1 / 20

ESA’s Crop Monitoring And Early Warning Service

ESA’s Crop Monitoring And Early Warning Service. Outline. This presentation Background Partners Services Early Warning Agricultural Monitoring CFSAM. ESA Stage 3 Background GMFS started in 2003 New contract GMFS3 -> 2013 Continuation of services to Stage 2 users

beth
Download Presentation

ESA’s Crop Monitoring And Early Warning Service

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ESA’sCrop Monitoring And Early Warning Service

  2. Outline • Thispresentation • Background • Partners • Services • EarlyWarning • Agricultural Monitoring • CFSAM

  3. ESA Stage 3 Background • GMFS started in 2003 • New contract GMFS3 -> 2013 • Continuation of services to Stage 2 users • Focus is onSustainability

  4. Partners

  5. ESA Technical officer User Board Overall Management VITO Scientific Board West Africa Regional coordinator AGRHYMET(CRA) East Africa Regional coordinator RCMRD Southern Africa Regional coordinator Service Groups 7 GMFS3 Services SouthernAfricaregion West Africaregion East Africaregion ZimbabweMoA EthiopiaMoARD MozambiqueINAM SudanFMoAF MalawiMoAFS MaliLaboSEP SenegalCSE

  6. EarlyWarning Service • CropYield and VegetationMonitoring • SoilMoistureAnalysis • FAST

  7. Early Warning Service  3 independant sources of information Convergence of evidenceanalysis MERIS Vegetation MSG Rainfall Radiation ASCAT Soilmoisture SUPPORT EW ANALYSIS TRAIN HOW TO USE THE DATA

  8. Early Warning Service

  9. QualitativeAnalysis: Earlyor Late Start of the GrowingSeason Crop Yield and Vegetation Monitoring Context: In SahelRegion the start of Season is a first indicator of cropdevelopmentsuccessorfailure (Approachpublished in the CILLS bulletin) Profile MatchingApproach: • Compare the fAPARprofilefor the 3 firstmonths of the 2011 seasonwith the average 1999-2010 • Display the shift that have the best fit with the • Long Term Average • Giveanoverview of the anticipatedordelayedarea at pixel level Phase/shift

  10. CropYield and VegetationMonitoring QualitativeAnalysis of ongoingGrowingSeasonfor Agricultural Monitoringbasedon low Resolution Data Context: Standard AnomalyMapsbasedoncomparisonwith LTA give a goodspatialoverview of anomalies, thisapproachaddsduration and intensity to the maps Cluster analysis : • Iso data classificationbasedon the relative • differencebetween 10 day VI and • Display classified map • with the corresponding classes profiles

  11. CropYield and VegetationMonitoring YieldEstimationbasedon Low ResolutionMonitoring Context: Non ParametricYieldForecast SimilarYears to Yieldestimate SimilartyAnalysis : • CROP MAP ! • foreach pixel the most similaryear is found • Display classified map • Per ADMIN percentage

  12. CropYield and VegetationMonitoring YieldForecasting USERS ParticipatoryDevelopment

  13. SoilMoistureMonitoringFAST Service

  14. Agricultural Monitoring • Support to the Optimization of the National Agricultural Survey Service • Agricultural Mapping • SAR Knowledge Transfer

  15. ASO in Malawi “ASO” service: “support to the optimisation of national surveys”. In collaboration with JRC this service is focussed to consultancy on the introduction of area frame sampling approaches , making use of EO data which istechnically sound and sustainable in the Malawian context Point frame: 500 m spacing , - approx. 4 points per km2 1. EO data are used for thedesign of the sampling frame and its realisation: location of sample points, interpretation and classification, masking and stratification. Points vs. segments 2. EO data are used with GPS for survey optimisation and execution, e.g. maps for identifying the sampled points, planning of itineraries, control (synergies with field area measurements for APES, etc. see also proposals by MoAFS on the use of IT , FAO) to be interpreted and classified Based on a simple LCLU legend 3. EO data are also used as auxiliary variables (land cover/land use classified images)to improve the accuracyin the estimation of the cropacreage by means of ad hoc statisticalprocedures. Up to 58.000 points are visited on the ground (sampling rate around 15 %)

  16. ASO + AM North Sudan • 2 Scales, Medium Resolution, High Resolution • LCCS support • High Resolution Satellite Image coverage NKOR • Multi resolution segmentation of NKOR • Harmonized field work • Outputs • Data & processing support for current LCCS mapping • recent HR Satellite image mosaic on state level • Segmentation layer • Field work

  17. ASO + AM in North-Sudan GMFS fAPAR-EoGNorth Sudan 2010 GMFS fAPAR-EoGNorth Sudan 2005 • Change maps: • Context: there is a huge variability in the extent of growth (EoG) in North Sudan, based on MERIS-FR fAPAR images and analysis is made on this difference. Maps can be used in support of the Agricultural Survey • Indication upon differences in growth activities • Training on use of change maps is currently ongoing (September 2011)

  18. CFSAM support to FAO/WFP FAO publication explaining the importance of Environmental Remote Sensing indicators for monitoring, using amongst others ESA-MERIS RR fAPAR (data processing + methodology = GMFS)

  19. Thank you ! Questions?

More Related