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 HealthWorld Agroforestry Centre (ICRAF)
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
Reliable data on land and soil functional properties
The things we really want to know about land and soil
Nutrient supply and retentionWater infiltration and storageAbility to resist erosionCarbon stocks and sequestration potentialTillage and engineering properties
Woody coverWildlife habitatHydrological functioning
Land health surveillance
AfricaSoils.net
Randomization of Sentinel Site locations stratified by climate
African Soil Information
Service
AfricaSoils Sentinel Site based on the Land Degradation
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)
Infrared Spectroscopy for rapid soil characterization
• Rapid
• Low cost
• Reproducible
• Predicts many soil functional properties
Soil IR fundamentals
1 = Fingerprint region e.g Si-O-Si stretching/bending2 = Double-bond region (e.g. C=O, C=C, C=N3 = Triple bond (e.g. C C, C N)≡ ≡4 = X–H stretching (e.g. O–H stretching)NIR = Overtones; key features clay lattice and water OH; SOM affects overall shape
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Cost surfaces, etc.
CovariatesRemote Sensing (RS) and Spatial Data
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
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
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 550Δ
Spectral signatures respond to management-induced changes in soil functional properties
NARL long-term experiment, Kenya
Spectral differences in SOC quality in aggregates
Verchot, L.V., Dutaur, L., Shepherd, K.D., Albrecht, A. 2011. Organic matter stabilization in soil aggregates: Understanding the biogeochemical mechanisms that determine the fate of carbon inputs in soils. Geoderma 161: 182–193.
Microaggregates had similar spectra despite large texture differences
Luero 35% sandTeso 76% sand
The meso- and macro- aggregates, and macro-aggregates were enriched in carboxylic-C and aromatic-C, indicating the importance of OM decomposition and plant-derived C in the stabilization of larger aggregates.
• Vibrations of H-bonded hydroxyl O-H in phenols • Asymmetric and symmetric aliphatic-C CH3 and CH2
stretching.• C = O stretching of carboxyl and ketones• Aromatic C = C conjugated with C = O and/or COO-
Aliphatic C–H deformation of CH2 or CH3 groups • C-O stretching of polysaccharide
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.
ResultsResults ((
Mineral Semi-quant (%)
QuartzMontmorilloniteMicroclineKaoliniteHematiteIlmeniteGibbsite
76.94.03.210.22.92.00.8
Quantitative x-ray diffraction spectroscopy
ResultsResults ((Spectral applications in long-term trials• Increase sample density (IR interpolation)
• Time series samples?• Interpret treatment effects on SOC functional groups (IR)
•Develop generalizable spectral indices of across-site and management-induced soil quality
•Examine treatment effects on aggregate stability (LDPSA)
•Characterize sites in tems of: spectral similarity (IR); mineralogical analysis (XRD); AfSIS population sample (IR, reference measures)