Upload
tomislav-hengl
View
841
Download
2
Tags:
Embed Size (px)
DESCRIPTION
Seminar at the Columbia University, Lamont Campus, New York
Citation preview
Global Soil Information Facilities
(A methodological framework for Open Soil
Information)
Tomislav Hengl
ISRIC � World Soil Information, Wageningen University
Seminar at CIESIN, Sept 14 2011
Key issues
I What do we know about world soils?
I What do you know about the GlobalSoilMap.net project?
I How to produce complete GlobalSoilMape.net propertymaps?
I How will soil information �t into the Global LandInformation System?
Seminar at CIESIN, Sept 14 2011
My backgrounds
I Senior researcher at ISRIC � World Soil Information;
I PhD in pedometric mapping @ ITC (GIS institute in Enschede)in 2003;
I 2 years university assistant; 2.5 years JRC Ispra; 2 yearsUniversity of Amsterdam;
I My expertise: Geostatistics, Digital Soil Mapping, spatialdata analysis, geomorphometry (vice-chair);
I Global Soil Information Facilities
Seminar at CIESIN, Sept 14 2011
My publications
Seminar at CIESIN, Sept 14 2011
What am I doing in USA?
Seminar at CIESIN, Sept 14 2011
AfricaSoils.net
Thank you!
1. Markus Walsh (Keith Shepherd)
2. Sonya Ahamed & Pedro Sanchez
Seminar at CIESIN, Sept 14 2011
My main inspirations / principles of work
I Open Source software for education and research
I Crowd sourcing systems for environmental datacollection
I Publicly accessible (soil) data products
Seminar at CIESIN, Sept 14 2011
Important assumptions
My research philosophy
is based on 4 important assumptions:
Seminar at CIESIN, Sept 14 2011
Assumption #1
Humans (companies and governments)
need to be closely monitored
Seminar at CIESIN, Sept 14 2011
Did you know?
I Global biodiversity has been heavily degraded due to humanactivities. The Living planet index has dropped from 1970sto 60% and will continue to do so (source: MillenniumAssessment project).
I By 2048 we will run out of �sh (your children will leave on aplanet where there are hardly any visible �sh in the oceans).
I 15-35% of global irrigation withdrawals are estimated to beunsustainable (source: WBCSD).
I Every year, 9.4 million ha of forests are lost (source: FAO�World agriculture: towards 2015/2030�).
Seminar at CIESIN, Sept 14 2011
Population trends
Seminar at CIESIN, Sept 14 2011
Decline of species (biodiversity)
Seminar at CIESIN, Sept 14 2011
Forests and croplands
Seminar at CIESIN, Sept 14 2011
Assumption #2
Soils (and hence information on soils)
will become more and more important
Seminar at CIESIN, Sept 14 2011
Food price index (FAO)
Seminar at CIESIN, Sept 14 2011
Soil threats
Soils are also more important because we are slowly loosing them:
I 305 million ha of land has been completely degraded (nolonger suitable for agriculture).
I 10-50% irrigated land a�ected by salinization (source:GLASOD).
I For a forest to return takes maybe 100 years; it takes100�400 years to produce 1 cm of topsoil � are soilsrenewable resource at all?
Seminar at CIESIN, Sept 14 2011
Soils might become precious in future
Reports by FAO (2002) show that, in future, 80 percent ofincreased crop production in developing countries will have to comefrom intensi�cation � higher yields, increased multiple croppingand shorter fallow periods.Any agricultural or environmental management modelrequires soil data as an input to estimation of yields, waterand nutrient dynamics.World demand for cereals has jumped from 39 million tones (in1970) to 103 million tones (in 2000) (source: FAO �Worldagriculture: towards 2015/2030�).
Seminar at CIESIN, Sept 14 2011
Assumption #3
Soil Information (global)
is one of the poorest GIS layers
Seminar at CIESIN, Sept 14 2011
What do we know about world soils?
I Harmonized World Soil Database: 1 km resolution griddedsoil property maps (16 properties for top and sub-surface soil).
