Global Research Project 4:<br />Reducing land health risks and targeting Agroforestry interventions to enhance land produc...
Apply methods to multi-scale targeting of sustainable land management & assessing intervention outcomes</li></ul>Thomas Gu...
Surveillance Science Principles<br /><ul><li>Measurefrequency of problems and associated risk factors in populations using...
Sentinel Site Surveillance Frameworka spatially stratified, hierarchical, randomized sampling framework<br />Sentinel site...
Soil-Plant Spectral Diagnostics<br /><ul><li>Spectral methods and decision support tools
Reference lab for AfSIS
Capacity building</li></li></ul><li>Scientific workflows<br />AfSIS IR spectral<br />prediction engine <br />
Digital mapping of land health<br />Automated reporting<br />Topsoil soil organic carbon (g kg-1) for Kipsing derived by s...
AfSISExternal Review<br />Pioneering unique effort<br /><ul><li>Pioneering effort intended to fill one of the major gaps i...
Unique scientific effort never attempted before.  Admirable first done in Africa.
Highly motivated team of creative scientists.
Well on track to deliver on its major goals</li></ul>Outstanding design & implementation<br /><ul><li>Well-documented, uni...
Outstanding design and implementation of field surveillance under very difficult conditions.
Sentinel sites will likely become long-term monitoring and research sites for many different purposes.</li></ul>Soil spect...
The ICRAF soil spectroscopy lab is a pioneering facility and many experts are taking notice.
Great progress in building soil spectral libraries for functional interpretation.
Good, well-documented workflows and quality control protocols.
Excellent training of NARS collaborators provided by the ICRAF lab.
Excellent potential for digital soil mapping in Africa / Large spill over effects
Excellent potential to link the soil spectral analysis information with higher-resolution remote sensing data for digital ...
Upcoming SlideShare
Loading in …5
×

land health surveillance highlights

668 views
620 views

Published on

land health surveillance highlights

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
668
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

