportional to their engagement JECAM is a research platform, not a funder, however the coordinated nature of JECAM provides a compelling opportunity to attract research funding (national or international sponsors). Please contact JECAM through the JECAM website (JECAM.org) or directly to Andrew Davidson( Andrew.Davidson@agr.gc.ca )

30 for more info - JECAM.ORG Thank you for your attention