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![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 the
coarsest global scale (B − k ), B−1 , . . . ,B−k are the higher order
components, 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](https://image.slidesharecdn.com/ovhenglseminarlamont-111010034130-phpapp01/75/Introducing-GSIF-seminar-at-Lamont-campus-58-2048.jpg)
Uploaded byTomislav Hengl
Introducing GSIF (seminar at Lamont campus)
The document discusses global soil information facilities and open soil data. It describes the GlobalSoilMap.net project, which aims to produce soil property maps at 3 arcseconds resolution globally. The presentation notes that soil data is currently one of the poorest global geospatial layers and that improving access to soil information is important as soils and sustainable land use planning will become more vital issues. Open sharing of soil data through initiatives like GlobalSoilMap.net can help build a global land information system to support better environmental and agricultural management worldwide.
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Introducing GSIF (seminar at Lamont campus)
- 1. Global Soil InformationFacilities (A methodological framework for Open Soil Information) Tomislav Hengl ISRIC World Soil Information, Wageningen University Seminar at CIESIN, Sept 14 2011
- 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. 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. My publications Seminar at CIESIN, Sept 14 2011
- 5. What am Idoing in USA? Seminar at CIESIN, Sept 14 2011
- 6. AfricaSoils.net Thank you! 1. Markus Walsh (Keith Shepherd) 2. Sonya Ahamed Pedro Sanchez Seminar at CIESIN, Sept 14 2011
- 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. Important assumptions My research philosophy is based on 4 important assumptions: Seminar at CIESIN, Sept 14 2011
- 9. Assumption #1 Humans (companies and governments) need to be closely monitored Seminar at CIESIN, Sept 14 2011
- 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. Population trends Seminar at CIESIN, Sept 14 2011
- 12. Decline of species(biodiversity) Seminar at CIESIN, Sept 14 2011
- 13. Forests and croplands Seminar at CIESIN, Sept 14 2011
- 14. Assumption #2 Soils (and hence information on soils) will become more and more important Seminar at CIESIN, Sept 14 2011
- 15. Critical areas (irrigation) Seminar at CIESIN, Sept 14 2011
- 16. Food price index(FAO) Seminar at CIESIN, Sept 14 2011
- 17. Soil threats Soils arealso 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. Soils might becomeprecious in future Reports by FAO (2002) show that, in future, 80 percent of increased crop production in developing countries will have to come from intensication higher yields, increased multiple cropping and shorter fallow periods. Any agricultural or environmental management model requires soil data as an input to estimation of yields, water and nutrient dynamics. World demand for cereals has jumped from 39 million tones (in 1970) to 103 million tones (in 2000) (source: FAO World agriculture: towards 2015/2030). Seminar at CIESIN, Sept 14 2011
- 19. Assumption #3 Soil Information (global) is one of the poorest GIS layers Seminar at CIESIN, Sept 14 2011
- 20. What do weknow 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. HWSD vs GlobCov GlobCover HWSD Seminar at CIESIN, Sept 14 2011
- 22. Should soils followpolitical boundaries? Seminar at CIESIN, Sept 14 2011
- 23. HWSD vs ISRICSIS (753 proles) Seminar at CIESIN, Sept 14 2011
- 24. The agreement plot(kappa 10%) Seminar at CIESIN, Sept 14 2011
- 25. Assumption #4 Global Resource Planning System can do much better than a local one Seminar at CIESIN, Sept 14 2011
- 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. GRMS (see Zeitgeistmoving forward 1:34h) Seminar at CIESIN, Sept 14 2011
- 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. GlobalSoilMap.net in comparisonwith 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. World soils innumbers 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. Global Soil Mapping(in numbers) The total productive soil areas: about 104 million square km. Seminar at CIESIN, Sept 14 2011
- 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. 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. 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. 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. 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
- 37. Maybe GlobalSoilMap.net willnot 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. The 3(4) bottlesof vine At the GSM2011.org meeting at JRC Ispra several people have oered to award the DSM team that delivers a complete country/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. ISRIC's response tothe GSM initiatives Global Soil Information Facilities a set of open tools and data portals Seminar at CIESIN, Sept 14 2011
- 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. 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. 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. 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. Main principles ofprogramming 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. 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. 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. Soil prole Seminar at CIESIN, Sept 14 2011
- 48. Soil prole attributeplot Seminar at CIESIN, Sept 14 2011
- 49. Soil grids astransparent polygons Seminar at CIESIN, Sept 14 2011
- 50. Multiple layers (aboveeach other) Seminar at CIESIN, Sept 14 2011
- 51. Animations Seminar at CIESIN, Sept 14 2011
- 52. Why KML? (1) Google Earth is #1: 350 millions of downloads! Seminar at CIESIN, Sept 14 2011
- 53. Why KML? (2) People that made Google Earth understand (space-time) statistics Seminar at CIESIN, Sept 14 2011
- 54. What is GlobalSoil 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. 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. 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 the global data); Seminar at CIESIN, Sept 14 2011
- 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. 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 the coarsest global scale (B − k ), B−1 , . . . ,B−k are the higher order components, 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. Multiscale signal S4 + S3 + S2 + S1 + e S4 + S3 + S2 + S1 S4 + S3 + S2 S4 + S3 S4 Figure: Based on McBratney (1998): Some considerations on methods for spatially aggregating and disaggregating soil information. Seminar at CIESIN, Sept 14 2011
- 60. 65k soil proles Figure:USDA NCSS Characterization Database, CSIRO National Soil Archive, ISRIC WISE, SPADE, Iran National soil prole database, Canadian Soil Information System, and African soil proles. Seminar at CIESIN, Sept 14 2011
- 61. Data sets availablefor Malawi Seminar at CIESIN, Sept 14 2011
- 62. Gridded maps forMalawi 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. 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 the data (interpolate instead of extrapolate). Seminar at CIESIN, Sept 14 2011
- 64. Organic carbon (6depths) Seminar at CIESIN, Sept 14 2011
- 65. One done, 18thousand to go. . . Seminar at CIESIN, Sept 14 2011
- 66. Lessons learned Conclusions Seminar at CIESIN, Sept 14 2011
- 67. Conclusions Value of soil information is likely to grow. Seminar at CIESIN, Sept 14 2011
- 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. 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. 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. 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. 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