Post on 09-Jul-2020
Alfred Hartemink
(on behalf of the global consortium)
ISRIC – World Soil Information
Wageningen
GlobalSoilMap.net GlobalSoilMap.net a new digital soil map of the worlda new digital soil map of the world
The use of soil informationThe use of soil information
GlobalSoilMap.netGlobalSoilMap.net
A digital soil map of the worldA digital soil map of the world
Aspect 1 Aspect 1 ––
Capture and Capture and CapitaliseCapitalise
Soil mapsSoil maps Soil samplesSoil samples
Reports, literatureReports, literature Soil data and informationSoil data and information
Aspect 2 Aspect 2 ––
Soil propertiesSoil properties
(not yet classes)(not yet classes)
Key properties
1. Organic Carbon (g/kg)
2. Sand
(%), Silt
(%), Clay
(%) & coarse fragments
(%)
3. pH
4. Depth
to bedrock or restricting layer (m)
From these attributes, the following two properties
will be predicted using pedo‐transfer functions:
5. Bulk Density
(kg/m3)
6. Available Water Capacity
(given in mm/m)
Optional:
7. ECEC
(Cations plus exchangeable acidity mol/kg)
8. EC
(Electrical conductivity dS/m)
0 ‐
5 cm
5 – 15 cm
15 – 30 cm
30 – 60 cm
60‐100 cm
100‐200 cm
Effective depth
Aspect 3 Aspect 3 ––
Showing UncertaintiesShowing UncertaintiesAWC (mm)
10- 1111 - 1212 - 1313 - 1414 - 1515 - 1616 - 1717 - 1818 - 19> 19
Standard errors
0.00 - 0.25
0.25 - 0.50
0.50 - 0.75
0.75 - 1.00
1.00 - 1.50
1.50 - 2.00
2.00 - 2.50
2.50 - 3.00
3.00 - 4.00
> 4.00
Variability of OC at selected across the Edgeroi study area.
0‐5cm
Lower
prediction
limit
30‐60cm
60‐100cm
Upper
prediction
limit
DSM
prediction
Aspect 4 Aspect 4 ––
Fine resolution grid 90 by 90 mFine resolution grid 90 by 90 m
From the polygon to the grid
0 ‐
5 cm
5 – 15 cm
15 – 30 cm
30 – 60 cm
60‐100 cm
100‐200 cm
Effective depth
Aspect 4 Aspect 4 ––
Fine resolution grid 90 by 90 mFine resolution grid 90 by 90 m
Which soil data are available?
Detailed soil mapswith legends
-Spatially weighted mean-Spatial disaggregation
Extrapolation fromreference areasSpatially weighted mean
Full Cover? Homosoil
Detailed soil maps with legendsand Soil Point data
Soil Point data Almost no data
NoYes
scorpankriging
Soil maps:-Spatially weighted mean-Spatial disaggregationSoil data:- scorpan kriging
Extrapolation fromreference areas:-Soil maps-Soil point data
Full Cover?
No Yes
Assign quality of soil data and coverage in the covariate space
Time
Initially a legacy based approach
PredictionsPredictions
Lithology
Soil
observations or
maps
with
legends
DEM
Climate
Existing
Soil
maps
scorpan
layers
Landcover
Sp
= f
(s,c,o,r,p,a,n) + e
f
‐
Linear
regression,
Regression
trees,
Random
forests,
Neural networks,Expert systemEtc..
Krige
residuals
(e)
Inferred
property
e.g.,
AWC
pH
CEC
Organic
C
Bulk
density
Clay
Sand
‘Modal’
profile
Fit mass‐
preserving
spline
Spline
averages at
specified
depth
ranges
Estimate averages
for spline at
standardised
depth
ranges
Fitted Spline
The spline
layer Soil C prediction
0‐5 cm 5‐15 cm 15‐30 cm
30‐60 cm 60‐100 cm 100‐200 cm
Reconstruct splines at every pixel
Carbon (%) 0-5cmHigh : 6.5 Low : 0.8
1
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11 task groups1.Specifications
2. Soil profile and map legacy data
3. Covariates
4. New Prediction Method Development
5. Application & Documentation of Existing Methods
6. Soil Information Model
7. Cyber‐Infrastructure
8. End‐user Engagement
9. Uncertainty and Accuracy
10. Operational production mapping
11. Global stratification (pedoecophysiographic)
Aspect 5 Aspect 5 ––
ItIt’’s a global projects a global project
North America
LatinAmerica/Caribbean
Eurasia
Africa
East Asia
Oceania
SouthAsia
North Africa/West Asia
Jordan
Start up in December 2006Start up in December 2006
The African launchThe African launch
1313thth
Jan 2009Jan 2009
The Global launch
17th
Feb 2009
"Let there be no mistake
about the significance of
this wonderful project"
Kofi Annan
"Soil mapping is one of the
pillars to the challenge of
sustainable development"
Jeffrey Sachs
Large differences
USA
Sub Sahara Africa
9.1 million km2
23.9 million km2
35,000 soil profiles
4,057 soil profiles
ThatThat’’s currently available !s currently available !
Progress –
Scientific Publications
2006
20072008
2010
Activities in the node – East Asia
Activities in the node – East AsiaProof‐of‐concept studies with voluntary source. 90m resolution maps are
being tested in the pilot areas
>0.05mm <0.001mm <0.01mm
Activities in the node – North America
Hired two post‐docs
Will produce soil property information.
Training workshops
Work closely with Canada and Mexico
Produced 30 m resolution
soil carbon map (1 m depth)
using spatially weighted
mean calculations from
SSURGO and STASGO
Information
Activities in the node – L AmericaLaunch at Seventeenth Latin American
Congress of Soil Science
Node established
Identify country coordinators
Technical meetings planned for March
Translation some standards texts in
Spanish
Plan training and capacity building
Activities in the node – L America
Activities in the node – OceaniaGood connections Australia – Indonesia –
New Zealand
Neil McKenzie, Mike Grundy, Peter
Wilson, David Jacquier, Budi Minasny,
Brendan Malone and John Gallant met in
Canberra to discuss scientific issues,
including proof of concept areas, and
developing the Oceania node.
Meetings in New Zealand, and Indonesia
with follow ups in Australia are planned.
There will be data from Australia
forthcoming for proof of concept studiesIndonesian Soil Science Society Conference 20-22 November 2009 in Yogyakarta
Activities in the node – Oceania
Agreed specifications: 90 m , the spline (six depth layers) and uncertainty. Figured out how to convert ASRIS coverage to a
90 m raster with depth data and uncertainty. Increased complexity the way forward, not
multi‐resolution,
From R. Viscarra Rossell
(CSIRO) From B. Malone et al. (Geoderma, 2009)
Some conclusions
Importance of soils and soil information is recognised in big
global issues (climate change, food production, environmental degradation,
biodiversity, water scarcity, land disputes and war)
Increasingly recognised:
soils are not the problem
but part of the solution
Increased demand for soil information by other scientific
disciplines, policy and society
Demand for raster based soil properties with uncertainties
Coincides with a quantum leap in technology to produce
accurate soil information in a timely manner
Enormous opportunities for soil science, and also for a new
generation to get engaged
Some conclusions
Thank you for your attentionThank you for your attention
Alfred Hartemink
(on behalf of the global consortium)
ISRIC – World Soil Information
Wageningen