Deep Learning with a Multi-Task Convolutional Neural Network to Generate a National-Scale 3D Soil Data Product: The Particle Size Distribution of the German Agricultural Soil Landscape.

Autor: Ließ, Mareike, Sakhaee, Ali

Publikováno v: Agriculture; Basel; Aug2024, Vol. 14 Issue 8, p1230, 20p

Deep learning with a multi-task convolutional neural network to generate a national-scale 3D soil data product: Particle size distribution of the German agricultural soil-landscape.

Autor: Ließ, Mareike, Sakhaee, Ali

Publikováno v: EGUsphere; 11/10/2023, p1-23, 23p

The centennial legacy of land-use change on organic carbon stocks of German agricultural soils.

Autor: Emde D; Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany., Poeplau C; Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany., Don A; Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany., Heilek S; Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany., Schneider F; Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany.

Publikováno v: Global change biology [Glob Chang Biol] 2024 Aug; Vol. 30 (8), pp. e17444.

Modeling the Agricultural Soil Landscape of Germany—A Data Science Approach Involving Spatially Allocated Functional Soil Process Units.

Autor: Ließ, Mareike

Publikováno v: Agriculture; Basel; Nov2022, Vol. 12 Issue 11, p1784, 31p

A Review of Farmland Soil Health Assessment Methods: Current Status and a Novel Approach.

Autor: Hussain, Zakir, Deng, Limei, Wang, Xuan, Cui, Rongyang, Liu, Gangcai

Publikováno v: Sustainability (2071-1050); Aug2022, Vol. 14 Issue 15, p9300-N.PAG, 17p