Worldgrids.org: building global covariates for automated mapping
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Keynote lecture at Spatial Statistics Conference 2011, Enschede

Keynote lecture at Spatial Statistics Conference 2011, Enschede

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Worldgrids.org: building global covariates for automated mapping Presentation Transcript

  • 1. Worldgrids.orgbuilding global covariates for automatedmappingTomislav Hengl & Hannes I. ReuterISRIC  World Soil Information, Wageningen University SS2010 conference, Mar 26th 2011
  • 2. About ISRIC ISRIC  World Soil Information. SS2010 conference, Mar 26th 2011
  • 3. About ISRIC ISRIC  World Soil Information. ISRIC = International Soil Reference Information Center. SS2010 conference, Mar 26th 2011
  • 4. About ISRIC ISRIC  World Soil Information. ISRIC = International Soil Reference Information Center. Non-prot organization / aliated to Wageningen University and Research. SS2010 conference, Mar 26th 2011
  • 5. About ISRIC ISRIC  World Soil Information. ISRIC = International Soil Reference Information Center. Non-prot organization / aliated to Wageningen University and Research. Mandate: serve soil data; serve international soil standards; moderate collaboration and partnerships. SS2010 conference, Mar 26th 2011
  • 6. About ISRIC ISRIC  World Soil Information. ISRIC = International Soil Reference Information Center. Non-prot organization / aliated to Wageningen University and Research. Mandate: serve soil data; serve international soil standards; moderate collaboration and partnerships. Projects: GlobalSoilMap.net, SOTER, Green Water Credits ... SS2010 conference, Mar 26th 2011
  • 7. This talk Global repository of publicly available data (worldgrids.org). A global multiscale approach to geostat mapping. Some examples: Malawi. Upcoming activities. SS2010 conference, Mar 26th 2011
  • 8. Main thesis Global (multiscale) modeling is now! SS2010 conference, Mar 26th 2011
  • 9. Analysis objectivesFor Diggle and Ribeiro (2007) there are three scientic objectivesof geostatistics: 1. model estimation, i.e.inference about the model parameters; 2. prediction, i.e.inference about the unobserved values of the target variable; 3. hypothesis testing; SS2010 conference, Mar 26th 2011
  • 10. Regression-krigingTarget variable z is a sum of deterministic and stochasticcomponents: z(s) = m(s) + ε(s) (1)where m(s) is the deterministic part of the variation (i.e.a linearfunction of the auxiliary variables), ε(s) is the residual for every (s). SS2010 conference, Mar 26th 2011
  • 11. BLUP for spatial data ˆ ˆ ˆ z (s0 ) = qT · β + λT · (z − q · β) ˆ 0 0 ˆ −1 β = qT · C−1 · q · qT · C−1 · z (2) ˆ λ0 = C−1 · c0This is the dominant model used in ∼90% of our mapping projects(Minasny and McBratney, 2007) SS2010 conference, Mar 26th 2011
  • 12. Zeds and ques SS2010 conference, Mar 26th 2011
  • 13. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. SS2010 conference, Mar 26th 2011
  • 14. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. SS2010 conference, Mar 26th 2011
  • 15. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. The original images need to be processed before you can use them as global covariates. SS2010 conference, Mar 26th 2011
  • 16. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. The original images need to be processed before you can use them as global covariates. Produce grids → prepare data for upload → geo-serve it. SS2010 conference, Mar 26th 2011
  • 17. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. The original images need to be processed before you can use them as global covariates. Produce grids → prepare data for upload → geo-serve it. The result is a repository with cca 100 unique rasters, that can be obtained directly from http://spatial-analyst.net/worldmaps/. SS2010 conference, Mar 26th 2011
  • 18. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. The original images need to be processed before you can use them as global covariates. Produce grids → prepare data for upload → geo-serve it. The result is a repository with cca 100 unique rasters, that can be obtained directly from http://spatial-analyst.net/worldmaps/. Each gridded map consists of 7200 columns and 3600 rows; the cell size is 0.05 arcdegrees, which corresponds to about 5.6 km; all maps fall on the same grid. SS2010 conference, Mar 26th 2011
