Preprints
https://doi.org/10.5194/egusphere-2023-2386
https://doi.org/10.5194/egusphere-2023-2386
10 Nov 2023
 | 10 Nov 2023

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

Mareike Ließ and Ali Sakhaee

Abstract. Many soil functions and processes are controlled by the soil particle size distribution. The generated three-dimensional continuous data product, which covers the particle size fractions of sand, silt, and clay in the agricultural soil-landscape of Germany, has a spatial resolution of 100 m and a depth resolution of 1 cm.  This product is an important component for predicting the effects of agricultural management practices and their adaptability to climate change, as well as for analyzing soil functions and numerous risks. The effectiveness of the convolutional neural network (CNN) algorithm in producing multidimensional, multivariate data products is demonstrated. Even though the potential of this deep learning approach to understand and model the complex soil-landscape relationship is virtually limitless, limitations are data-driven. Further research is needed to assess the required complexity and depth of the CNN and the inclusion of the landscape surrounding each soil profile.

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Mareike Ließ and Ali Sakhaee

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-2386', Philippe Lagacherie, 08 Dec 2023
    • AC1: 'Reply on CC1', Mareike Ließ, 14 Dec 2023
  • RC1: 'Comment on egusphere-2023-2386', Philippe Lagacherie, 28 Dec 2023
    • AC2: 'Reply on RC1', Mareike Ließ, 03 Jan 2024
  • RC2: 'Comment on egusphere-2023-2386', Anonymous Referee #2, 08 Jan 2024
    • AC3: 'Reply on RC2', Mareike Ließ, 09 Jan 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-2386', Philippe Lagacherie, 08 Dec 2023
    • AC1: 'Reply on CC1', Mareike Ließ, 14 Dec 2023
  • RC1: 'Comment on egusphere-2023-2386', Philippe Lagacherie, 28 Dec 2023
    • AC2: 'Reply on RC1', Mareike Ließ, 03 Jan 2024
  • RC2: 'Comment on egusphere-2023-2386', Anonymous Referee #2, 08 Jan 2024
    • AC3: 'Reply on RC2', Mareike Ließ, 09 Jan 2024
Mareike Ließ and Ali Sakhaee
Mareike Ließ and Ali Sakhaee

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Short summary
The CNN is a powerful algorithm to generate three-dimensional multivariate data products. Its high potential is demonstrated by generating a data product for the agricultural soil landscape of Germany. It comprises soil particle size fractions in a vertical resolution of one centimeter. Many soil functions and processes are controlled by the soil particle size distribution. The developed data product is of particular importance to model agricultural processes.