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Global Soil Information Facilities(A methodological framework for Open SoilInformation)Tomislav HenglISRIC  World Soil Inf...
Key issues   What do we know about world soils?   What do you know about the GlobalSoilMap.net project?   How to produce c...
My backgrounds   Senior researcher at   ISRIC    World Soil Information;   PhD in pedometric mapping @ ITC (GIS institute ...
My publications                  Seminar at CIESIN, Sept 14 2011
What am I doing in USA?                          Seminar at CIESIN, Sept 14 2011
AfricaSoils.netThank you! 1.   Markus Walsh (Keith Shepherd) 2.   Sonya Ahamed  Pedro Sanchez                             ...
My main inspirations / principles of work   Open Source software for education and research   Crowd sourcing systems for e...
Important assumptions             My research philosophy       is based on 4 important assumptions:                       ...
Assumption #1      Humans (companies and governments)          need to be closely monitored                               ...
Did you know?   Global biodiversity has been heavily degraded due to human   activities. The   Living planet index   has d...
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                        ...
Critical areas (irrigation)                              Seminar at CIESIN, Sept 14 2011
Food price index (FAO)                         Seminar at CIESIN, Sept 14 2011
Soil threatsSoils are also more important because we are slowly loosing them:    305 million ha   of land has been complet...
Soils might become precious in futureReports by FAO (2002) show that, in future, 80 percent ofincreased crop production in...
Assumption #3            Soil Information (global)         is one of the poorest GIS layers                               ...
What do we know about world soils?   Harmonized World Soil Database:        1 km resolution gridded   soil property maps (...
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 proles)                                  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                            ...
GLIS                                                                                   Soil properties (soil information s...
GRMS (see Zeitgeist moving forward 1:34h)                                    Seminar at CIESIN, Sept 14 2011
GlobalSoilMap.net   An international initiative to make soil property maps (7+3) at   six depths at 3 arcsecs (100 m).   t...
GlobalSoilMap.net in comparison with other projects                                     4.0                               ...
World soils in numbers   Total land area:   14.8 billion ha                                                         73.6%)...
Global Soil Mapping (in numbers)   The total productive soil areas:   about 104 million square   km.                      ...
Global Soil Mapping (in numbers)   The total productive soil areas:   about 104 million square   km.                      ...
Global Soil Mapping (in numbers)   The total productive soil areas:   about 104 million square   km.                      ...
Global Soil Mapping (in numbers)   The total productive soil areas:   about 104 million square   km.                      ...
Global Soil Mapping (in numbers)   The total productive soil areas:   about 104 million square   km.                      ...
Productive soil areasFigure: Soil productive area mask derived using the MODIS LAI images.Projected in the Transverse Merc...
Maybe GlobalSoilMap.net will not cost as much?Technology might be the solution!    Automated mapping    Global soil covari...
The 3(4) bottles of vineAt the GSM2011.org meeting at JRC Ispra several people haveoered to award the DSM team that delive...
ISRICs response to the GSM initiatives          Global Soil Information Facilities        a set of open tools and data por...
GSIF components 1.   Cyber infrastructure for input, analysis and visualization      of data. 2.   Global databases (legac...
Overview             Open Soil Profiles                                                  Soil covariates (worldgrids)     ...
Proposed implementation 1.   Produce a suite of utilities to import, re-format, analyze      and visualize spatial soil da...
List of utilities 1. Global soil mapping (core) package   GSIF 2. Soil   visualization package  plotKML 3. Soil   Referenc...
Main principles of programming 1.   Hide complexity from the users    (scale, eective precision,      3D geostat) 2. Deliv...
The software triangle                               Statistical                               computing                   ...
Functionality (plotKML)   Visualize soil proles measurements (using the original soil   colors);   Visualize soil prole ph...
Soil prole              Seminar at CIESIN, Sept 14 2011
Soil prole 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, S...
Why KML? (2)   People that made Google Earth understand               (space-time) statistics                             ...
What is Global Soil Mapper?                Global Soil Mapper      is an automated system (R+OSGeo) for         generation...
Global Soil Mapper: the main principles 1.   Put emphasis on inputs (point data, soil polygon maps,      covariates) and t...
GSIF function predictpredict.gsm ( target.var = ORCDRC, observations = soilprofiles.org,+             covariates = worldgr...
