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Capacità di scambio cationico effettiva iSDAsoil
Capacità di scambio cationico effettiva media e deviazione standard prevista a profondità del suolo di 0-20 cm e 20-50 cm, i valori dei pixel devono essere trasformati in modo inverso con exp(x/10)-1. Nelle aree di giungla fitta (generalmente nell'Africa centrale), l'accuratezza del modello è bassa e quindi si verificano artefatti come bande … africa alluminio isda suolo -
Carbonio totale iSDAsoil
Carbonio totale a profondità del suolo di 0-20 cm e 20-50 cm, media e deviazione standard previste. I valori dei pixel devono essere trasformati nuovamente con exp(x/10)-1. Nelle aree di giungla fitta (generalmente nell'Africa centrale), la precisione del modello è bassa e, di conseguenza, potrebbero verificarsi artefatti come bande … africa alluminio isda suolo -
Classe di texture USDA iSDAsoil
Classe di tessitura del suolo USDA a profondità del suolo di 0-20 cm e 20-50 cm. Nelle aree di giungla fitta (generalmente nell'Africa centrale), la precisione del modello è bassa e potrebbero essere visibili artefatti come bande. Le previsioni delle proprietà del suolo sono state effettuate da Innovative Solutions for Decision … africa alluminio isda suolo -
Alluminio estraibile dal suolo iSDA
Alluminio estraibile a profondità del suolo di 0-20 cm e 20-50 cm, media e deviazione standard previste. I valori dei pixel devono essere trasformati nuovamente con exp(x/10)-1. Le previsioni delle proprietà del suolo sono state effettuate da Innovative Solutions for Decision Agriculture Ltd. (iSDA) con una dimensione del pixel di 30 m utilizzando il machine learning combinato … africa alluminio isda suolo
Datasets tagged aluminium in Earth Engine
[null,null,[],[[["\u003cp\u003eThis dataset provides soil property predictions for Africa at 30m pixel size, including extractable aluminum, total carbon, effective cation exchange capacity, and USDA texture class.\u003c/p\u003e\n"],["\u003cp\u003ePredictions are available for two soil depths: 0-20 cm and 20-50 cm, and include predicted mean and standard deviation.\u003c/p\u003e\n"],["\u003cp\u003eData is back-transformed using exp(x/10)-1 for analysis.\u003c/p\u003e\n"],["\u003cp\u003eModel accuracy is lower in dense jungle areas (generally over central Africa), potentially leading to artifacts like banding.\u003c/p\u003e\n"],["\u003cp\u003ePredictions were generated by Innovative Solutions for Decision Agriculture Ltd.(iSDA) using machine learning techniques.\u003c/p\u003e\n"]]],["iSDA provides soil data for Africa at 30m pixel size, focusing on depths of 0-20 cm and 20-50 cm. This includes extractable aluminium, total carbon, effective cation exchange capacity, and USDA texture class. Data includes predicted mean and standard deviation. Pixel values require back-transformation using the formula exp(x/10)-1. Model accuracy may be low in dense jungle areas, potentially showing banding artifacts. Machine learning is employed for soil property predictions.\n"],null,["# Datasets tagged aluminium in Earth Engine\n\n-\n\n |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil Effective Cation Exchange Capacity](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_cation_exchange_capacity) |\n | Effective Cation Exchange Capacity predicted mean and standard deviation at soil depths of 0-20 cm and 20-50 cm, Pixel values must be back-transformed with exp(x/10)-1. In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts such as banding (striping) ... |\n | [africa](/earth-engine/datasets/tags/africa) [aluminium](/earth-engine/datasets/tags/aluminium) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) |\n\n-\n\n |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil Total Carbon](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_carbon_total) |\n | Total carbon at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation. Pixel values must be back-transformed with exp(x/10)-1. In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts such as banding (striping) might be ... |\n | [africa](/earth-engine/datasets/tags/africa) [aluminium](/earth-engine/datasets/tags/aluminium) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil USDA Texture Class](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_texture_class) |\n | USDA Texture Class at soil depths of 0-20 cm and 20-50 cm. 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 Solutions for Decision ... |\n | [africa](/earth-engine/datasets/tags/africa) [aluminium](/earth-engine/datasets/tags/aluminium) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### iSDAsoil extractable Aluminium](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_aluminium_extractable) |\n | Extractable aluminium at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation. Pixel values must be back-transformed with exp(x/10)-1. Soil property predictions were made by Innovative Solutions for Decision Agriculture Ltd. (iSDA) at 30 m pixel size using machine learning coupled ... |\n | [africa](/earth-engine/datasets/tags/africa) [aluminium](/earth-engine/datasets/tags/aluminium) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) |"]]