-
OpenLandMap-Sandinhalte
Sandgehalt 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… envirometrix opengeohub openlandmap sand soil usda -
iSDAsoil Sand Content
Sandgehalt 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 isda sand boden
Datasets tagged sand in Earth Engine
[null,null,[],[[["\u003cp\u003eThe iSDAsoil dataset provides predicted mean and standard deviation of sand 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 sand content percentages at six standard depths (0, 10, 30, 60, 100, and 200 cm) globally (excluding Antarctica) at 250 m resolution, based on machine learning predictions from soil profiles and samples.\u003c/p\u003e\n"]]],[],null,["# Datasets tagged sand in Earth Engine\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### OpenLandMap Sand Content](/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02) |\n | Sand 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 | [envirometrix](/earth-engine/datasets/tags/envirometrix) [opengeohub](/earth-engine/datasets/tags/opengeohub) [openlandmap](/earth-engine/datasets/tags/openlandmap) [sand](/earth-engine/datasets/tags/sand) [soil](/earth-engine/datasets/tags/soil) [usda](/earth-engine/datasets/tags/usda) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil Sand Content](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_sand_content) |\n | Sand 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) [isda](/earth-engine/datasets/tags/isda) [sand](/earth-engine/datasets/tags/sand) [soil](/earth-engine/datasets/tags/soil) |"]]