1. Land Health Surveillance Harnessing science and technology to provide Reliable, comparable, and locally relevant information on land health status, risks and intervention outcomes Global Research Project 4: Land Health World Agroforestry Centre (ICRAF)
2. Land Health The capacity of land to sustain delivery of essential ecosystem services (the benefits people obtain from ecosystems) Widespread degradation is reducing productivity, impeding development , damaging the environment
5. AfricaSoils Sentinel Site based on the L and D egradation S urveillance F ramework a spatially stratified, h i e r a r c h i c a l , r a n d o mized sampling framework Sentinel site (100 km 2 ) 16 Clusters (1 km 2 ) 10 Plots (1000 m 2 ) 4 Sub-Plots (100 m 2 )
12. Covariates Remote Sensing (RS) and Spatial Data Cost surfaces, etc. Elevation Vegetation Hydrology Topographical properties Climate Landsat Legacy data ASTER Quickbird MODIS 500 m 250 m 28.5 m 15 m 2.4 m 0.6 m ?
15. Spectral prediction of TOC, POC, Charcoal-C Australian and Kenya soils Janik LJ, Skjemstad JO, Shepherd KD and Spouncer LR (2007) The prediction of soil carbon fractions using mid-infrared-partial least square analysis. Journal of Australian Soil Research 45(2): 73–81. TOC : alkyl –CH2 stretching modes; carbohydrate overtones of the –COH stretch; carboxylic acid –COOH; amide I and II bands; alkyl –CH2 deformation; aromatic –CH in plane deformation; carbohydrate–COH stretch. CHAR : C=C skeletal vibrations; phenolic , or COO stretching vibrations; ring C–H in plane deformations
16. Spectral prediction of SOC in global alfisols Kamau-Rewe, M., Rasche, F., Cobo, J.G., Dercon, G., Shepherd, K.D., Cadisch, G. (2011). Generic prediction of soil organic carbon in Alfisols using diffuse reflectance Fourier transformed mid-infrared spectroscopy. Soil Science Society of America Journal 75: 2358–2360. Not treated (NT) and with mineral signature subtracted Δ550
19. Spectral prediction of C mineralization rates in SOC fractions Mutuo PK, Shepherd KD, Albrecht A, and Cadisch G (2006) Prediction of Carbon Mineralization Rates from Different Soil Physical Fractions Using Diffuse Reflectance Spectroscopy. Soil Biology & Biochemistry 38:1658–1664.
23. Results ( Characterise sites relative to AfSIS population
Hinweis der Redaktion
Third, use of infrared spectroscopy for rapid soil characterization. Using only light, this a rapid, low cost and high reproducible methods, which can predict not only carbon but a number of other soil functional properties.