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
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 />
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 />
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 />
Well on track to deliver on its major goals</li></ul>Outstanding design & implementation<br /><ul><li>Well-documented, unique soil health surveillance methodology.
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 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.
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 soil mapping in Africa through automated mapping techniques.
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 />
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 />
Protocol for Measuring Soil Carbon in Landscapes<br />1988<br />2006<br />
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
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 – firstname.lastname@example.org<br />
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 />
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
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 />
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 />
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 />
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
Develop a web-based interface for searching geospatial data
Develop a logical structure for a spatial data repository
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
Creating a web-interfaced spatial relations modeling and hypothesis testing tool
Giving access to advanced in-house users to use a desk-top Geographical Information System (GIS) for analyzing the spatial data
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 />