Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction
Abstract
:1. Introduction
2. Materials and Methods
2.1. Characterization of the Study Area
2.2. Remote Sensing Based Classification of Maize Fields
2.2.1. Selection and Pre-Processing of Remote Sensing Data
2.2.2. Preparation of Reference Data
2.2.3. Pixel-Based Classification of Imagery
2.3. Agricultural Biogas Producing Units
2.4. Determining of Pedotopes Susceptible for Compaction during Maize Harvesting
2.5. Determining of Site-Specific Susceptibility for Soil Erosion by Water
- Soil erodibility factor (K): Derived from the soil texture of the topsoil determined in the framework of the German land appraisal. Textures were then assigned to K factors and corrected by soil skeleton and organic carbon contents using Equations (3)–(6), given in [33]. Values of the K factor for the study area with a raster resolution of 5 m by 5 m were provided by the State Office for Geology and Mining Rhineland Palatinate.
- Rainfall and runoff factor (R): R factors were calculated using the following regression equation: R = 0.0788 * mean annual precipitation (in mm) * −2.82 which was valid for the Federal Republic of Germany. Values of the R factor for the study area with a raster resolution of 1 km by 1 km were provided by the State Office for Geology and Mining Rhineland Palatinate.
2.6. Data Analysis and Mapping
3. Results and Discussions
3.1. Maize Classification
3.2. Extent and Changes in Silage Maize Cultivation in the Study Area
3.3. Maize Cultivation on Pedotopes Susceptible for Soil Compaction
3.4. Natural Susceptibility of the Soils for Erosion and Threats to Soil Due to Maize Cultivation
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Year | Sensitivity | Specificity | Kappa |
---|---|---|---|
2009 | >0.99 | ~0.97 | ~0.97 |
2016 | >0.99 | ~0.91 | ~0.93 |
Susceptibility for Soil Compaction | Soil Types |
---|---|
High | Stagnosols, Planosols |
Medium |
|
Low | All other soil types |
Soil Erosion Potential | Soil Loss acc. to Enat |
---|---|
t ha−1 a−1 | |
Very low | <5 |
Low | 5–10 |
Medium | 10–25 |
High | 25–50 |
Very high | >50 |
Year | Remote-Sensing Based Approach | Statistical Data | Difference between stat. Data and Remote-Sensing Based Approach | |
---|---|---|---|---|
ha | ha | ha | % | |
2009 | 7305 | 9147 | −1842 | −20.1 |
2016 | 8447 | 11496 | −3049 | −26.5 |
Agricultural Area | Maize 2009 | Maize 2016 | |||||
---|---|---|---|---|---|---|---|
ha | % | ha | % | ha | % | ||
Total | 87,422 | 100 | 7305 | 100 | 8447 | 100 | |
Classifiable | 31,706 | 36.3 | 2867 | 39.2 | 3249 | 38.5 | |
Vulnerability for soil compaction | Low | 28,758 | 90.7 | 2567 | 89.5 | 2997 | 92.2 |
Medium | 2226 | 7.0 | 252 | 8.8 | 195 | 6.0 | |
High | 722 | 2.3 | 48 | 1.7 | 57 | 1.8 |
Erosion Potential | Agricultural Area | 2009 | 2016 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Maize | Non-Maize | Maize | Non-Maize | |||||||
ha | % | ha | % | ha | % | ha | % | ha | % | |
Very low | 8335 | 9.5 | 724 | 10.4 | 7611 | 9.5 | 791 | 9.7 | 7545 | 9.5 |
Low | 9268 | 10.6 | 1034 | 14.8 | 8233 | 10.2 | 1147 | 14.1 | 8121 | 10.2 |
Medium | 29,414 | 33.7 | 3045 | 43.6 | 26,369 | 32.8 | 3508 | 43.2 | 25,906 | 32.7 |
High | 25,126 | 28.8 | 1846 | 26.5 | 23,280 | 29.0 | 2249 | 27.7 | 22,877 | 28.9 |
Very high | 15,256 | 17.5 | 330 | 4.7 | 14,926 | 18.6 | 426 | 5.3 | 14830 | 18.7 |
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Ruf, T.; Gilcher, M.; Udelhoven, T.; Emmerling, C. Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction. Land 2021, 10, 128. https://doi.org/10.3390/land10020128
Ruf T, Gilcher M, Udelhoven T, Emmerling C. Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction. Land. 2021; 10(2):128. https://doi.org/10.3390/land10020128
Chicago/Turabian StyleRuf, Thorsten, Mario Gilcher, Thomas Udelhoven, and Christoph Emmerling. 2021. "Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction" Land 10, no. 2: 128. https://doi.org/10.3390/land10020128
APA StyleRuf, T., Gilcher, M., Udelhoven, T., & Emmerling, C. (2021). Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction. Land, 10(2), 128. https://doi.org/10.3390/land10020128