GMN-RK         Global Multiscale Nested RK =          a 3D spatial prediction method  based on a four-level nested Regress...
Nested RKz(sB ) = m0 (sB−k ) + e1 (sB−k |sB−[k−1] ) + . . . + ek (sB−1 |sB ) + ε(sB )where   m0 (sB−k )   is the value of ...
Multiscale signal             S4 + S3 + S2 + S1 + e             S4 + S3 + S2 + S1             S4 + S3 + S2             S4 ...
65k soil prolesFigure: USDA NCSS Characterization Database, CSIRO National SoilArchive, ISRIC WISE, SPADE, Iran National s...
Data sets available for Malawi                                 Seminar at CIESIN, Sept 14 2011
Gridded maps for Malawi                                             Parent            General           Erosion           ...
The downscaling approachFigure: Predictions of soil organic carbon for top depth at various scales.By running a multiscale...
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   Value of soil information is likely to grow.                                                  Seminar at CIE...
Conclusions   Value of soil information is likely to grow.   GSIF is a methodological framework for    continuous   produc...
Conclusions   Value of soil information is likely to grow.   GSIF is a methodological framework for    continuous   produc...
Conclusions   Value of soil information is likely to grow.   GSIF is a methodological framework for    continuous   produc...
Soils of Mars   Astrophysists are selling something very abstract for a   high price. Soils are the basic of human surviva...
Next steps            Re-implement the method using a `clean data   Next step:   set (USA data) and write up step-by-step ...
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Introducing GSIF (seminar at Lamont campus)

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  1. 1. Global Soil Information Facilities(A methodological framework for Open SoilInformation)Tomislav HenglISRIC World Soil Information, Wageningen University Seminar at CIESIN, Sept 14 2011
  2. 2. Key issues What do we know about world soils? What do you know about the GlobalSoilMap.net project? How to produce complete GlobalSoilMape.net property maps? How will soil information t into the Global Land Information System? Seminar at CIESIN, Sept 14 2011
  3. 3. My backgrounds Senior researcher at ISRIC World Soil Information; PhD in pedometric mapping @ ITC (GIS institute in Enschede) in 2003; 2 years university assistant; 2.5 years JRC Ispra; 2 years University of Amsterdam; My expertise: Geostatistics, Digital Soil Mapping, spatial data analysis, geomorphometry (vice-chair); Global Soil Information Facilities Seminar at CIESIN, Sept 14 2011
  4. 4. My publications Seminar at CIESIN, Sept 14 2011
  5. 5. What am I doing in USA? Seminar at CIESIN, Sept 14 2011
  6. 6. AfricaSoils.netThank you! 1. Markus Walsh (Keith Shepherd) 2. Sonya Ahamed Pedro Sanchez Seminar at CIESIN, Sept 14 2011
  7. 7. My main inspirations / principles of work Open Source software for education and research Crowd sourcing systems for environmental data collection Publicly accessible (soil) data products Seminar at CIESIN, Sept 14 2011
  8. 8. Important assumptions My research philosophy is based on 4 important assumptions: Seminar at CIESIN, Sept 14 2011
  9. 9. Assumption #1 Humans (companies and governments) need to be closely monitored Seminar at CIESIN, Sept 14 2011
  10. 10. Did you know? Global biodiversity has been heavily degraded due to human activities. The Living planet index has dropped from 1970s to 60% and will continue to do so (source: Millennium Assessment project). By 2048 we will run out of sh (your children will leave on a planet where there are hardly any visible sh in the oceans). 15-35% of global irrigation withdrawals are estimated to be unsustainable (source: WBCSD). Every year, 9.4 million ha of forests are lost (source: FAO World agriculture: towards 2015/2030). Seminar at CIESIN, Sept 14 2011
  11. 11. Population trends Seminar at CIESIN, Sept 14 2011
  12. 12. Decline of species (biodiversity) Seminar at CIESIN, Sept 14 2011
  13. 13. Forests and croplands Seminar at CIESIN, Sept 14 2011
  14. 14. Assumption #2 Soils (and hence information on soils) will become more and more important Seminar at CIESIN, Sept 14 2011
  15. 15. Critical areas (irrigation) Seminar at CIESIN, Sept 14 2011
  16. 16. Food price index (FAO) Seminar at CIESIN, Sept 14 2011
