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OpenLandMap Clay Content
Tongehalt in % (kg / kg) in 6 Standardtiefen (0, 10, 30, 60, 100 und 200 cm) bei einer Auflösung von 250 m. Basierend auf Machine-Learning-Vorhersagen aus einer globalen Zusammenstellung von Bodenprofilen und ‑proben. Die Verarbeitungsschritte werden hier ausführlich beschrieben. Die Antarktis ist… clay envirometrix opengeohub openlandmap soil usda -
iSDAsoil-Tongehalt
Tongehalt in Bodentiefen von 0–20 cm und 20–50 cm,\nvorhergesagter Mittelwert und Standardabweichung. In Gebieten mit dichtem Dschungel (in der Regel über Zentralafrika) ist die Modellgenauigkeit gering und es können Artefakte wie Streifen auftreten. Die Vorhersagen zu Bodeneigenschaften wurden von Innovative … afrika ton isda boden
Datasets tagged clay in Earth Engine
[null,null,[],[[["\u003cp\u003eThe iSDAsoil dataset provides the predicted mean and standard deviation of clay content at soil depths of 0-20 cm and 20-50 cm for Africa, with potential lower accuracy in dense jungle regions.\u003c/p\u003e\n"],["\u003cp\u003eThe OpenLandMap dataset offers clay content percentages at six standard depths (0, 10, 30, 60, 100, and 200 cm) globally (excluding Antarctica) at a 250 m resolution, based on machine learning predictions from soil profiles and samples.\u003c/p\u003e\n"]]],["The data provides information on soil clay content from two sources. The first, iSDAsoil, offers predicted mean and standard deviation of clay content for 0-20 cm and 20-50 cm depths in Africa, noting potential banding artifacts in dense jungle areas. The second, OpenLandMap, details clay content in percentages (kg/kg) at six standard depths (0-200 cm) globally, using machine learning with a 250 m resolution.\n"],null,["# Datasets tagged clay in Earth Engine\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### OpenLandMap Clay Content](/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02) |\n | Clay content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution Based on machine learning predictions from global compilation of soil profiles and samples. Processing steps are described in detail here. Antarctica is ... |\n | [clay](/earth-engine/datasets/tags/clay) [envirometrix](/earth-engine/datasets/tags/envirometrix) [opengeohub](/earth-engine/datasets/tags/opengeohub) [openlandmap](/earth-engine/datasets/tags/openlandmap) [soil](/earth-engine/datasets/tags/soil) [usda](/earth-engine/datasets/tags/usda) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil Clay Content](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_clay_content) |\n | Clay content at soil depths of 0-20 cm and 20-50 cm,\\\\npredicted mean and standard deviation. In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts such as banding (striping) might be seen. Soil property predictions were made by Innovative ... |\n | [africa](/earth-engine/datasets/tags/africa) [clay](/earth-engine/datasets/tags/clay) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) |"]]