1. MARS Webviewer training course 20 th - 21 th June 2013: With focus on Africa Training on Crop monitoring with remote sensing Joint Research Centre, Ispra, 17 th - 21 th June 2013 Hugo de Groot, Alterra, Wageningen UR. hugo.degroot@wur.nl hugo.degroot@wur.nl

2. Content Introduction to the MARSOP3 project and data Exploring MARSOP3 data by using the webviewer Extensive demo Hands-on training

3. JRC: Joint Research Centre IES: Institute for Environment and Sustainability AGRI4CAST AGRI-ENV FoodSec GeoCAP MARS unit (Monitoring Agricultural ResourceS) MARSOP3: (www.marsop.info) European Commission MARSOP3 services Monitoring Agricultural Resources (MARS) Operational services

4. MARSOP3: list of operational services weather monitoring based on interpolated station data Africarainfall estimates based on MSG and observed rainfall pan-Europeweather and vegetation indices based on MSG-SEVIRI pan-Europe and Horn of Africavegetation indices based on MODIS-250m sensor pan-Europevegetation indices based on METOP-AVHRR sensor globalvegetation indices based on NOAA-AVHRR sensor globalvegetation indices based on SPOT-VEGETATION sensor globalcrop specific drought monitoring globalweather monitoring based on ECMWF deterministic forecast pan-Europecrop yield forecast based on ECMWF ensemble models pan-Europe and Asiacrop yield forecast based on ECMWF deterministic forecast pan-Europecrop yield forecast based on interpolated station data pan-Europecrop monitoring based on ECMWF ensemble models pan-Europe and Asiacrop monitoring based on ECMWF deterministic forecast pan-Europecrop monitoring based on interpolated station data pan-Europeweather monitoring based on ECMWF ensemble models pan-Europe and Asiaweather monitoring based on ECMWF deterministic forecast pan-Europe

5. MARS Webviewer MARSOP3 services deliver and store large amounts of basic and added value data (size is now 7 TB !) Basic weather data / Remote Sensing based Vegetation Indices Added value data generated in the various operational levels of the MARSOP3 services through downscaling and aggregation Online viewer enables user to perform spatial and temporal analysis of global state-of-art data sets in a customized way

6. Exploring the data by using the Mars webviewer http://www.marsop.info Note: Possibility to register (normally access is granted for half a year)

7. Login to the Mars webviewer guest1 ispra guest2 ispra... guest30ispra

8. Choices at startup Region of interest Zoom to specific part Result type Map, Graph, Quicklook

9. MARSOP3: regions of interest Demo

10. Viewer capabilities: Produce MAPS and GRAPHS for spatial and temporal analysis: On the fly created from the data; based on user choices Large amount of indicators available View QUICKLOOKS Static, preprocessed results from crop monitoring by remote sensing. Indicators: Normalized Difference Vegetation Index (NDVI) Dry Matter Productivity (DMV) Fraction of Absorbed Photosyntheticly Active Radiation (fAPAR) Rainfall estimates (for whole Africa only)

11. Map and graph Rainfall anomaly april / may Example of weather indicators

12. Quicklook

13. MARSOP: list of operational services weather monitoring based on interpolated station data Africarainfall estimates based on MSG and observed rainfall pan-Europeweather and vegetation indices based on MSG-SEVIRI pan-Europe and Horn of Africavegetation indices based on MODIS-250m sensor pan-Europevegetation indices based on METOP-AVHRR sensor globalvegetation indices based on NOAA-AVHRR sensor globalvegetation indices based on SPOT-VEGETATION sensor globalcrop specific drought monitoring globalweather monitoring based on ECMWF deterministic forecast pan-Europecrop yield forecast based on ECMWF ensemble models pan-Europe and Asiacrop yield forecast based on ECMWF deterministic forecast pan-Europecrop yield forecast based on interpolated station data pan-Europecrop monitoring based on ECMWF ensemble models pan-Europe and Asiacrop monitoring based on ECMWF deterministic forecast pan-Europecrop monitoring based on interpolated station data pan-Europeweather monitoring based on ECMWF ensemble models pan-Europe and Asiaweather monitoring based on ECMWF deterministic forecast pan-Europe

14. Datasets and resolutions

15. Quicklook: define content User defines which part of the data will be visualized Hierarchical choices: Resolution Theme (service) Indicator Function Time period and other additional parameters Push the button

16. Quicklook: view result Possible user actions: = home, start again

17. Define content: Function Used everywhere Default:Year of Interest (YOI), and default the year of interest is the actual year Other:Long term average (LTA) Difference with long term average Difference with previous year Difference with any other year (availability depends on situation) Important to see the spatial distribution of temporal effects or anomalies ! Demo

18. Map: map actions Map mode buttons: Activate one, then click inside the map Map action buttons: Perform action immediate on click Additional functionality: Leave this map window, start other part

19. Map: define content User defines which part of the data will be visualized Hierarchical choices: Resolution Theme (service) Crop / Landcover Indicator Function Time period and other additional parameters Aggregation type Push the button