  • 19. Worldgrids.org I was ask to write a review of publicly available global data sets of interest for species distribution modeling. I discovered that at 15 km resolution, there is A LOT of publicly available data which are under-used. The original images need to be processed before you can use them as global covariates. Produce grids → prepare data for upload → geo-serve it. The result is a repository with cca 100 unique rasters, that can be obtained directly from http://spatial-analyst.net/worldmaps/. Each gridded map consists of 7200 columns and 3600 rows; the cell size is 0.05 arcdegrees, which corresponds to about 5.6 km; all maps fall on the same grid. PS: I also have a lot of data at 1 km. SS2010 conference, Mar 26th 2011
  • 20. Read more (or see a gallery) SS2010 conference, Mar 26th 2011
  • 21. Flight pathsPreparing worldgrids  an example with ight paths (density map) SS2010 conference, Mar 26th 2011
  • 22. PyWPSOverlay, subset, reproject, aggregate functionality (example):> GNworldgrids(layername="globcov", xcoord=6.848911, ycoord=52.245427) [1] "50"under construction. SS2010 conference, Mar 26th 2011
  • 23. Global Soil Information An international initiative to make soil property maps (7+3) at six depths at 3 arcsecs (100 m). the lightmotive is to assemble, collate, and rescue as much of the worlds existing soil data ; Some 30 people directly involved (ISRIC is the main project coordinator). International compilation of soil data. The soil-equivalent of the OneGeology.org, GBIF, GlobCover and similar projects. See full specications at http://globalsoilmap.org/specifications SS2010 conference, Mar 26th 2011
  • 24. My dream is to build an Open multipurpose GLIS SS2010 conference, Mar 26th 2011
  • 25. The six pillars of open geo-data production1 1. open data, in real-time 2. open source geospatial software 3. open, reproducable procedures 4. open, web-based, methods for data and processing models (interoperability) 5. open and explicitly quantied signicance and accuracy levels of research ndings 6. managed, open user and developer communities 1 Edzer Pebesma, (OpenGeostatistic.org) SS2010 conference, Mar 26th 2011
  • 26. GSM in numbers The total productive soil areas: about 104 million square km. SS2010 conference, Mar 26th 2011
  • 27. GSM in numbers The total productive soil areas: about 104 million square km. To map the world soils at 100 m (1:200k), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. According to Pedro Sanchez, world soils could be mapped for $0.20 USD per ha ($300 million USD). SS2010 conference, Mar 26th 2011
  • 28. GSM in numbers The total productive soil areas: about 104 million square km. To map the world soils at 100 m (1:200k), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. According to Pedro Sanchez, world soils could be mapped for $0.20 USD per ha ($300 million USD). We would require some 65M proles according to the strict rules of Avery (1987). SS2010 conference, Mar 26th 2011
  • 29. GSM in numbers The total productive soil areas: about 104 million square km. To map the world soils at 100 m (1:200k), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. According to Pedro Sanchez, world soils could be mapped for $0.20 USD per ha ($300 million USD). 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 43,200Ö21,600 pixels. SS2010 conference, Mar 26th 2011
  • 30. GSM in numbers The total productive soil areas: about 104 million square km. To map the world soils at 100 m (1:200k), would cost about 5 billion EUR (0.5 EUR per ha) using traditional methods. According to Pedro Sanchez, world soils could be mapped for $0.20 USD per ha ($300 million USD). 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 43,200Ö21,600 pixels. One image of the world at a 100 m resolution contains 27 billion pixels (productive soil areas only!). SS2010 conference, Mar 26th 2011
  • 31. Our proposal Build global repositories of point and gridded data (covariate). SS2010 conference, Mar 26th 2011
  • 32. Our proposal Build global repositories of point and gridded data (covariate). Animate people to contribute to the data repositories (crowdsourcing). SS2010 conference, Mar 26th 2011
  • 33. Our proposal Build global repositories of point and gridded data (covariate). Animate people to contribute to the data repositories (crowdsourcing). Implement the six pillars of open geo-data production (especially open infrastructures and open code). SS2010 conference, Mar 26th 2011
  • 34. Our proposal Build global repositories of point and gridded data (covariate). Animate people to contribute to the data repositories (crowdsourcing). Implement the six pillars of open geo-data production (especially open infrastructures and open code). Prove that it is doable ( showcases). SS2010 conference, Mar 26th 2011
