GEOGLAM Global Agricultural Monitoring. Michel Deshayes

Transcription

1 GEOGLAM Global Agricultural Monitoring Michel Deshayes

2 Outline GEOGLAM and AMIS GEOGLAM Structure and Governance New activities and projects Rangelands and Pasture Monitoring Early Warning Crop Monitor Increased collaboration with WMO 2 / 11

3 GEOGLAM & AMIS Two initiatives to increase information availability, quality and transparency : GEO-GLAM GEOGLAM : improve information on supply (GEO) AMIS : improve information on markets (FAO) Supply Prices Demand Politicies Finance Stocks Trade AMIS UNITED NATIONS HLTF Food Security 3 / 11

4 GEOGLAM Crop Monitor for AMIS (1/3) Crop Monitor for AMIS: 1 Year Operational! From June 2014 : New presentation of results (1/3) a. A global map for the 4 AMIS crops (Maize, Wheat, Soybean, rice) Map of end August / 11

5 GEOGLAM Crop Monitor for AMIS (2/3) From June 2014 : New presentation of results (2/3) 4 synthetic texts 5 / 11

6 GEOGLAM Crop Monitor for AMIS (2/3) From June 2014 : New presentation of results (2/3) 4 synthetic texts 6 / 11

7 Achievements GEOGLAM Crop Monitor for AMIS (3/3) A presentation of results with graphics and text (cont ) c. 4 synthetic pie-charts sectors proportional to countries average share of world production colors according to local crop conditions symbols to explain reasons for bad conditions Rice 28 August 14 Wheat Maize Soybean 7 / 11 7

8 GEOGLAM Structure and Governance GEOGLAM Advisory Committee Including G20 Donor representation, program stakeholders Program Coordinator + Secretariat Implementation Committee consisting of Implementation Team leads 1. Global / Regional System of Systems main producer countries, main commodities 2. National Capacity Building for agricultural monitoring using earth observation 4. EO data coordination 3. Monitoring countries at risk food security assessment 5. Method improvement through R&D coordination (eg. JECAM) 6. Data products and information dissemination Tasks Tasks Tasks 8 / 11

9 Emerging activities a. RAPP - Rangelands and Pasture Productivity Objectives establish a dedicated global system for observing pastures and rangeland status, biomass dynamics and productivity more effective planning based on accurate forecasts of pasture and rangelands productivity variability. improved global understanding of risk across all landscapes as climate and land use change through the addition of these lands into global agricultural monitoring. RAPP Rangeland and Pasture Productivity Monitoring Action under Australian leadership (CSIRO) 2 nd Workshop held in Paris, July 2014 Objectives: Develop community, identify pilot areas, identify key EO data sets, discuss interface global pasture monitoring system 3 rd workshop, Brasil July 2015 (TBC) 9 / 11

10 Emerging activities b. EWCM Early Warning Crop Monitor (1/2) Countries at Risk Monitoring Ongoing projects : FAO (GIEWS), WFP, USA (FEWS-NET), EC (MARS-FS), China (CropWatch-FS) Agreement on organising a collaborative monitoring of Countries at Risk 1st meeting: Frascati (Feb.2014), 2 nd meeting: Addis-Ababa (Oct.2014) Next meeting: FAO-Rome (13 th May 2015) On-going: Development of a prototype Website, allowing partners inputs and data & information sharing (next slide) 10 / 11

11 Emerging activities b. EWCM Early Warning Crop Monitor (2/2) Verdin et al. 11 / 11

12 Emerging activities c. Increased cooperation with WMO Under discussion with WMO : A closer cooperation with CAgM (Commission for Agric. Meteorology), at the initiative of its President, Prof. B-L Lee June: 1st meeting in GEO Sec. with Prof. Lee (WMO ExCom66) November: GAMOS conference, Jeju (Korea), Nov GAMOS = Global Agro-Meteorological Outlook Service Alliance through S2S-AgModel Linkages Terms and deliverables of future collaboration to be discussed e.g. WMO S2S: Subseasonal to Seasonal Prediction Project 12 / 11

13 Thanks for attention! GEOGLAM, Global Agricultural Monitoring 13

14 EO-based Agricultural Monitoring in Africa (1/2): Challenges Info needs for Agricultural Monitoring Crop area mapping Cropland map (and area) Crop type area / map (parcel level) - as early as possible Crop growth monitoring Crop stages - Phenology Crop yield forecast EO-based crop yield model African challenges for EO monitoring Mixed crops Small fields, sometimes uneasy to delineate (convoluted limits) Variable presence of natural vegetation Cropping systems changing over time 14 / 15

15 Agricultural Monitoring (2/2) : Need to adapt to Regional Agrosystems ex. Mixed crops Rungbe, Tanzania Agroforestry systems based on : Small fields : m². Crops: perennial (coffee, banana, cocoa, tea, fruit trees) & annual (corn, rice). «CBM» : Coffee, Banana, and Maize Trends Upper areas: CBM progressing, with gradual trimming of tea-cropping areas and Afromontane forest. Lower areas : CBM being abandoned in advantage of cocoa and rice monoculture, supported by significant investments (irrigation). C. Lelong CIRAD 15 / 30

16 Issue of Quality of Global Cropland Maps Accuracy of global Land Cover maps Ex. MODIS Land Cover Product Assessment in Sub-Saharan Africa (29 countries) using : FAO and AGRHYMET statistical agricultural data 55 5x5 km very-high-resolution images (DigitalGlobe, SPOT) Results : Maximum precision 70%, and often less. User Accuracy Leroux, L., A. Jolivot, A. Bégué, D. Lo Seen, and B. Zoungrana How Reliable Is the MODIS Land Cover Product for Crop Mapping Sub-Saharan Agricultural Landscapes? Remote Sensing 6: doi: /rs / 15

17 Issue of Quality of Global Cropland Maps Accuracy of global Land Cover maps Ex. MODIS Land Cover Product Assessment in Sub-Saharan Africa (29 countries) using : FAO and AGRHYMET statistical agricultural data 55 5x5 km very-high-resolution images (DigitalGlobe, SPOT) Results : Maximum precision 70%, and often less. User Accuracy Leroux, L., A. Jolivot, A. Bégué, D. Lo Seen, and B. Zoungrana How Reliable Is the MODIS Land Cover Product for Crop Mapping Sub-Saharan Agricultural Landscapes? Remote Sensing 6: doi: /rs / 15