Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.2.1. Remotely Sensed Data
2.2.2. Distribution Datasets for Spring Maize
2.2.3. Actual Disaster Records
2.2.4. Phenophase Observations
2.2.5. Yield Data
2.3. Methods
2.3.1. Construction of Drought Samples
2.3.2. Drought Threshold Curves
2.3.3. Daily Dynamic Thresholds and Its Validation
2.3.4. Maize Yield Analysis
3. Results
3.1. Dynamic Threshold Model for Agricultural Drought Grades
3.1.1. Determination of Daily Dynamic Thresholds for Different Drought Grades
3.1.2. Validation of Drought Grades
3.2. Analysis of Historical Drought Events Based on Dynamic Drought Thresholds of VWI
3.2.1. Drought Dynamics at a Typical Station
3.2.2. Spatial Evolution of Drought in Typical Drought Years
3.2.3. Impact of Drought on Spring Maize Yield
3.3. Distribution Characteristics of Drought Identified by VWI in 2000–2020
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Drought Grade | Drought Threshold |
---|---|
Drought free | |
Mild drought | |
Moderate drought | |
Severe drought |
Drought Grade | R2 | a | b | c | d |
---|---|---|---|---|---|
Drought free | 0.91 | 36.60 | 11.24 | 95.74 | 11.15 |
Mild drought | 0.91 | 39.46 | 10.15 | 93.35 | 11.07 |
Moderate drought | 0.93 | 41.15 | 10.15 | 91.37 | 11.16 |
Severe drought | 0.96 | 44.08 | 9.76 | 89.56 | 11.49 |
Drought Grade | Accuracy of Validation | Number of Drought Samples | |
---|---|---|---|
Complete Correspondence | Within One Grade | ||
Total | 84.6% | 96.2% | 78 |
Mild drought | 93.8% | 100.0% | 16 |
Moderate drought | 76.3% | 94.7% | 38 |
Severe drought | 91.7% | 95.8% | 24 |
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Wu, X.; Wang, P.; Gong, Y.; Zhang, Y.; Wang, Q.; Li, Y.; Guo, J.; Han, S. Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize. Remote Sens. 2024, 16, 3260. https://doi.org/10.3390/rs16173260
Wu X, Wang P, Gong Y, Zhang Y, Wang Q, Li Y, Guo J, Han S. Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize. Remote Sensing. 2024; 16(17):3260. https://doi.org/10.3390/rs16173260
Chicago/Turabian StyleWu, Xia, Peijuan Wang, Yanduo Gong, Yuanda Zhang, Qi Wang, Yang Li, Jianping Guo, and Shuxin Han. 2024. "Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize" Remote Sensing 16, no. 17: 3260. https://doi.org/10.3390/rs16173260