-
iSDAsoil 有效阳离子交换容量
有效阳离子交换容量在土壤深度 0-20 厘米和 20-50 厘米处的预测平均值和标准差,像素值必须使用 exp(x/10)-1 进行反转换。在茂密丛林地区(通常位于非洲中部),模型准确性较低,因此会出现条纹(条带)等伪影… africa aluminium isda soil -
iSDAsoil 总碳
土壤深度为 0-20 厘米和 20-50 厘米的总碳含量、预测均值和标准差。必须使用 exp(x/10)-1 对像素值进行反转换。在茂密丛林地区(通常位于非洲中部),模型准确性较低,因此可能会出现条纹(条状)等伪影。 africa aluminium isda soil -
iSDAsoil USDA 土壤类
土壤深度为 0-20 厘米和 20-50 厘米处的美国农业部土壤质类。在茂密丛林地区(通常位于非洲中部),模型准确性较低,因此可能会出现条纹(条状)等伪影。土壤性质预测由 Innovative Solutions for Decision … africa aluminium isda soil -
iSDAsoil 可提取的铝
土壤深度为 0-20 厘米和 20-50 厘米的可提取铝的预测均值和标准差。必须使用 exp(x/10)-1 对像素值进行反转换。Innovative Solutions for Decision Agriculture Ltd. (iSDA) 使用机器学习与 … africa aluminium isda soil
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) |"]]