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This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.Sven Gilliams, VITO‐TAP
SIGMA Consortium
Introduction
2050 – 70% increase in agricultural productivity? Sustainable intensification of agriculture:
• Agricultural Expansion• Agricultural Intensification
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
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This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
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SIGMA ‐ Facts Funded By The European Commission Start 1 November 2013 – 30 March 2017 Agriculture AND EnvironmentAgriculture AND Environment 22 partners, 17 countries
• VITO, CIRAD, JRC, IIASA, Alterra, RADI, NMSC, DEIMOS, GeoSAS, RCMRD, Aghrymet, RCMRD, Sarvision, Sarmap, INTA, Geoville , UCL, EFTAS, FAO, ITC, GISAT, IKI, SRI
Argentina, Ukraine, China, Russia, Burkina Faso, Ethiopia USA, Brazil, Vietnam, Belgium, …11 2 M EUR 11,2 M EUR
A Major European contribution to GEOGLAM
Coordinated by VITO Coordinated by VITO http://www.geoglam‐sigma.info/
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
SIGMA ‐ Goal
Improve Remote Sensing based methods and indicators to
monitor and assess progress towards “sustainable agriculture”,
Inventory of Crop land distribution and its changes over timeCh t i h i i lt l d ti l l Characterize changes in agricultural production levels
Assess environmental impact of agriculture over time
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
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SIGMA Activities
Land cover & crop Agricultural E I tLand cover & cropland assessment
Agricultural Productivity
Env. Impact Assessment of Land use change
Sites: IKI RAN, SRI, RADI, CIRAD, INTA, VITO, UCL, GEOSAS, AGHRYMET
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
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Data Management
Capacity Building
SIGMA: Data Management• SIGMA distribution facility• SIGMA Analysis facility (VEGA)• SIGMA Validation facility(GeoWiki)• Agricultural database (STAC)
Expert validation campaignCore reference data set (~ 4000 samples)o e e e e ce da a se ( 000 sa p es)
Object‐based validation samples of high qualitySIGMA project partners & invited experts
Geowiki crowd sourcing campaignLarge number of point validation samples of unknown
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
Large number of point validation samples of unknownquality (~ 50 000 samples)
Cross‐site experiments & Global Validation Effort
htt // t b / t h? PR3 MPP https://www.youtube.com/watch?v=PR3xMPPyp‐I&feature=youtu.be
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
SIGMA: Global Cropland Priority map for land cover mapping + Global cropland map
Spatial aggregation of country levelcropland maps that best satisfy 4criteria:1) timeliness, 2) confidence, 3)thematic definition and 4) spatialresolution adequation.
Waldner, F.; Fritz, S.; Di Gregorio, A.; Plotnikov, D.; Bartalev, S.; Kussul, N.; Gong, P.; Thenkabail, P.;
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
Waldner, F.; Fritz, S.; Di Gregorio, A.; Plotnikov, D.; Bartalev, S.; Kussul, N.; Gong, P.; Thenkabail, P.; Hazeu, G.; Klein, I.; Löw, F.; Miettinen, J.; Dadhwal, V.K.; Lamarche, C.; Bontemps, S.; Defourny, P. A Unified Cropland Layer at 250 m for Global Agriculture Monitoring. Data 2016, 1, 3.
SIGMA: Global AE StratificationGlobal SIGMA geodatabase – 1 kmAgricultural landscape character as a functional
hierarchy of abiotic, biotic and cultural phenomena
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
SIGMA next: Global Cropland
A fully automated cropland classification frameworkCombining SIGMA’s validation stratification and mapping achievementsThe method relies on baseline data sets for training and handles high dimensional input data and is trained specifically for different agro‐ecological strata.
Combining SIGMA’s validation, stratification and mapping achievements
Waldner F., Sepulcre Canto G., Defourny P., “Automated Annual Cropland Mapping using Knowledge-Based Temporal Features” 2015 ISPRS Journal of Photogrammetry and Remote Sensing Volume 110 December 2015 Pages 1 13
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
Features , 2015, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 110, December 2015, Pages 1–13
Production; Potential for agricultural intensificationintensificationConcept of yield gaps Use of crop models
to assess potential yield level Use of EO & models & statistics
to assess actual yield levels
Developed procedure to select sites using an agro-climatic zonation (CZ) and crop masks
Crop mask millet
Locations for crop calibration
CZ representativeness Burkina Faso
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
Production; Trends of environmental parametersparameters Provision of time‐series of EO data:
• LR vegetation indices & spectral inter‐calibration of sensors to replace pmissing values & to extend time series
• Soil moisture• Evapotranspiration
HR data simulation (data fusion) Trend analysis & change detection
• Yearly phenology (SoS, EoS, length)• Number of growing seasons per year
Crop monitoring & yield estimation protocols
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
SIGMA: take away for UFA JECAM SUPPORT
• Expand African network!??S d d d B i• Standards and Best practices
• Cropland definition,…• Field data collection• Validation• Validation• Cross site experiments
SIGMA TRAINING SESSIONS• 2 regional sessions in Africa (organised by RCMRD)• Topics
o Agricultural Statisticso EO based Agricultural Monitoringo Crop modellingo Environmental Impact Assessment of Agricultural land use change
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
Thank you!VITO, CIRAD, JRC, IIASA, Alterra, RADI,
NMSC, DEIMOS, GeoSAS, RCMRD, A h t RCMRD S i i SAghrymet, RCMRD, Sarvision, Sarmap, INTA, Geoville , UCL, EFTAS, FAO, ITC,
GISAT, IKI, SRI
This project has received funding from the European Union’s Seventh Programme for research,technological development and demonstration under grant agreement No 603719.
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