I 1:5M scale FAO-UNESCO Soil Map of the Word: fromwhich ISRIC has produced 5 by 5 arc-minutes global soilproperty maps (for 0�20, 20�40, 40�60, 60�80 and80�100 cm) in combination with the ISRIC-WISE soil pro�ledatabase.
I The Distributed Active Archive Center (DAAC) soilproperty maps
I USGS-produced soil property maps
I Atlas of the Biosphere soil maps
Seminar at CIESIN, Sept 14 2011
HWSD vs GlobCov
GlobCover HWSD
Seminar at CIESIN, Sept 14 2011
Should soils follow political boundaries?
Seminar at CIESIN, Sept 14 2011
HWSD vs ISRIC SIS (753 pro�les)
Seminar at CIESIN, Sept 14 2011
The agreement plot (kappa <10%)
Seminar at CIESIN, Sept 14 2011
Assumption #4
Global Resource Planning System
can do much better than a local one
Seminar at CIESIN, Sept 14 2011
GLIS
GLOBAL
LAND INFORMATION
SYSTEM
Soil properties (soil information system)
- physical and chemical soil properties, nutrient
capacity, water storage, acidity/salinity…
Live weather channel (meteorological forecasting)
- anticipated temperature (min, max), rainfall, frost
hazard, drought hazard, flood hazard…
Plant monitoring channel (MODIS/ENVISAT)
- current biomass production, biomass anomalies
(pest and diseases), plant health…
Socio-economic data (site-specific)
- administrative units, new laws and regulations,
market activity, closest offices, agro-dealers…
Spatial location (site)
Query site
attributes
Information
incorrect?Update with
ground truth data
Fertilization
Irrigation
Pest treatment
Best crop calendar
Yield estimates
Environmental risks
Suggest the best
land use practice
Model library
Seminar at CIESIN, Sept 14 2011
GRMS (see �Zeitgeist moving forward� 1:34h)
Seminar at CIESIN, Sept 14 2011
GlobalSoilMap.net
I An international initiative to make soil property maps (7+3) atsix depths at 3 arcsecs (100 m).
I the leitmotif is to �assemble, collate, and rescue as much of
the worlds existing soil data� ;
I The soil-equivalent of the OneGeology.org, GBIF, GlobCoverand similar projects.
I The biggest DSM project ever!
Seminar at CIESIN, Sept 14 2011
GlobalSoilMap.net in comparison with other projects
SRTM GADM
1990 1995 2000 2005 2010 2015 2020
2.0
2.5
3.0
3.5
4.0
Year
Re
so
lutio
n (
m)
in lo
g-s
ca
le
GPWv3
MOD13C2
MOD12C1
CHLO/SST
GLWD
DMSP-OLSv4
WorldClim
GlobCov2
FRA
5.6 km
HWSDv1EcoRegions
GlobalSoilMap?
OneGeology?
Seminar at CIESIN, Sept 14 2011
World soils in numbers
I Total land area: 14.8 billion ha
I Estimated total productive soil area: 10.9 billion ha (73.6%)
I Drylands (deserts, semi-deserts): 3.6 billion ha (24.3%)
I Wetlands (swamps, marshes, and bogs): 440 million ha (3%)
I Arable and permanent crops: 1.5 billion ha (11%)
I Potential areas suitable in varying degrees for the rainfedproduction of arable and permanent crops: 2.8 billion ha
Seminar at CIESIN, Sept 14 2011
Global Soil Mapping (in numbers)
I The total productive soil areas: about 104 million squarekm.
I To map the world at 100 m (1:200k), would cost about5 billion EUR (0.5 EUR per ha) using traditional methods.
I We would require some 65M pro�les according to the strictrules of Avery (1987).
I World map at 0.008333333 arcdegrees (ca.1 km) resolution isan image of size 43,200Ö21,600 pixels.
I 27 billion pixels needed to represent the whole world in100 m (productive soil areas).
Seminar at CIESIN, Sept 14 2011
Global Soil Mapping (in numbers)
I The total productive soil areas: about 104 million squarekm.
