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SoilGrids1km is a collection of updatable soil property and class maps of the world at a resolution of 1 km produced using state-of-the-art model-based statistical methods. Presents estimates (means and 90% confidence intervals) for pH, texture (sa, si, cl), organic carbon and more for 6 depth layers up to 2 m depth.
Digital soil mapping (DSM) in soil science, also referred to as predictive soil mapping [1] or pedometric mapping, is the computer-assisted production of digital maps of soil types and soil properties. Soil mapping, in general, involves the creation and population of spatial soil information by the use of field and laboratory observational ...
In 2010, Stamen was awarded a US$400,000 grant from the Knight Foundation [21] to create a series of freely-available web maps based on OpenStreetMap data. The resulting map tiles (called Toner, Watercolor, and Terrain) are available for unlimited use under the Creative Commons Attribution license and are compatible with open source mapping ...
Soil and Water Assessment Tool (SWAT) is a free and open source hydrology model and GIS computer simulation sponsored by the USDA. SWAT is a well known geographic hydrological model in use by many universities and government agencies around the world, and integrates with commercial products like ArcGIS .
This is a list of free and open-source software for geological data handling and interpretation. The list is split into broad categories, depending on the intended use of the software and its scope of functionality. Notice that 'free and open-source' requires that the source code is available and users are given a free software license.
HYDRUS suite of software is supported by an interactive graphics-based interface for data-preprocessing, discretization of the soil profile, and graphic presentation of the results. While HYDRUS-1D simulates water flow, solute and heat transport in one-dimension, and is a public domain software , HYDRUS 2D/3D extends the simulation capabilities ...
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Pedometric mapping, or statistical soil mapping, is data-driven generation of soil property and class maps that is based on use of statistical methods. [1] [2] [3] Its main objectives are to predict values of some soil variable at unobserved locations, and to access the uncertainty of that estimate using statistical inference i.e. statistically optimal approaches.