  17. 17. Soil threatsSoils are also more important because we are slowly loosing them: 305 million ha of land has been completely degraded (no longer suitable for agriculture). 10-50% irrigated land aected by salinization (source: GLASOD). For a forest to return takes maybe 100 years; it takes 100400 years to produce 1 cm of topsoil are soils renewable resource at all? Seminar at CIESIN, Sept 14 2011
  18. 18. Soils might become precious in futureReports by FAO (2002) show that, in future, 80 percent ofincreased crop production in developing countries will have to comefrom intensication 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
  19. 19. Assumption #3 Soil Information (global) is one of the poorest GIS layers Seminar at CIESIN, Sept 14 2011
  20. 20. What do we know about world soils? Harmonized World Soil Database: 1 km resolution gridded soil property maps (16 properties for top and sub-surface soil). 1:5M scale FAO-UNESCO Soil Map of the Word: from which ISRIC has produced 5 by 5 arc-minutes global soil property maps (for 020, 2040, 4060, 6080 and 80100 cm) in combination with the ISRIC-WISE soil prole database. The Distributed Active Archive Center (DAAC) soil property maps USGS-produced soil property maps Atlas of the Biosphere soil maps Seminar at CIESIN, Sept 14 2011
  21. 21. HWSD vs GlobCov GlobCover HWSD Seminar at CIESIN, Sept 14 2011
  22. 22. Should soils follow political boundaries? Seminar at CIESIN, Sept 14 2011
  23. 23. HWSD vs ISRIC SIS (753 proles) Seminar at CIESIN, Sept 14 2011
  24. 24. The agreement plot (kappa 10%) Seminar at CIESIN, Sept 14 2011
  25. 25. Assumption #4 Global Resource Planning System can do much better than a local one Seminar at CIESIN, Sept 14 2011
  26. 26. GLIS Soil properties (soil information system) - physical and chemical soil properties, nutrient capacity, water storage, acidity/salinity… Model library Live weather channel (meteorological forecasting) - anticipated temperature (min, max), rainfall, frost hazard, drought hazard, flood hazard… Fertilization Irrigation Plant monitoring channel (MODIS/ENVISAT) Pest treatment - current biomass production, biomass anomalies Best crop calendar (pest and diseases), plant health… Yield estimates Environmental risks Socio-economic data (site-specific) GLOBAL - administrative units, new laws and regulations, LAND INFORMATION market activity, closest offices, agro-dealers… SYSTEM Suggest the best land use practice Query site attributes Information Update with incorrect? ground truth data Spatial location (site) Seminar at CIESIN, Sept 14 2011
  27. 27. GRMS (see Zeitgeist moving forward 1:34h) Seminar at CIESIN, Sept 14 2011
  28. 28. GlobalSoilMap.net An international initiative to make soil property maps (7+3) at six depths at 3 arcsecs (100 m). the leitmotif is to assemble, collate, and rescue as much of the worlds existing soil data ; The soil-equivalent of the OneGeology.org, GBIF, GlobCover and similar projects. The biggest DSM project ever! Seminar at CIESIN, Sept 14 2011
  29. 29. GlobalSoilMap.net in comparison with other projects 4.0 GLWD EcoRegions HWSDv1 5.6 km MOD12C1 MOD13C2 CHLO/SST 3.5 FRA Resolution (m) in log-scale WorldClim GPWv3 3.0 DMSP-OLSv4 GlobCov2 OneGeology? 2.5 SRTM GADM GlobalSoilMap? 2.0 1990 1995 2000 2005 2010 2015 2020 Year Seminar at CIESIN, Sept 14 2011
  30. 30. World soils in numbers Total land area: 14.8 billion ha 73.6%) Estimated total productive soil area: 10.9 billion ha ( Drylands (deserts, semi-deserts): 3.6 billion ha (24.3%) Wetlands (swamps, marshes, and bogs): 440 million ha (3%) Arable and permanent crops: 1.5 billion ha (11%) Potential areas suitable in varying degrees for the rainfed production of arable and permanent crops: 2.8 billion ha Seminar at CIESIN, Sept 14 2011
  31. 31. Global Soil Mapping (in numbers) The total productive soil areas: about 104 million square km. Seminar at CIESIN, Sept 14 2011
  32. 32. Global Soil Mapping (in numbers) The total productive soil areas: about 104 million square km. k To map the world at 100 m (1:200 ), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. Seminar at CIESIN, Sept 14 2011
  33. 33. Global Soil Mapping (in numbers) The total productive soil areas: about 104 million square km. k To map the world at 100 m (1:200 ), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. We would require some 65M proles according to the strict rules of Avery (1987). Seminar at CIESIN, Sept 14 2011