I To map the world at 100 m (1:200k), would cost about5 billion EUR (0.5 EUR per ha) using traditional methods.
I We would require some 65M pro�les according to the strictrules of Avery (1987).
I World map at 0.008333333 arcdegrees (ca.1 km) resolution isan image of size 43,200Ö21,600 pixels.
I 27 billion pixels needed to represent the whole world in100 m (productive soil areas).
Seminar at CIESIN, Sept 14 2011
Global Soil Mapping (in numbers)
I The total productive soil areas: about 104 million squarekm.
I To map the world at 100 m (1:200k), would cost about5 billion EUR (0.5 EUR per ha) using traditional methods.
I We would require some 65M pro�les according to the strictrules of Avery (1987).
I World map at 0.008333333 arcdegrees (ca.1 km) resolution isan image of size 43,200Ö21,600 pixels.
I 27 billion pixels needed to represent the whole world in100 m (productive soil areas).
Seminar at CIESIN, Sept 14 2011
Global Soil Mapping (in numbers)
I The total productive soil areas: about 104 million squarekm.
I To map the world at 100 m (1:200k), would cost about5 billion EUR (0.5 EUR per ha) using traditional methods.
I We would require some 65M pro�les according to the strictrules of Avery (1987).
I World map at 0.008333333 arcdegrees (ca.1 km) resolution isan image of size 43,200Ö21,600 pixels.
I 27 billion pixels needed to represent the whole world in100 m (productive soil areas).
Seminar at CIESIN, Sept 14 2011
Global Soil Mapping (in numbers)
I The total productive soil areas: about 104 million squarekm.
I To map the world at 100 m (1:200k), would cost about5 billion EUR (0.5 EUR per ha) using traditional methods.
I We would require some 65M pro�les according to the strictrules of Avery (1987).
I World map at 0.008333333 arcdegrees (ca.1 km) resolution isan image of size 43,200Ö21,600 pixels.
I 27 billion pixels needed to represent the whole world in100 m (productive soil areas).
Seminar at CIESIN, Sept 14 2011
Productive soil areas
Figure: Soil productive area mask derived using the MODIS LAI images.Projected in the Transverse Mercator system used e.g.in Google Maps.
Seminar at CIESIN, Sept 14 2011
Maybe GlobalSoilMap.net will not cost as much?
Technology might be the solution!
I Automated mapping
I Global soil covariates � SRTM DEM GDEM TanDEM-X,MODIS LST, Meteo images (SMOS), TRMM
I Downscaling methods
I Soil spectroscopy (rapid soil sampling)
Seminar at CIESIN, Sept 14 2011
The 3(4) bottles of vine
At the GSM2011.org meeting at JRC Ispra several people haveo�ered to award the DSM team that delivers a completecountry/continent size GlobalSoilMap.net product:
I 1 bottle if it contains complete list of soil properties;
I 1 bottle if it includes uncertainty estimates;
I 1 bottle if its accuracy is satisfactory;
I (1 bottle if it is being used by agronomist);
Seminar at CIESIN, Sept 14 2011
ISRIC's response to the GSM initiatives
Global Soil Information Facilities
a set of open tools and data portals
Seminar at CIESIN, Sept 14 2011
GSIF components
1. Cyber infrastructure for input, analysis and visualizationof data.
2. Global databases (legacy data, gridded covariates) thatare main inputs to global soil mapping.
3. Software tools (modules and packages) and manuals forcreation of geoinformation, for instance, according tothe GlobalSoilMap.net speci�cations.
