Spatiotemporally Map** Non-Grain Production of Winter Wheat Using a Developed Auto-Generating Sample Algorithm on Google Earth Engine
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Datasets
2.2.1. Landsat Surface Reflectance Imagery
2.2.2. Historical Samples Used to Support the Algorithm for Auto-Generating Samples
3. Methods
3.1. Auto-Generating Winter Wheat Sample Algorithm
3.2. One-Class Support Vector Machine for Winter Wheat Map**
3.3. Spatiotemporally Map** Non-Grain Production of Winter Wheat
4. Results
4.1. Auto-Generating Winter Wheat Samples
4.2. AGWWS Maps
4.3. Spatiotemporal Pattern of NGPOWW
5.2. Spatiotemporally Pattern of Winter Wheat
5.3. Marginalization of Winter Wheat Planting Caused by NGPOWW
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Band/Index | Wavelength [Min–Max] (μm)/Equation |
---|---|
Blue (B) | [0.45–0.52] |
Green (G) | [0.52–0.60] |
Red (R) | [0.63–0.69] |
NIR (Near-Infrared) | [0.77–0.90] |
SWIR1 (Shortwave Infrared 1) | [1.55–1.75] |
SWIR2 (Shortwave Infrared 2) | [2.08–2.35] |
Normalized Difference Vegetation Index (NDVI) [45] | |
Land Surface Water Index (LSWI) [46,47] | |
Enhanced Vegetation Index (EVI) [48] |
Period | Winter Wheat to Rice (×103 ha) | Winter Wheat Change (×103 ha) | Proportion |
---|---|---|---|
2000–2005 | 23.60 | 3461.30 | 0.68% |
2005–2010 | 12.60 | 2483.00 | 0.51% |
2010–2015 | 52.80 | 2869.70 | 1.84% |
Intersection Criteria | ≥SAD | ≤ED | ≤NIRDI | |
---|---|---|---|---|
Different thresholds | 1 | 0.678546 | 0.339203 | 0.201108 |
2 | 0.805858 | 0.264924 | 0.104253 | |
3 | 0.853300 | 0.205496 | 0.056761 | |
4 | 0.892172 | 0.152997 | 0.021987 | |
5 | 0.926136 | 0.110889 | −0.004949 | |
6 | 0.955699 | 0.080112 | −0.029506 | |
7 | 0.978941 | 0.056054 | −0.054408 | |
8 | 0.993051 | 0.034353 | −0.085166 |
Year | Training Samples | Validation Samples | |
---|---|---|---|
Winter Wheat | Winter Wheat | Non-Winter Wheat | |
2000 | 642 | 345 | 306 |
2005 | 631 | 316 | 361 |
2010 | 644 | 332 | 361 |
2015 | 644 | 332 | 347 |
2021 | 671 | 353 | 405 |
Year | Class | Winter Wheat | Non-Winter Wheat | UA (%) | PA (%) | F1 (%) | OA (%) |
---|---|---|---|---|---|---|---|
2000 | Winter wheat | 297 | 100 | 74.81 | 86.09 | 80.05 | 77.27 |
Non-winter wheat | 48 | 206 | 81.10 | 67.32 | 73.57 | ||
2005 | Winter wheat | 220 | 20 | 91.67 | 69.62 | 79.14 | 82.87 |
Non-winter wheat | 96 | 341 | 78.03 | 94.46 | 85.46 | ||
2010 | Winter wheat | 261 | 72 | 78.38 | 78.61 | 78.50 | 79.37 |
Non-winter wheat | 71 | 289 | 80.28 | 80.06 | 80.17 | ||
2015 | Winter wheat | 252 | 37 | 87.20 | 75.90 | 81.16 | 82.77 |
Non-winter wheat | 80 | 310 | 79.49 | 89.34 | 84.12 | ||
2021 | Winter wheat | 262 | 24 | 91.61 | 76.38 | 83.31 | 85.96 |
Non-winter wheat | 81 | 381 | 82.47 | 94.07 | 87.89 |
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Zhang, M.; Sun, P.; Sun, Z. Spatiotemporally Map** Non-Grain Production of Winter Wheat Using a Developed Auto-Generating Sample Algorithm on Google Earth Engine. Remote Sens. 2024, 16, 659. https://doi.org/10.3390/rs16040659
Zhang M, Sun P, Sun Z. Spatiotemporally Map** Non-Grain Production of Winter Wheat Using a Developed Auto-Generating Sample Algorithm on Google Earth Engine. Remote Sensing. 2024; 16(4):659. https://doi.org/10.3390/rs16040659
Chicago/Turabian StyleZhang, Meng, Peijun Sun, and Zhangli Sun. 2024. "Spatiotemporally Map** Non-Grain Production of Winter Wheat Using a Developed Auto-Generating Sample Algorithm on Google Earth Engine" Remote Sensing 16, no. 4: 659. https://doi.org/10.3390/rs16040659