  34. 34. Global Soil Mapping (in numbers) The total productive soil areas: about 104 million square km. k To map the world at 100 m (1:200 ), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. We would require some 65M proles according to the strict rules of Avery (1987). World map at 0.008333333 arcdegrees (ca.1 km) resolution is an image of size 43,200 Ö21,600 pixels. Seminar at CIESIN, Sept 14 2011
  35. 35. Global Soil Mapping (in numbers) The total productive soil areas: about 104 million square km. k To map the world at 100 m (1:200 ), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. We would require some 65M proles according to the strict rules of Avery (1987). World map at 0.008333333 arcdegrees (ca.1 km) resolution is an image of size 43,200 Ö21,600 pixels. 27 billion pixels needed to represent the whole world in 100 m (productive soil areas). Seminar at CIESIN, Sept 14 2011
  36. 36. Productive soil areasFigure: 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
  37. 37. Maybe GlobalSoilMap.net will not cost as much?Technology might be the solution! Automated mapping Global soil covariates SRTM DEM GDEM TanDEM-X, MODIS LST, Meteo images (SMOS), TRMM Downscaling methods Soil spectroscopy (rapid soil sampling) Seminar at CIESIN, Sept 14 2011
  38. 38. The 3(4) bottles of vineAt the GSM2011.org meeting at JRC Ispra several people haveoered to award the DSM team that delivers a completecountry/continent size GlobalSoilMap.net product: 1 bottle if it contains complete list of soil properties; 1 bottle if it includes uncertainty estimates; 1 bottle if its accuracy is satisfactory; (1 bottle if it is being used by agronomist); Seminar at CIESIN, Sept 14 2011
  39. 39. ISRICs response to the GSM initiatives Global Soil Information Facilities a set of open tools and data portals Seminar at CIESIN, Sept 14 2011
  40. 40. GSIF components 1. Cyber infrastructure for input, analysis and visualization of data. 2. Global databases (legacy data, gridded covariates) that are main inputs to global soil mapping. 3. Software tools (modules and packages) and manuals for creation of geoinformation, for instance, according to the GlobalSoilMap.net specications. 4. Standards and protocols for data entry, map generation and data sharing. Seminar at CIESIN, Sept 14 2011
  41. 41. Overview Open Soil Profiles Soil covariates (worldgrids) Global Continental scale Country/state-level Soil variables Soil site info Soil analytical data Descriptive properties 5.6 km repository 1 km repository 100 / 250 m repository R packages GSIF package Map import module Data entry module Harmonization module Spline fitting Spatial analysis module plotKML (GSIF Servers) cyber infrastructure Data import to R Data visualization Data export Soil property maps Six+four key soil parameters Webmapping API Global coverage (organic carbon, pH, clay, silt, sand, coarse fragments) Real-time spatial prediction at six standard depths (0-5, 5- (Google Maps) 15, 15-30, 30-60, 60-100, 100- GlobalSoilMap.net functionality 200 cm) for web-applications and with included upper and Geo-serving and geoprocessing lower 95% probability ranges functionality 100 m (250 m, 1 km and 5.6 km) Seminar at CIESIN, Sept 14 2011
  42. 42. Proposed implementation 1. Produce a suite of utilities to import, re-format, analyze and visualize spatial soil data 2. Design them so they t the needs of operational global soil mapping 3. Focus on using R+OSGeo 4. Get the whole DSM community involved (in design, in development, in use) 5. Provide training in development and use to countries and nodes Seminar at CIESIN, Sept 14 2011
  43. 43. 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
  44. 44. Main principles of programming 1. Hide complexity from the users (scale, eective precision, 3D geostat) 2. Deliver data and results so that no software training is required to open it ( KML) 3. Link to R+OSGeo community ( do not invent functionality that already exists and is operational) Seminar at CIESIN, Sept 14 2011
  45. 45. The software triangle Statistical computing GDAL ground GRASS GIS overlays, time-series KML Browsing of geo-data GIS analysis Seminar at CIESIN, Sept 14 2011
