[WG1] Soil Monitoring for Mankind and Environment Safety 20th World Congress of Soil Science, 8 – 13 June 2014, Jeju, Korea

1. Soil Spectroscopy in the Africa Soil
Information Service
Getting the best out of light
[WG1] Soil Monitoring for Mankind and Environment Safety
20th World Congress of Soil Science, 8 – 13 June 2014, Jeju, Korea
Keith D Shepherd, Land Health Decisions
World Agroforestry Centre (ICRAF), Nairobi, Kenya
Earth Institute, Columbia University (adjunct)

2. Surveillance Science
• Measure frequency of problems and associated risk factors in
populations using statistical sampling designs & standardized
measurement protocols
UNEP. 2012. Land Health Surveillance: An Evidence-
Based Approach to Land Ecosystem Management.
Illustrated with a Case Study in the West Africa
Sahel. United Nations Environment Programme,
Nairobi.
http://www.unep.org/dewa/Portals/67/pdf/LHS_Rep
ort_lowres.pdf
Identify problem
Develop case
defintition
Develop
screening test(s)
Measure prevalence
(no. cases/area)
Measure incidence
(no. cases/area/time)
Confirm risk factors
Measure
environmental
correlates
Differentiate risk
factors
Infrared
spectroscopy
Shepherd KD and Walsh MG (2007) Infrared
spectroscopy—enabling an evidence-based
diagnostic surveillance approach to agricultural
and environmental management in developing
countries. Journal of Near Infrared Spectroscopy
15: 1-19.

3. Africa Soil
Information Service
Consistent field
protocol
Soil spectroscopy
Coupling with
remote sensingPrevalence, Risk factors, Digital
Sentinel sites
Randomized sampling schemes

4. Data & soil library management
Barcoding
Soil archiving system
1.2 km shelving holds over 40 t of soil

5. Spectral shape relates to basic soil properties
• Mineral composition
• Iron oxides
• Organic matter
• Water (hydration,
hygroscopic, free)
• Carbonates
• Soluble salts
• Particle size distribution
 Functional properties

6. Field spectroscopy
Shepherd KD and Walsh MG. (2002) Development of
reflectance spectral libraries for characterization of
soil properties. Soil Science Society of America
Journal 66:988-998.

7. Infrared spectroscopy
Dispersive VNIR FT-NIR FT-MIR Robotic FT-MIR Portable
Handheld MIR Mobile phone devices
Brown D, Shepherd KD, Walsh MG (2006). Global soil
characterization using a VNIR diffuse reflectance library
and boosted regression trees. Geoderma 132:273–290.
Shepherd KD and Walsh MG (2007) Infrared
spectroscopy—enabling an evidence-based diagnostic
surveillance approach to agricultural and environmental
management in developing countries. Journal of Near
Infrared Spectroscopy 15: 1-19.
Terhoeven-Urselmans T, Vagen T-G, Spaargaren O,
Shepherd KD. 2010. Prediction of soil fertility properties
from a globally distributed soil mid-infrared spectral
library. Soil Sci. Soc. Am. J. 74:1792–1799

8. Spectral fingerprinting
Total X-ray fluorescence
spectroscopy
X-ray diffraction
spectroscopy
Mineral Semi-
quant
(%)
Quartz
Albite
Microcline
Kaolinite
Hematite
Muscovite
Diopside
69.2
5.0
4.3
9.9
2.8
4.3
4.6
Infrared spectroscopy

9. Laser diffraction
particle size analysis

10. Main AfSIS workflow, products & services overview
Markus Walsh, AfSIS

11. Markus Walsh, AfSIS
Africa Soil
Information Service
www.africasoils.net

12. On-line Spectral Prediction Engine
Bayesian Additive Regression Trees
Jiehua Chen & William Wu
Columbia University

13. On-line Spectral Prediction Engine
Bayesian Additive Regression Trees

14. Africa Spectral Lab Network
•IAMM, Mozambique
•AfSIS, Sotuba, Mali
•AfSIS, Salien, Tanzania
•AfSIS, Chitedze, Malawi
•CNLS, Nairobi, Kenya
•CNRA, Abidjan, Cote D’Ivoire
•KARI, Nairobi, Kenya
•ICRAF, Yaounde, Cameroon
•Obafemi Awolowo University,
Ibadan, Nigeria
•IAR, Zaria, Nigeria
•ATA, Addis Ababa, Ethiopia (6)
•IITA, Ibadan, Nigeria
•IITA, Yaounde, Cameroon
•IER, Arusha, Tanzania
•FMARD, Nigeria
•CNLS, Nairobi, Kenya
•BLGG, Kenya (mobile)

15. Land Health
Surveillance
Out-scaling
Tibetan Plateau/ Mekong
Vital signs
Cocoa - CDIParklands Malawi
National surveillance
systems
Regional Information Systems
Project baselines
EthioSis
Rangelands E/W AfricaSLM Cameroon MICCA EAfrica
Global-Continental Monitoring Systems
Evergreen Ag / Horn of Africa
CRP pan-tropical sites
AfSIS

16. Futures
• Capacity building
• Spatial-spectral prediction of soil properties
• Direct prediction of management response
• Low cost mobile devices