  • 35. Soil proles from various projects (65k points) SS2010 conference, Mar 26th 2011
  • 36. Critical question: How to produce soil property maps @ 100 m with such limited data? SS2010 conference, Mar 26th 2011
  • 37. Global Multiscale Nested RKWe propose using nested RK model: z(sB ) = m0 (sB−k ) + e1 (sB−k |sB−[k+1] ) + . . . + ek (sB−2 |sB−1 ) + ε(sB ) (3)where z(s ) is the value of the target variable estimated at ground Bscale (B), , . . . , are the higher order components, B−1 ) is the residual variation from scale s to a B−ke (s |shigher resolution scale s , and ε is spatially auto-correlated k B−k B−(k+1) B−(k+1)residual soil variation (dealt with ordinary kriging). B−k SS2010 conference, Mar 26th 2011
  • 38. Multi-scale concept SS2010 conference, Mar 26th 2011
  • 39. Multi-resolution signal (McBratney, 1998) SS2010 conference, Mar 26th 2011
  • 40. 1 km resolution (AVHRR) SS2010 conference, Mar 26th 2011
  • 41. 300 m resolution (ENVISAT) SS2010 conference, Mar 26th 2011
  • 42. 25 m resolution (Landsat) SS2010 conference, Mar 26th 2011
  • 43. The proposed system SS2010 conference, Mar 26th 2011
  • 44. Showcase Let us see some real examples SS2010 conference, Mar 26th 2011
  • 45. GM-NRK in action: Malawi showcase 2740 soil observations, from which some 8001000 contain complete analytical and descriptive data. SS2010 conference, Mar 26th 2011
  • 46. GM-NRK in action: Malawi showcase 2740 soil observations, from which some 8001000 contain complete analytical and descriptive data. 1:800k polygon soil map. SS2010 conference, Mar 26th 2011
  • 47. GM-NRK in action: Malawi showcase 2740 soil observations, from which some 8001000 contain complete analytical and descriptive data. 1:800k polygon soil map. Some 30-40 gridded layers at various resolutions (covariates). SS2010 conference, Mar 26th 2011
  • 48. Data sets available for Malawi (a) (b) (c) 48.8 32.7 16.6 0.5 10° 11° 12° 13° 14° 15° 16° 38000 32667 27333 22000 17° 33° 34° 35° SS2010 conference, Mar 26th 2011
  • 49. Gridded maps for Malawi SS2010 conference, Mar 26th 2011
  • 50. Regression analysis 10 20 30 40 0 2000 4000 max 6 5 4 SOC.T 3 2 1 0 40 30 biocl5 20 10 6000 PRECm 4000 2000 0 5000 4000 3000 globedem 2000 1000 0 0 0 1 2 3 4 5 6 0 2000 6000 SS2010 conference, Mar 26th 2011
  • 51. pH visualized in GE (1 degree block) SS2010 conference, Mar 26th 2011
  • 52. Conclusions Global models  global multiscale predictions  are now. SS2010 conference, Mar 26th 2011
  • 53. Conclusions Global models  global multiscale predictions  are now . It is very probable that, in the near future, any geostatistical analysis will be global. SS2010 conference, Mar 26th 2011
  • 54. Conclusions Global models  global multiscale predictions  are now . It is very probable that, in the near future, any geostatistical analysis will be global. We probably need to re-write the geostatistical algorithms so they work with sphere geometry (3D + time). SS2010 conference, Mar 26th 2011
  • 55. Conclusions Global models  global multiscale predictions  are now . It is very probable that, in the near future, any geostatistical analysis will be global. We probably need to re-write the geostatistical algorithms so they work with sphere geometry (3D + time). There is enormous amount of publicly available RS and GIS data that is waiting to be used for geostatistical mapping  use it ! SS2010 conference, Mar 26th 2011
  • 56. In one sentence: Take a broader view! SS2010 conference, Mar 26th 2011
  • 57. Next steps Launch 5 and 1 km worldgrids. SS2010 conference, Mar 26th 2011
  • 58. Next steps Launch 5 and 1 km worldgrids. Provide geo-service and spatial analysis functionality (overlay, subset, aggregate). SS2010 conference, Mar 26th 2011
  • 59. Next steps Launch 5 and 1 km worldgrids. Provide geo-service and spatial analysis functionality (overlay, subset, aggregate). Start making cyber-infrastructure for 250 m and 100 m grids. SS2010 conference, Mar 26th 2011
  • 60. Next steps Launch 5 and 1 km worldgrids. Provide geo-service and spatial analysis functionality (overlay, subset, aggregate). Start making cyber-infrastructure for 250 m and 100 m grids. Provide geo-processing services for automated mapping. SS2010 conference, Mar 26th 2011
  • 61. Join GEOSTAT SS2010 conference, Mar 26th 2011
  • 62. Space-time workshop (Münster) SS2010 conference, Mar 26th 2011