Sven Gilliams, VITO-TAP, 30/05/2017, IACS WS Gent. An eye on crops, thanks to global Satellite monitoring
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1 Sven Gilliams, VITO-TAP, 30/05/2017, IACS WS Gent An eye on crops, thanks to global Satellite monitoring
2 VITO FLEMISH INSTITUTE FOR TECHNOLOGICAL RESEARCH: AREAS OF EXPERTISE Energy Materials Chemistry Health Land use remotesensing.vito.be
3 End to end solutions Platforms Drone - local Aircraft - region HALE UAV - country Satellite - global Instruments Value Added Services & Information Products Markets Vegetation Agriculture Water Infrastructure Environment & Security remotesensing.vito.be
4 Agriculture
5 Advice for Agriculture From global monitoring to local advice Frequent observations to monitor crop growth Provide reliable data access Assure capacity Focus on research and development to use ever evolving technology (new satellites, better capabilities ) remotesensing.vito.be
6 Processing center Sentinel 2 Sentinel 3 processing Current capacity 6 remotesensing.vito.be
7 The Product Distribution Facility vito-eodata.be remotesensing.vito.be
8 Software and processing chain development Large availability of free remote sensing data, but: Remote sensing and processing software not specifically designed for time series processing Food security analysts are usually not software programmers Tools developed in the past are no longer updated (e.g. WINDISP) Online platforms don t allow high degree of customization (e.g. Crop explorer, Decision Support Interface (DSI), MARS Viewer) remotesensing.vito.be
9 Agricultural Monitoring Examples Global-> local
10 Remote sensing support to the European Union» EC JRC MARSOP» Agricultural production?» Support to the European Commission Common Agricultural Policy (CAP)» Since 2000» Operational delivery remote sensing indicators and software CIS CCA WAF IGA ASI MCS SAC AFR remotesensing.vito.be
11 Agriculture and Environment FP7 Land cover & crop land assessment Agricultural Productivity Env. Impact Assessment of Land use change Sites: IKI RAN, SRI, RADI, CIRAD, INTA, VITO, UCL, GEOSAS, AGHRYMET SIGMA: Global Phenology remotesensing.vito.be
12 Global Drought Monitoring Global Near Real Time Cropland & grassland Agricultral Stress Index
13 Agriculture & Food Security: Agricultural Stress Index System Monitoring vegetation drought stress on a global scale focusing on crop areas in growing season The vegetation health index (VHI), based on linear combination of vegetation and temperature related indices, is used as indicator for drought probability Progress in of the first growing season on dekad 1 July calculated on the Long Term Average of NOAA-AVHRR over the years A phenological NDVI-based model is used to define the start of the growing season VHI is averaged over the growing season and aggregated over administrative units Agricultural stress index (ASI) at the end of The ASI is defined as the percentage of crop area within each administrative unit with a mean Vegetation Health Index (VHI) over the growing season below 35%. remotesensing.vito.be
14 Development of new products for agriculture monitoring Global CO 2 uptake remotesensing.vito.be
15 Online Applications / Viewers / Dashboards Satellite Time Series Viewer as first step: Aim: quickly explore & review satellite time series and complementary indicators for agriculture and environmental monitoring remotesensing.vito.be
16 WatchITgrow for the future of the Belgian potato chain Monitoring potatoes from space!» Crop development» Field heterogeneity» Risk at production and quality losses» Yield forecasts For all actors in the potato chain: - Get access to satellite images, weather data, yield forecasts - Store your own field data (e.g. treatments, yield samples, )
17 Weather info» Country wide weather info on a weekly basis:» Average temperature» Precipitation sum deviation with average risk at production or quality losses?
18 Satellite images» Sentinel-2:» 10m pixels» Since August 2015» Every 10 and soon every 5 days» DMC/Deimos:» 22m pixels» since 2009» Every 2 days monitor & compare fields
19 Monitor your fields throughout the season Greenness index Emergence 1 May May May June July July Aug 2016 Senescence 26 Aug Sept Sept Sept 25 Sept Sept Oct 2016
20 Check your fields for anomalies Water logging in June 2016 Sentinel-2 of 20 July 2016 (10m) UAV image of 18 July 2016 (RGB, 3 cm) UAV image of 18 July 2016 (NDVI, 8 cm) NDVI Greenness index < 50%: crop lost or severely damaged
21 Check your fields for heterogeneity Sentinel-2 of 20 Aug 2016 Greenness index useful for field selection (historical data) improved sampling (per zone) Electrical conductivity (EC) Acidity (ph) evolution towards precision agriculture: variable rate application of fertilizers, irrigation, haulm killing, Reference data from soil scans (source: CRA- W)
22 Compare your fields Sentinel-2 of 22 Aug 2016 Senescence started? Haulm killing applied? optimize field visits input for planning / logistics (harvest) More advanced senescence Still green
23 Optical (e.g. Sentinel 2) Sensitive to biophysical processes Relatively simple signal Cloud issues SAR (e.g. Sentinel 1) Sensitive to vegetation structure Complex signal All-weather Goal: use both in complementary way to better monitor crops remotesensing.vito.be
24 Thank you for your attention Sven Gilliams, Agricultural Applications Team leader, VITO remote sensing 30/05/2017 IACS WS, Gent
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