Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Areas and Cropping Systems
2.2. Data Acquisition and Treatment
2.2.1. Remote Sensing Image Data Acquisition
2.2.2. Soil Sample Data Collection
2.3. Multi-Period Crop Growth Information Data Construction
2.4. Modeling and Optimization
2.4.1. Random Forest
2.4.2. Optuna Hyperparameter Optimization Framework
2.5. Model Evaluation and Validation
2.6. Technology Roadmap
3. Results
3.1. Remote Sensing Data with Different AN Contents
3.1.1. Spectral Character of Different AN Contents During the Bare Soil Period
3.1.2. Differences in Growth of Different Crops
3.2. AN Mapping Accuracy for Different Bare Soil Periods
3.3. AN Mapping Accuracy by Introducing Information About Different Growth Periods
3.4. Accuracy of Soil AN Mapping Based on Different Crop Types
3.5. Spatial Distribution of Soil AN Content
4. Discussion
4.1. Impact of Introducing Growth Information on AN Content Mapping
4.2. Combining the Advantages of Different Crop Types
4.3. Limitations and Perspectives
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
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Band | Central Wavelength (nm) | Bandwidth (nm) | Spatial Resolution (m) |
---|---|---|---|
B2 | 490 | 65 | 10 |
B3 | 560 | 35 | 10 |
B4 | 665 | 30 | 10 |
B5 | 705 | 15 | 20 |
B6 | 740 | 15 | 20 |
B7 | 783 | 20 | 20 |
B8 | 842 | 115 | 10 |
B8a | 865 | 20 | 20 |
B11 | 1610 | 90 | 20 |
B12 | 2190 | 180 | 20 |
Zone | N | Min (mg kg−1) | Max (mg kg−1) | Mean (mg kg−1) | SD | CV (%) |
---|---|---|---|---|---|---|
Total | 188 | 65.81 | 387.10 | 213.85 | 61.16 | 28.60 |
Soybean | 129 | 76.65 | 387.10 | 211.17 | 60.47 | 28.64 |
Maize | 59 | 65.81 | 357.68 | 219.76 | 62.84 | 28.60 |
Zone | Month | R2 | RMSE (%) |
---|---|---|---|
Soybean | April | 0.557 | 2.466 |
May | 0.522 | 2.927 | |
October | 0.434 | 3.625 | |
Maize | April | 0.491 | 7.251 |
May | 0.459 | 7.410 | |
October | 0.375 | 7.836 |
Zone | Input Variable | R2 | RMSE (%) |
---|---|---|---|
Soybean | Bands | 0.557 | 2.466 |
Bands + EVI717 | 0.621 | 2.340 | |
Maize | Bands | 0.491 | 7.251 |
Bands + EVI819 | 0.515 | 6.940 | |
Total | Bands | 0.597 | 2.244 |
Bands + EVI717 | 0.585 | 2.669 | |
Bands + EVI819 | 0.531 | 3.499 | |
Bands + EVIc | 0.632 | 1.740 |
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Zhang, X.; Ma, Y.; Ma, S.; Qin, C.; Wang, Y.; Liu, H.; Chen, L.; Zhu, X. Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing. Agriculture 2025, 15, 1531. https://doi.org/10.3390/agriculture15141531
Zhang X, Ma Y, Ma S, Qin C, Wang Y, Liu H, Chen L, Zhu X. Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing. Agriculture. 2025; 15(14):1531. https://doi.org/10.3390/agriculture15141531
Chicago/Turabian StyleZhang, Xinle, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, and Xiaomeng Zhu. 2025. "Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing" Agriculture 15, no. 14: 1531. https://doi.org/10.3390/agriculture15141531
APA StyleZhang, X., Ma, Y., Ma, S., Qin, C., Wang, Y., Liu, H., Chen, L., & Zhu, X. (2025). Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing. Agriculture, 15(14), 1531. https://doi.org/10.3390/agriculture15141531