http://www.fao.org/globalsoilpartnership This presentation was made during the GSP/E-SOTER Global Soil Information workshop that took place at the FAO HQ, Rome , Italy from 20-23 March 2012. This presentation was made on the third day, and it presents Global Soil Spectral Library. ©FAO: http://www.fao.org

1. Global Soil Spectral Library
World Agroforestry Centre (ICRAF) & ISRIC
A global reference, spectral library and conversion
database for harmonization of legacy soil data for the
GlobalSoilMap.net project
Towards Global Soil Information: activities within the GEO Task
Global Soil Data, FAO, Rome, 19 – 23 March 2012

2. Rationale
• GlobalSoilMap.net largely based on making effective use of legacy soils
data.
• Legacy soil data consists of field observations, laboratory analyses and
conventional soil maps collected over the last 60-80 years as part of
numerous national, regional and institutional soil survey programs.
• Much of this legacy soils data is fragmented, non-standard between
countries and often even within countries.
• Difficult to share or exchange data across national, state or even project
borders because of significant differences in standards, methods of analysis,
definitions and legends.
• Need for soil data to be harmonized to a single consistent reference method
in order to be comparable globally and suitable for use in producing global
maps and databases.
• In addition soil infrared spectroscopy and proximal sensing methods
increasingly used for estimating soil properties, but as yet no comprehensive
global calibration libraries exists (Viscarra Rossel, 2009; Terhoeven et al.,

3. Project Objectives
1. Design and populate a global soil property and spectral
reference library
 Full range of soil types & environmental settings
on each continent or node (500 profiles per node)
 Sample from each horizon analysed using
commonly used methods for each soil property
2. Provide inter-method calibrations
1. Provide infrared spectral calibrations
1. Maintain and further build the reference library

4. Infrared Spectroscopy for rapid soil
characterization
• Rapid
• Low cost
• Reproducible
•Predicts many soil
functional
properties

5. What soil properties affect spectral
shape?
These are the key determinants of soil functional properties:
nutrient supply & retention; carbon sequestration; hydraulic properties;
erodibility; tillage & engineering properties

6. www.africasoils.net
Randomization of Sentinel Site
locations stratified by climate
zone
African Soil Information
Service

7. AfricaSoils Sentinel
Site based on the Land
Degradation Surveillance
Framework
a spatially stratified, hierarchical,
rand
omized sampling framework
Sentinel site (100 km2)
16 Clusters (1 km2)
10 Plots (1000 m2)
4 Sub-Plots (100 m2)

8. ?
Cost surfaces, etc.
Covariates
Remote 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

9. Local(site-level)Cref
High resolution digital mapping
10 km

10. RegionalCref
160 km
Regional mapping

11. Instrumentation
Dispersive VNIR FT-NIR FT-MIR Handheld NIR/MIR
•Portable
•Repeatability?
•External service
•No validation
•Benchtop
•Repeatability ***
•Self serviceable
•Validation in-built
•ISO compliant
•Industry proven
•Multipurpose
•Benchtop
•Repeatability***
•No gas purging
•Some servicing
•Robotic
•Validation in-built
•ISO compliant
•Outperforms NIR
•Handheld
•Sample
homogeneity?
•Variable
moisture?
•Repeatability?
•Still expensive
•Rapidly
developing
•Need to prepare
by developing
soil reference
libraries

12. Current global spectral library initiatives
• Soil Spectroscopy Group
(Geophysical Research Abstracts, Vol. 11, EGU2009-14021, 2009; NIR News 2009 doi:
10.1255/nirn.1131)
• global soil spectral library (VNIR)
• community of practice for soil spectroscopy
BEN DOR, Eyal - Tel Aviv University; BROWN, David - Washington State University; DEMATTE, Alexandre - Sao
Paolo University; SHEPHERD, Keith – ICRAF; STENBERG, Bosse - Swedish Agricultural University; VISCARRA
ROSSEL*, Raphael – CSIRO Land & Water
• Brown et al 2006: VNIR spectra from NSSC archives: 3768 samples
from all 50 U.S. states and two tropical territories and an additional
416 samples from 36 different countries in Africa (125), Asia (104),
the Americas (75) and Europe (112)
• Terhoeven-Urselmans et al 2010: MIR spectra from ISRIC archives:
4438 soil samples from 754 soil profiles (56 countries) but only 971
samples from 18 countries with complete data

13. ISRIC global spectral library
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
Results for
30%
independent
validation set

14. 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
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

15. Africa Soil Information Service
Spectral library
Prediction performance for soil physical properties and total carbon and nitrogen
using mid-infrared spectroscopy for sentinel sites analysed to date.
Validation results are for a 50% random hold-out sample using boosted regression
trees.

16. Spectral calibration transfer
Robotoic high throughput
MIR (Shepherd & Walsh, 2007)

17. Current global spectral library limitations
• Soil spectral calibrations limited by quality and
consistency of the reference data
• Large libraries needed to cover the global range in soil
conditions
• Need to include a number spectral instrument types
(VNIR, NIR, MIR)
A viable library will be based on conducting new reference
measures in one laboratory with excellent quality control

18. Proposed plan
• Phase 1 (6 months): Scoping, evaluation, feasibility
assessment
• Survey available profiles; additional sampling?
• Export/import procedures; shipping
• Suite of methods to be used
• Analytical lab for spectral and reference methods
• Cost analysis
• Full proposal development
• Phase 2 (3 years): Sampling and analysis
• Full implementation
• Global database made available