land health surveillance highlights

  1. 1. Global Research Project 4:<br />Reducing land health risks and targeting Agroforestry interventions to enhance land productivity<br />Vagen<br />Land Health - the capacity of land to sustain delivery of essential ecosystem services (the benefits people obtain from ecosystems)<br /><ul><li>Develop methods for evidenced-based management of land health – Land Health Surveillance
  2. 2. Apply methods to multi-scale targeting of sustainable land management & assessing intervention outcomes</li></ul>Thomas Gumbricht; Tor-Gunnar Vagen;JianchuXu;EmiasBetemariam; Andrew Sila; Spectral Lab Staff; Keith Shepherd<br />JeremiasMowo; Joy Turkihawa;AthanaseMukuralinda; ZacTchoundjeu; BertinTakoutsing; Christophe Kouame;<br />GudetaSileshi; Tracy Beedy; Pal Singh; Sonya Dewi; Ric Coe; AnjaGassner<br />
  3. 3. Surveillance Science Principles<br /><ul><li>Measurefrequency of problems and associated risk factors in populations using statistical sampling designs & standardized measurement protocols</li></ul>Assess association between problems and risk factors using statistical models<br />Rigorously evaluate interventionsusing experimental designs with controls<br />Meta-analysisis the primary information source for designing policy/programmes<br /><ul><li>Operational surveillance systems are built into everyday policy and practice</li></li></ul><li>Regional Spatial Information Systems<br />?<br />500 m<br />MODIS<br />Elevation<br />250 m<br />28.5 m<br />Vegetation<br />Landsat<br />Hydrology<br />15 m<br />Topographical <br />properties<br />ASTER<br />Climate<br />2.4 m<br />Cost surfaces, etc.<br />Quickbird<br />0.6 m<br />Legacy data<br />
  4. 4. Sentinel Site Surveillance Frameworka spatially stratified, hierarchical, randomized sampling framework<br />Sentinel site (100 km2)<br />16 Clusters (1 km2)<br />10 Plots (1000 m2)<br />4 Sub-Plots (100 m2)<br />
  5. 5. Soil-Plant Spectral Diagnostics<br /><ul><li>Spectral methods and decision support tools
  6. 6. Reference lab for AfSIS
  7. 7. Capacity building</li></li></ul><li>Scientific workflows<br />AfSIS IR spectral<br />prediction engine <br />
  8. 8. Digital mapping of land health<br />Automated reporting<br />Topsoil soil organic carbon (g kg-1) for Kipsing derived by statistical modelling of georeferenced soil carbon estimates to reflectance values from a QuickBird satellite image <br />
  9. 9.
  10. 10.
  11. 11. AfSISExternal Review<br />Pioneering unique effort<br /><ul><li>Pioneering effort intended to fill one of the major gaps in spatial information worldwide
  12. 12. Unique scientific effort never attempted before. Admirable first done in Africa.
  13. 13. Highly motivated team of creative scientists.
  14. 14. Well on track to deliver on its major goals</li></ul>Outstanding design & implementation<br /><ul><li>Well-documented, unique soil health surveillance methodology.
  15. 15. Outstanding design and implementation of field surveillance under very difficult conditions.
  16. 16. Sentinel sites will likely become long-term monitoring and research sites for many different purposes.</li></ul>Soil spectroscopy lab a pioneering facility / Excellent training of NARS<br /><ul><li>Systematic use of IR spectroscopy is groundbreaking in the world of soil testing.
  17. 17. The ICRAF soil spectroscopy lab is a pioneering facility and many experts are taking notice.
  18. 18. Great progress in building soil spectral libraries for functional interpretation.
  19. 19. Good, well-documented workflows and quality control protocols.
  20. 20. Excellent training of NARS collaborators provided by the ICRAF lab.
  21. 21. Excellent potential for digital soil mapping in Africa / Large spill over effects
  22. 22. Excellent potential to link the soil spectral analysis information with higher-resolution remote sensing data for digital soil mapping in Africa through automated mapping techniques.
  23. 23. Large spillover effects due to other projects and initiatives adopting the methodologies</li></li></ul><li>Land Health Out-scaling<br />Africa Soils Information Service<br />New Digital Soil Map of the World<br />Global Agricultural Monitoring System – Gates - CI<br />Regional Information Systems<br />Tibetan Plateau/ Mekong<br />Great Green Wall<br />National surveillance <br />systems<br />Rwanda, Ethiopia<br />Project baselines<br />Cocoa - CDI<br />Parklands Malawi<br />Rangelands E/W Africa<br />SLM Cameroon<br />MICCA EAfrica<br />
  24. 24. Tree Density Mapping at Fine Resolution<br />Map of tree density in an areas with steep climatic gradients in northern Kenya, derived from modelling ground data collected from sentinel sites to Landsat imagery (28.5 m resolution).<br />+ Mapping tree and land cover affected by plantation economy in Amazon, Congo, Mekong (Jianchu, Zac, Roberto)<br />+ Great Green Wall Baseline proposal (Gumbricht, Vagen, et al)<br />
  25. 25. Protocol for Measuring Soil Carbon in Landscapes<br />1988<br />2006<br />
  26. 26. Latin America – Amazon Information System<br />GIS datasets<br /><ul><li>Vector datasets (infrastructural, political, biophysical)</li></ul>Speciesoccurencedatabase<br /><ul><li>150,000 geo-referenced species occurrence records
  27. 27. 179 Agroforestry treespecies</li></ul>Downscaledclimatedata<br /><ul><li>Scenario SRES A1B
  28. 28. 5 GCMs (CNRM, CSIRO, ECHAM5, MIROC3)
  29. 29. 2030, 2050, 2080</li></ul>Satellite derived data<br /><ul><li>MODIS 1km² data(EVI, NDVI, LAI, FPAR, NPP etc.)
  30. 30. Cloud-free LANDSAT –Mosaics</li></ul>Empirical modelling<br />Predictions of species distribution and biome shifts under CC<br />High resolution species distribution <br />maps<br />Konstantin König – k.koenig@cgiar.org<br />
  31. 31. Modelling spread of plantation rubber and associated forest loss in Xishuangbanna, China<br />1988<br />2006<br />Environmental space occupied by rubber through time<br />
  32. 32. CRP5: Water, Land & Ecosystems<br />
  33. 33. Information Systems forLand, Water & Ecosystems<br />Vision<br />Natural resource and environmental policy and management decision making in agriculture and associated areas is increasingly based upon sound scientific evidence<br />Outcomes<br /><ul><li>A wide range of stakeholders have access to high quality spatial information and decision support systems on land and water resourcescondition/trends and intervention performance
  34. 34. Scientifically sound planning, implementation, and evaluation of land and water management policy and practice</li></li></ul><li>CRP5 Priority Basins<br />Africa Soil<br />Information<br />Service <br />
  35. 35. Agro-ecological Information SystemCRP5 Water, Land, Ecosystems<br />Strengthening water surveillance: (i) remote sensing of components of water balance; <br />(ii) standardized datasets of simulated water data at fine spatial resolution. Landscape genomics.<br />
  36. 36. ICRAF Geoinformatics Unit<br />The foundation of ICRAF’s research are trees as an object (what?) in space (where?) and time (when?) linked to function (so what?) and drivers (why/why not?), which makes quantifying local, national and global benefits of trees a multivariate spatio-temporal question.<br />From the extensive work with spatial data within GRP4, ICRAF launched a new Geoinformatics unit 1st June 2011.<br />The rationale for ICRAF to create a Geoinformatics unit is resting on the fact that the bottleneck for using spatial data is no longer data cost or availability, but rather lack of consistent and comprehensive processing, analysis, visualization, mining and dissemination methods. Hence the emphasis of the proposed strategy is on adopting and implementing scientific methods that are normally not used in combination, and to produce quality tagged spatial datasets that are then analyzed and visualized using state-of-the-art scientific methods.<br />
  37. 37. ICRAF Geoinformatics Unit<br />Initially the Geoinformatics unit will concentrate on developing service functions for ICRAF researchers, including:<br /><ul><li>Develop an open source based geo-catalogue of existing spatial data holdings
  38. 38. Develop a web-based interface for searching geospatial data
  39. 39. Develop a logical structure for a spatial data repository
  40. 40. Develop a web-interface allowing in-house access to a set of standard maps</li></ul>Further tasks include<br /><ul><li>Setting up a web map server allowing all users to generate customized maps
  41. 41. Creating a web-interfaced spatial relations modeling and hypothesis testing tool
  42. 42. Giving access to advanced in-house users to use a desk-top Geographical Information System (GIS) for analyzing the spatial data
  43. 43. Connecting the spatial data holdings and models to scientific workflows for automatic analysis of continental to global datasets.</li></li></ul><li>ICRAF Geoinformatics Unit<br />For those interested in the development of spatial data processing and access, the Geoinformatics unit will host three of the method breakout events on Tuesday and Wednesday.<br />A6. Geoinformatics 1. Monitoring vegetation annual phenology from time series of satellite imagery <br />B5. Geoinformatics 3. ICRAF online spatial data infrastructure - development of new web-tool for supporting research <br />C4. Geoinformatics 2. Automatic derivation of landscape biophysical characteristics from satellite images <br />

×