Sven Gilliams, VITO TAP SIGMA Consortium

Transcription

1 Sven Gilliams, VITO TAP SIGMA Consortium

2 Introduction % increase in agricultural productivity? Sustainable intensification of agriculture: Agricultural Expansion Agricultural Intensification 2

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4 SIGMA Facts Funded By The European Commission Start 1 November March 2017 Agriculture 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 A Major European contribution to GEOGLAM Coordinated by VITO sigma.info/

5 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 time Characterize changes in agricultural lproduction levelsl Assess environmental impact of agriculture over time 5

6 SIGMA Activities Land cover & crop Agricultural Env. Impact land assessment Productivity Assessment of Land use change Sites: IKI RAN, SRI, RADI, CIRAD, INTA, VITO, UCL, GEOSAS, AGHRYMET Data Management Capacity Building 6

7 SIGMA: Data Management SIGMA distribution facility SIGMA Analysis facility (VEGA) SIGMA Validation facility(geowiki) Agricultural database (STAC) Expert validation campaign Core oereference eee cedata a set (~ 4000 samples) Object based validation samples of high quality SIGMA project partners & invited experts Geowiki crowd sourcing campaign Large number of point validation samples of unknown quality (~ samples)

8 Cross site experiments & Global Validation Effort t / t h? I&feature=youtu.be

9 SIGMA: Global Cropland Priority map for land cover mapping + Global cropland map Spatial aggregation of country level cropland maps that best satisfy 4 criteria: 1) timeliness, 2) confidence, 3) thematic definition and 4) spatial resolution adequation. 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.

10 SIGMA: Global AE Stratification Agricultural landscape character as a functional hierarchy of abiotic, biotic and cultural phenomena Global SIGMA geodatabase 1 km

11 SIGMA next: Global Cropland A fully automated cropland classification framework Combining SIGMA s validation, stratification and mapping achievements The method relies on baseline data sets for training and handles high dimensional input data and is trained specifically for different agro ecological strata. 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

12 Production; Potential for agricultural intensification Concept 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

13 Production; Trends of environmental parameters Provision of time series of EO data: LR vegetation indices & spectral inter calibration of sensors to replace missing 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

14 SIGMA: take away for UFA JECAM SUPPORT Expand African network!?? Standards d and Best practices Cropland definition, Field data collection Validation Cross site experiments SIGMA TRAINING SESSIONS 2 regional sessions in Africa (organised by RCMRD) Topics o Agricultural Statistics o EO based Agricultural Monitoring o Crop modelling o Environmental Impact Assessment of Agricultural land use change

15 Thank you! VITO, CIRAD, JRC, IIASA, Alterra, RADI, NMSC, DEIMOS, GeoSAS, RCMRD, Aghrymet, RCMRD, Sarvision, i Sarmap, INTA, Geoville, UCL, EFTAS, FAO, ITC, GISAT, IKI, SRI