4. Standards and protocols for data entry, map generationand data sharing.
Seminar at CIESIN, Sept 14 2011
Overview
Open Soil Profiles
(GSIF Servers) cyber infrastructure
Soil variables
Soil site info
Soil analytical data
Descriptive properties
Soil covariates (worldgrids)
5.6 km repository
Global
1 km repository
Continental scale
100 / 250 m repository
Country/state-level
R packages
GSIF package
Map import module
Data entry module
Harmonization module
Spline fitting
Spatial analysis module
plotKML
Data import to R
Data visualization
Data export
Soil property maps
100 m (250 m, 1 km and 5.6 km)
Global coverageSix+four key soil parameters
(organic carbon, pH, clay, silt,
sand, coarse fragments)
at six standard depths (0-5, 5-
15, 15-30, 30-60, 60-100, 100-
200 cm)
and with included upper and
lower 95% probability ranges
Webmapping API
Real-time spatial prediction
(Google Maps)
GlobalSoilMap.net functionality
for web-applications
Geo-serving and geoprocessing
functionality
Seminar at CIESIN, Sept 14 2011
Proposed implementation
1. Produce a suite of utilities to import, re-format, analyzeand visualize spatial soil data
2. Design them so they �t the needs of operational globalsoil mapping
3. Focus on using R+OSGeo
4. Get the whole DSM community involved (in design, indevelopment, in use)
5. Provide training in development and use to countries andnodes
Seminar at CIESIN, Sept 14 2011
List of utilities
1. Global soil mapping (core) package � GSIF
2. Soil visualization package � plotKML
3. Soil Reference Library � SRL
4. Geo-services (PythonWPS, Geoserver, RServe, GDAL utilities)
Seminar at CIESIN, Sept 14 2011
Main principles of programming
1. Hide complexity from the users (scale, e�ective precision,3D geostat)
2. Deliver data and results so that no software training is requiredto open it (KML)
3. Link to R+OSGeo community (do not invent functionalitythat already exists and is operational)
Seminar at CIESIN, Sept 14 2011
The software triangle
GIS analysis
Browsing of
geo-data
Statistical
computing
KML
GDAL
ground
overlays,
time-series
GRASS GIS
Seminar at CIESIN, Sept 14 2011
Functionality (plotKML)
I Visualize soil pro�les measurements (using the original soil
colors);
I Visualize soil pro�le photographs;
I Plot results of prediction (soil property maps) using standard
color schemes;
I Visualize uncertainty in the soil property maps;
Seminar at CIESIN, Sept 14 2011
Soil pro�le
Seminar at CIESIN, Sept 14 2011
Soil pro�le attribute plot
Seminar at CIESIN, Sept 14 2011
Soil grids as transparent polygons
Seminar at CIESIN, Sept 14 2011
Multiple layers (above each other)
Seminar at CIESIN, Sept 14 2011
Animations
Seminar at CIESIN, Sept 14 2011
Why KML? (1)
Google Earth is #1: >350 millions of downloads!
Seminar at CIESIN, Sept 14 2011
Why KML? (2)
People that made Google Earth understand
(space-time) statistics
Seminar at CIESIN, Sept 14 2011
What is Global Soil Mapper?
Global Soil Mapper
is an automated system (R+OSGeo) for
generation of soil property maps
that meet the GlobalSoilMap.net specs
Seminar at CIESIN, Sept 14 2011
Global Soil Mapper: the main principles
1. Put emphasis on inputs (point data, soil polygon maps,covariates) and tools (GSIF)
2. Fit model parameters per soil property for the wholeworld
3. Map the world block-by-block (automated mapping)
4. Update the maps as soon as the new point / covariatesarrive (while you sleep)
Seminar at CIESIN, Sept 14 2011
GSIF function predict
predict.gsm ( target.var = "ORCDRC", observations = soilprofiles.org,
+ covariates = worldgrids.org, model = GMN-RK,
+ newdata = boundingbox )
model = GMN-RK is the default global model (�tted using theglobal data);
Seminar at CIESIN, Sept 14 2011
GMN-RK
Global Multiscale Nested RK =
a 3D spatial prediction method
based on a four-level nested Regression-Kriging
Seminar at CIESIN, Sept 14 2011
Nested RK
z(sB) = m0(sB−k) + e1(sB−k|sB−[k−1]) + . . .+ ek(sB−1|sB) + ε(sB)
where m0(sB−k) is the value of the target variable estimated at thecoarsest global scale (B− k), B−1, . . . ,B−k are the higher order
components, ek(sB−k|sB−[k−1]) is the residual variation from scalesB−k to a �ner resolution scale sB−[k−1], and ε is the spatially
auto-correlated residual soil variation dealt with ordinary kriging.
