136 results on '"Ließ, Mareike"'
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2. Implementing result-based agri-environmental payments by means of modelling
3. Spatial Prediction of Organic Matter Quality in German Agricultural Topsoils.
4. 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.
5. Payments by modelled results: A novel design for agri-environmental schemes
6. Spectral data processing for field-scale soil organic carbon monitoring
7. Predictive monitoring of soil organic carbon using multispectral UAV imagery: a case study on a long-term experimental field
8. Spectral Data Processing for Field-Scale Soil Organic Carbon Monitoring
9. Reply on RC2
10. 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
11. Optimisation in machine learning: An application to topsoil organic stocks prediction in a dry forest ecosystem
12. Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales
13. On-the-Go Vis-NIR Spectroscopy for Field-Scale Spatial-Temporal Monitoring of Soil Organic Carbon
14. Spatial prediction of soil water retention in a Páramo landscape: Methodological insight into machine learning using random forest
15. 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.
16. On-the-go Vis-NIR spectroscopy for field-scale spatial-temporal monitoring of soil organic carbon
17. Sampling for regression-based digital soil mapping: Closing the gap between statistical desires and operational applicability
18. Natural Landslides Which Impact Current Regulating Services: Environmental Preconditions and Modeling
19. Multivariate 3D soil parameter space - Germany [agricultural soil-landscape, version 1.0]
20. DATA and PTFs: Development of pedotransfer functions for water retention in tropical mountain soilscapes: Spotlight on parameter tuning in machine learning
21. Spatial topsoil texture predictions: Topsoil texture regionalization for agricultural soils in Germany – an iterative approach to advance model interpretation
22. DATA: Error propagation in spectrometric functions of soil organic carbon
23. Modeling the Agricultural Soil Landscape of Germany—A Data Science Approach Involving Spatially Allocated Functional Soil Process Units
24. Spatial prediction of organic carbon in German agricultural topsoil using machine learning algorithms
25. On the benefits of clustering approaches in digital soil mapping: an application example concerning soil texture regionalization
26. Can soil spectroscopy contribute to soil organic carbon monitoring on agricultural soils?
27. 3D soil parameter space of the agricultural landscape [Germany, Version 2]
28. Modeling the agricultural soil landscape of Germany—A data science approach involving spatially allocated functional soil process units
29. Spatial prediction of organic carbon in German agricultural topsoil using machine learning algorithms
30. On the benefits of clustering approaches in digital soil mapping: an application example concerning soil texture regionalization
31. Topsoil texture regionalization for agricultural soils in Germany – an iterative approach to advance model interpretation
32. Making use of the World Reference Base diagnostic horizons for the systematic description of the soil continuum — Application to the tropical mountain soil-landscape of southern Ecuador
33. Uncertainty in the spatial prediction of soil texture: Comparison of regression tree and Random Forest models
34. Systemic modelling of soil functions under the impact of agricultural management
35. Digital Soil Mapping in Southern Ecuador
36. Topsoil Texture Regionalization for Agricultural Soils in Germany—An Iterative Approach to Advance Model Interpretation
37. Supplementary material to "Performance of three machine learning algorithms for predicting soil organic carbon in German agricultural soil"
38. Performance of three machine learning algorithms for predicting soil organic carbon in German agricultural soil
39. Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile
40. Machine learning with GA optimization to model the agricultural soil-landscape of Germany: An approach involving soil functional types with their multivariate parameter distributions along the depth profile
41. On the benefits of clustering approaches in digital soil mapping: an application example concerning soil texture regionalization
42. Can soil spectroscopy contribute to soil organic carbon monitoring on agricultural soils?
43. Exploring the Vis-NIR wavelength importance in SOC models under field and lab conditions in a long-term field experiment
44. Systemic soil modelling and the evaluation of functions
45. Payments by modelled results: A novel design for agri-environmental schemes
46. Development of pedotransfer functions for water retention in tropical mountain soil landscapes: spotlight on parameter tuning in machine learning
47. Development of pedotransfer functions for water retention in tropical mountain soil landscapes: spotlight on parameter tuning in machine learning
48. VIS-NIR wavelength importance in SOC models
49. Systemic modelling of soil functions under the impact of agricultural management
50. Applying machine learning and differential evolution optimization for soil texture predictions at national scale (Germany)
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