  46. 46. Functionality (plotKML) Visualize soil proles measurements (using the original soil colors); Visualize soil prole photographs; Plot results of prediction (soil property maps) using standard color schemes; Visualize uncertainty in the soil property maps; Seminar at CIESIN, Sept 14 2011
  47. 47. Soil prole Seminar at CIESIN, Sept 14 2011
  48. 48. Soil prole attribute plot Seminar at CIESIN, Sept 14 2011
  49. 49. Soil grids as transparent polygons Seminar at CIESIN, Sept 14 2011
  50. 50. Multiple layers (above each other) Seminar at CIESIN, Sept 14 2011
  51. 51. Animations Seminar at CIESIN, Sept 14 2011
  52. 52. Why KML? (1) Google Earth is #1: 350 millions of downloads! Seminar at CIESIN, Sept 14 2011
  53. 53. Why KML? (2) People that made Google Earth understand (space-time) statistics Seminar at CIESIN, Sept 14 2011
  54. 54. 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
  55. 55. 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 whole world 3. Map the world block-by-block (automated mapping) 4. Update the maps as soon as the new point / covariates arrive (while you sleep) Seminar at CIESIN, Sept 14 2011
  56. 56. GSIF function predictpredict.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
  57. 57. 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
  58. 58. Nested RKz(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 the coarsest global scale (B − k ), B−1 , . . . ,B−k are the higher ordercomponents, ek (sB−k |sB−[k−1] ) is the residual variation from scale sB−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
  59. 59. Multiscale signal S4 + S3 + S2 + S1 + e S4 + S3 + S2 + S1 S4 + S3 + S2 S4 + S3 S4Figure: Based on McBratney (1998): Some considerations on methodsfor spatially aggregating and disaggregating soil information. Seminar at CIESIN, Sept 14 2011
  60. 60. 65k soil prolesFigure: USDA NCSS Characterization Database, CSIRO National SoilArchive, ISRIC WISE, SPADE, Iran National soil prole database,Canadian Soil Information System, and African soil proles. Seminar at CIESIN, Sept 14 2011
  61. 61. Data sets available for Malawi Seminar at CIESIN, Sept 14 2011
  62. 62. Gridded maps for Malawi Parent General Erosion Land Climate Biomes material land use deposition management Rainfall map of the world 5.6 km MODIS-based long term Land Surface Temperature (day/night) Elevation Geologic Provinces of Africa 1 km Soil polygon map (FAO classes) ENVISAT Land Cover map (GlobCov) MODIS (MCD12Q1) land cover dynamics 250 m MODIS (MCD13Q1) Enhanced Vegetation Index (EVI) and medium infrared band (MIR) TWI, TRI, Slope, Surface roughness, 100 m Insolation Landsat ETM thermal band Seminar at CIESIN, Sept 14 2011
  63. 63. The downscaling approachFigure: 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
  64. 64. Organic carbon (6 depths) Seminar at CIESIN, Sept 14 2011
  65. 65. One done, 18 thousand to go. . . Seminar at CIESIN, Sept 14 2011
  66. 66. Lessons learned Conclusions Seminar at CIESIN, Sept 14 2011
  67. 67. Conclusions Value of soil information is likely to grow. Seminar at CIESIN, Sept 14 2011
  68. 68. Conclusions Value of soil information is likely to grow. GSIF is a methodological framework for continuous production of Open Soil Information. Seminar at CIESIN, Sept 14 2011
  69. 69. Conclusions Value of soil information is likely to grow. GSIF is a methodological framework for continuous production of Open Soil Information. Advantage of using a GMN-RK is that we can employ a diversity of predictors ( CLORPT factors work at dierent scales). Seminar at CIESIN, Sept 14 2011
  70. 70. Conclusions Value of soil information is likely to grow. GSIF is a methodological framework for continuous production of Open Soil Information. Advantage of using a GMN-RK is that we can employ a diversity of predictors ( CLORPT factors work at dierent scales). Global is now (local statistical models will become extinct?). Seminar at CIESIN, Sept 14 2011
  71. 71. 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
  72. 72. Next steps Re-implement the method using a `clean data Next step: set (USA data) and write up step-by-step guidelines. Publish the GSIF package and WPS for GSM (anyone can become a digital soil mapper). Complete and publish plotKML and GSIF R packages. Map the whole of Africa at 100 m (end of 2012). Seminar at CIESIN, Sept 14 2011
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