Seminar at CIESIN, Sept 14 2011
Multiscale signal
S4
+ S
3 +
S2
+ S
1 +
eS
4 +
S3
+ S
2 +
S1
S4
+ S
3 +
S2
S4
+ S
3S
4
Figure: Based on McBratney (1998): Some considerations on methodsfor spatially aggregating and disaggregating soil information.
Seminar at CIESIN, Sept 14 2011
65k soil pro�les
Figure: USDA NCSS Characterization Database, CSIRO National SoilArchive, ISRIC WISE, SPADE, Iran National soil pro�le database,Canadian Soil Information System, and African soil pro�les.
Seminar at CIESIN, Sept 14 2011
Data sets available for Malawi
Seminar at CIESIN, Sept 14 2011
Gridded maps for Malawi
5.6 km
1 km
250 m
100 m
BiomesClimateParent
material
General
land use
Erosion
deposition
MODIS-based long term Land
Surface Temperature (day/night)
Land
management
Rainfall map of the world
Elevation
Geologic Provinces of Africa
MODIS (MCD12Q1) land cover dynamics
ENVISAT Land Cover map (GlobCov)
MODIS (MCD13Q1) Enhanced Vegetation
Index (EVI) and medium infrared band (MIR)
TWI, TRI, Slope,
Surface roughness,
Insolation
Landsat ETM
thermal band
Soil polygon map (FAO classes)
Seminar at CIESIN, Sept 14 2011
The downscaling approach
Figure: Predictions of soil organic carbon for top depth at various scales.By running a multiscale global model we can �ll in the large gaps in thedata (interpolate instead of extrapolate).
Seminar at CIESIN, Sept 14 2011
Organic carbon (6 depths)
Seminar at CIESIN, Sept 14 2011
One done, 18 thousand to go. . .
Seminar at CIESIN, Sept 14 2011
Lessons learned
Conclusions
Seminar at CIESIN, Sept 14 2011
Conclusions
I Value of soil information is likely to grow.
I GSIF is a methodological framework for continuousproduction of Open Soil Information.
I Advantage of using a GMN-RK is that we can employ adiversity of predictors (CLORPT factors work at di�erentscales).
I Global is now (local statistical models will become extinct?).
Seminar at CIESIN, Sept 14 2011
Conclusions
I Value of soil information is likely to grow.
I GSIF is a methodological framework for continuousproduction of Open Soil Information.
I Advantage of using a GMN-RK is that we can employ adiversity of predictors (CLORPT factors work at di�erentscales).
I Global is now (local statistical models will become extinct?).
Seminar at CIESIN, Sept 14 2011
Conclusions
I Value of soil information is likely to grow.
I GSIF is a methodological framework for continuousproduction of Open Soil Information.
I Advantage of using a GMN-RK is that we can employ adiversity of predictors (CLORPT factors work at di�erentscales).
I Global is now (local statistical models will become extinct?).
Seminar at CIESIN, Sept 14 2011
Conclusions
I Value of soil information is likely to grow.
I GSIF is a methodological framework for continuousproduction of Open Soil Information.
I Advantage of using a GMN-RK is that we can employ adiversity of predictors (CLORPT factors work at di�erentscales).
I Global is now (local statistical models will become extinct?).
Seminar at CIESIN, Sept 14 2011
Soils of Mars
�Astrophysists are selling something very abstract for a
high price. Soils are the basic of human survival, yet we
manage to acquire much less research funds.�
Neil McKenzie (CSIRO)
�We know more about soils of Mars than about soils of
Africa.�
Pedro Sanchez (Earth Institute)
Seminar at CIESIN, Sept 14 2011
Next steps
I Next step: Re-implement the method using a `clean' dataset (USA data) and write up step-by-step guidelines.
I Publish the GSIF package and WPS for GSM (anyone canbecome a digital soil mapper).
I Complete and publish plotKML and GSIF R packages.
I Map the whole of Africa at 100 m (end of 2012).
Seminar at CIESIN, Sept 14 2011