Global Soil Information Facilities (book)
1-degree tiles (world)Submitted by t.hengl on February 8, 2011 - 18:25
 One degree tiles based on the land mask map. Attached below:
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20 simulations (block support) of the soil organic carbonSubmitted by t.hengl on June 16, 2011 - 14:47
 20 simulations (block support) of the soil organic carbon for the Meuse study area (cross-section from West to East at Y=330348). Bold line indicates the median value and broken lines indicate upper and lower quantiles (95%) derived using the raster package. R code (25) |
Animated display of uncertainty in mapping soil classesSubmitted by t.hengl on June 17, 2011 - 10:29
 KML file (104) |
Changes in soil carbon modeled using splinesSubmitted by t.hengl on June 16, 2011 - 14:21
 Changes in soil carbon modeled using information on horizon (stratified model; left) and mass-preserving spline (right). R code (25)
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Decomposition of a signal into four components plus noiseSubmitted by t.hengl on June 16, 2011 - 14:32
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Global soil mask map in the Google Projection systemSubmitted by t.hengl on September 15, 2010 - 12:19
 Global soil mask map at resolution of 5.6 km representing soil productive areas (defined as areas with LAI >0 in any of the last 10 years). This soil mask map was estimated by using the MODIS long-term series of Leaf Area Index images. |
Multiscale simulations of organic matter for Meuse case studySubmitted by t.hengl on June 16, 2011 - 14:37
 Multiscale simulations of organic matter for Meuse case study: downscaling from 40 m (soil mapping units) to 10 m resolution (LiDAR data). In each step spatial detail and contrast are refined by adding higher resolution data. |
Point and block predictions and simulations using the Meuse datasetSubmitted by t.hengl on June 16, 2011 - 14:43
 Point (above) and block (below) predictions and simulations using the Meuse dataset available in the gstat package. Notice that prediction values produced by point and block methods are quite similar. Simulations on block support, however, seem to produce somewhat 'smoother' maps than the point-support predictions. The difficulty of using block simulations, however, is that the computational intensity is an order of magnitude greater compared to simulations at point support. R code (25) |
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Prediction or organic matter as geo-GIF (KML)Submitted by t.hengl on June 16, 2011 - 15:40
 KML file (104) |
Predictions of organic matter (Meuse data) visualized using polygons (KML)Submitted by t.hengl on June 16, 2011 - 15:37
 Predictions of organic matter for the Meuse data set visualized using polygons (each grid node a single polygon). This method allows the surveyor to match the predictions with the features in the background and understand how the scale of the gridded maps corresponds to the spatial detail of the actual features. Hollow or blank areas are regions of extrapolation i.e. areas where the prediction error exceeds the global variance. KML file (104) |
Predictions of soil organic carbon for E33_S14Submitted by t.hengl on June 16, 2011 - 15:43
 Predictions of soil organic carbon for first standard depth (2.5 cm) for block E33_S14. Download organic carbon for whole Malawi (18). |
In November 2008, an $18 million grant has been obtained from the Bill & Melinda Gates foundation and the Alliance for a Green Revolution in Africa (AGRA) to map most parts in Sub-Sahara Africa, and make all Sub-Saharan Africa data available. From this grant there are also funds for coordinating global efforts and for the establishment of a global consortium. Several institutions have assumed a leading role in this effort and have made substantial financial and in-kind contributions.
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