Soil Spectroscopy in the Africa Soil Information Service

Transcription

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

2 Surveillance Science Measure frequency of problems and associated risk factors in populations using statistical sampling designs & standardized measurement protocols UNEP Land Health Surveillance: An Evidence- Based Approach to Land Ecosystem Management. Develop screening test(s) Infrared spectroscopy Identify problem Develop case defintition Measure prevalence (no. cases/area) Measure incidence (no. cases/area/time) Measure environmental correlates Differentiate risk factors Illustrated with a Case Study in the West Africa Sahel. United Nations Environment Programme, Nairobi. ort_lowres.pdf 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: Confirm risk factors

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

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:

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: 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: Terhoeven-Urselmans T, Vagen T-G, Spaargaren O, Shepherd KD Prediction of soil fertility properties from a globally distributed soil mid-infrared spectral library. Soil Sci. Soc. Am. J. 74:

8 Infrared spectroscopy Spectral fingerprinting Total X-ray fluorescence spectroscopy X-ray diffraction spectroscopy Mineral Semiquant (%) Quartz Albite Microcline Kaolinite Hematite Muscovite Diopside

9 Laser diffraction particle size analysis

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

11 Markus Walsh, AfSIS Africa Soil Information Service

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 Global-Continental Monitoring Systems Vital signs CRP pan-tropical sites AfSIS Regional Information Systems Tibetan Plateau/ Mekong Evergreen Ag / Horn of Africa National surveillance systems EthioSis SLM Cameroon Parklands Malawi Project baselines Rangelands E/W Africa Cocoa - CDI MICCA EAfrica

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