land health surveillance highlights

2. Apply methods to multi-scale targeting of sustainable land management & assessing intervention outcomesThomas Gumbricht; Tor-Gunnar Vagen;JianchuXu;EmiasBetemariam; Andrew Sila; Spectral Lab Staff; Keith Shepherd JeremiasMowo; Joy Turkihawa;AthanaseMukuralinda; ZacTchoundjeu; BertinTakoutsing; Christophe Kouame; GudetaSileshi; Tracy Beedy; Pal Singh; Sonya Dewi; Ric Coe; AnjaGassner

4. Sentinel Site Surveillance Frameworka spatially stratified, hierarchical, randomized sampling framework Sentinel site (100 km2) 16 Clusters (1 km2) 10 Plots (1000 m2) 4 Sub-Plots (100 m2)

6. Reference lab for AfSIS

8. Digital mapping of land health Automated reporting 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

12. Unique scientific effort never attempted before. Admirable first done in Africa.

13. Highly motivated team of creative scientists.

15. Outstanding design and implementation of field surveillance under very difficult conditions.

17. The ICRAF soil spectroscopy lab is a pioneering facility and many experts are taking notice.

18. Great progress in building soil spectral libraries for functional interpretation.

19. Good, well-documented workflows and quality control protocols.

20. Excellent training of NARS collaborators provided by the ICRAF lab.

21. Excellent potential for digital soil mapping in Africa / Large spill over effects

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.

24. Tree Density Mapping at Fine Resolution 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). + Mapping tree and land cover affected by plantation economy in Amazon, Congo, Mekong (Jianchu, Zac, Roberto) + Great Green Wall Baseline proposal (Gumbricht, Vagen, et al)

25. Protocol for Measuring Soil Carbon in Landscapes 1988 2006

28. 5 GCMs (CNRM, CSIRO, ECHAM5, MIROC3)

30. Cloud-free LANDSAT –MosaicsEmpirical modelling Predictions of species distribution and biome shifts under CC High resolution species distribution maps Konstantin König – k.koenig@cgiar.org

31. Modelling spread of plantation rubber and associated forest loss in Xishuangbanna, China 1988 2006 Environmental space occupied by rubber through time

32. CRP5: Water, Land & Ecosystems

35. Agro-ecological Information SystemCRP5 Water, Land, Ecosystems Strengthening water surveillance: (i) remote sensing of components of water balance; (ii) standardized datasets of simulated water data at fine spatial resolution. Landscape genomics.

36. ICRAF Geoinformatics Unit 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. From the extensive work with spatial data within GRP4, ICRAF launched a new Geoinformatics unit 1st June 2011. 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.

38. Develop a web-based interface for searching geospatial data

39. Develop a logical structure for a spatial data repository

41. Creating a web-interfaced spatial relations modeling and hypothesis testing tool

42. Giving access to advanced in-house users to use a desk-top Geographical Information System (GIS) for analyzing the spatial data