World Soils 250m Coarse Fragments

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root. This layer contains the physical soil variable coarse fragments (cfvo). Coarse fragments are particles that are more than 2 millimeters in diameter. These coarse fragments are not included in chemical, mineralogical, and some physical analyses. Soils that have a high percentage of coarse fragments are less desirable for most uses. A high proportion of fragments dilutes the effectiveness of the fine earth part of the soil (particles less than 2 millimeters in diameter). On the soil surface, fragments dissipate some of the energy of raindrops. Therefore, soils with a moderate amount of coarse fragments on the surface tend to resist erosion. Percolation of water through soil is often more rapid where the percentage of coarse fragments is greatest, if other properties are similar. This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands. Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for coarse fragments are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties. Dataset Summary Phenomenon Mapped: Volumetric fraction of coarse fragments (> 2 mm) in cm³/100cm³ (vol%) Cell Size: 250 meters Pixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned Integer Coordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m) Extent: World land area except Antarctica Visible Scale: All scales are visible Number of Columns and Rows: 160300, 100498 Source: Soilgrids.org Publication Date: May 2020 Analysis: Analysis-Optimized Data from the soilgrids.org mean predictions for cfvo were used to create this layer. You may access coarse fragments values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client. Mean depth (cm) Actual depth range of data -2.5 0-5cm depth range -10 5-15cm depth range -22.5 15-30cm depth range -45 30-60cm depth range -80 60-100cm depth range -150 100-200cm depth range What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application. Read more in our blogs: Dsicoveries and Revelations: Exploring the World Soils 250m Layers Getting Started with Multidimensional Soil Layers in the ArcGIS Living Atlas of the World Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK. In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions. This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics. Analysis In order to leverage the optimization for analysis, the capability must be enabled by your ArcGIS organization administrator. More information on enabling this feature can be found in the ‘Regional data hosting’ section of this help doc. Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See the ArcGIS Living Atlas: Analysis-Optimized Imagery Layers Group for a complete list of imagery layers optimized for analysis. More information about soilgrids layers Answers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data. To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version. This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro. Accessing this layer's companion uncertainty layer Because data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.