20. Map: view result

21. Map: Layers = export or print = home, start again = open additional map window Multiple map windows are linked Demo

22. Maps and Quicklooks: time out Hands on: Play around with the viewer in Africa Change the resolution and view the result map Change the theme and view the result map Switch between ‘Quicklooks’ and ‘Maps’ Change the indicator and view the result map Play with the function and view the result map Play with the time period and view the result map Open multiple linked maps and play around Go to the ‘Layers’ tab and add additional layers to the map Don’t change the legend, and don’t look at graphs

23. Graphs Always act on at least one ‘spatial entity’, so on a specific area This ‘spatial entity’ can be of any available resolution So it can be: a country (Admin Level 0 = Countries) a district (Admin Level 1 = Districts) a grid cell

24. Graphs: opening a graph Select a ‘spatial entity’ from the map Inside the map, activate the ‘Select feature’ tool: Click inside the map in order to select an area The selected area gets highlighted (maplayer must be visible) Click on the ‘Add graph window’ button:

25. Map: opening a graph = export or print = home, start again = open additional map window Multiple map windows are linked Shown before = open graph window for selected spatial entity

26. Graphs Select the ‘graph type’: Demo

27. Graph types All available years Bar chart Extra options: One specific year, one indicator, multiple spatial entities Line chart, more spatial entities possible (up to 6) Extra options: and Shift-click ! One specific year, multiple indicators, one spatial entity Line chart, more chart series possible (up to 6) Extra options:

28. Graph: define content User defines which part of the data will be visualized Push the button Hierarchical choices: Theme (service) Crop / Landcover Indicator Function Time aggregation Overlapping profile Note: Time period is specified in separate tab

29. Graph: define content Push the button Time period: Default starts at January 1 st Timescale depends on dataset (Theme) For Africa mostly ‘Dekad’ (10 day periods) 1 – 10 11 – 20 21 – end of Month

30. Define content: Overlapping profile Used for graphs Use: Explore extreme situations Compare with other years Note: The Year of Interest (YOI) is excluded in calculating the overlapping profile values !

31. Maps and Graphs Maps and Graphs are linked Functionality at the map window for linking Select feature tool, works on the ‘active layer’ The graph gets updated automatically on a change of the selected area (if the selected area is of the same resolution) The active layer can be changed on the Layers-tab : Demo On a resolution changes the active layer changes automatically

32. Map and graph Indication of green and healthy vegetation cover Example of remote sensing based vegetation index

33. Maps and Graphs: time out Hands on: Play around with maps and graphs in Africa Open a map window and click the ‘Add graph’ button: What happens? Make sure you can open a graph window from the map window Try the three different graph types, view the graph results With a graph result on the screen: Change the selected spatial entity by selecting another one from the map Change the theme, the crop / landcover, the indicator and view the result graphs Play with the function and the time period and view the result graphs Play with the overlapping profile and view the result graphs Switch between ‘Africa’, ‘West Africa’ and ‘Horn of Africa’ Open multiple linked maps, open a graph from every map window and play around Go to ‘Home’ and start a graph: graph only window Question: how to select a ‘spatial entity’

34. Map legends Each indicator has a default legend, the system legend. Possible user actions: - Edit: Change a legend. - Select: Select a different legend. - Delete: Delete a previous saved legend.

35. Map legends Edit legend ‘by hand’: Add / remove legend classes Change legend class range, color or label

36. Legend type: Auto-calculate other than normal legends Map legends Class boundaries get calculated on the fly based on the actual values which correspond with the current user choices for variable and time-period. Two types: Equal area Equal width

37. Map legends Update map = Preview map with the new legend settings. The legend is not yet saved. Save as = Add this legend to the database storage, for later reuse. It must be stored under a new name. Save = overwrite this legend with the new settings (only available for an earlier saved legend). Show and / or store the result:

38. Map legends Select legend: Choose from a selection of legends, designed for this indicator Check ‘Show all’ to choose from all legends:

39. Map legends Delete legend: Throw away an earlier saved legend Demo

40. Map legends: time out Hands on: Play around with legends Open a map window and view a result map Start the legend editor Add a legend class and view the result map Remove a legend class and view the result map Change the color for some classes and view the result map Play around with the legend types (normal / equal area / equal width) and view the result maps Save the new legend for later reuse Did you give the new legend a name? If not, what happened? Save some more legends Switch between saved legends and view the result maps Remove a saved legend

41. Map viewer Examples: time period: look at growing seasons starting in October or November Go deeper into (and show) aggregation type, within short time period (for Minimum Temperature or so).

42. Map viewer: Map export facilities Print Save as.pdf Save as.png

43. Map viewer: export facilities Print Save as.pdf Save as.png Save as.csv, to open in Excel

44. Map viewer: Quicklook export facilities After download: Print from your browser Save from your browser Demo

45. Export facilities: time out Hands on: Play around with the export facilities Open a quicklook window and view a quicklook result Download the quicklook Save the quicklook image on your hard disk Open a map window and view the result map Export the result map to your local file system Open a graph window and view the result graph Export the result map to your local file system. Try different formats, including.csv If you have Excel installed: Open the.csv file in Excel