New Workflow of Plastic-Mulched Farmland Mapping using Multi-Temporal Sentinel-2 data
Abstract
:1. Introduction
2. Study Regions
3. Data Sets
3.1. Sentinel-2 Data and Preprocessing
3.2. Ground Reference Data
4. Methods
4.1. Principle and Workflow
4.2. Possible PML Layer Generation
4.2.1. New PML Indices
4.2.2. Feature Separability and Importance Estimation
4.2.3. Possible PML Layer Generation
4.3. Vegetation Layer and PML Map Generation
4.4. Accuracy Assessment
- No significance between classifiers 1 and 2 (N): −1.96 < Z < 1.96.
- Positive significance (classifier 1 has higher accuracy than classifier 2) (S+): Z > 1.96.
- Negative significance (classifier 1 has lower accuracy than classifier 2) (S-): Z < −1.96.
5. Results and Discussion
5.1. Feature Separability and Importance for Bare Land and PML Discrimination
5.2. PML Mapping Accuracy Assessment
5.3. Statistical Comparison
5.4. Advantages and Limitations
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Bands/Indices | Equations |
---|---|
Reflectance of Blue 3 band (B7 of Sentinel-2) | |
Reflectance of Green 3 band (B7 of Sentinel-2) | |
Reflectance of Red 3 band (B7 of Sentinel-2) | |
Reflectance of Red-edge 1 band (B7 of Sentinel-2) | |
Reflectance of Red-edge 2 band (B7 of Sentinel-2) | |
Reflectance of Red-edge 3 band (B7 of Sentinel-2) | |
Reflectance of narrow NIR band (B8A of Sentinel-2) | |
Reflectance of board NIR band (B8 of Sentinel-2) | |
Reflectance of SWIR 1 band (B11 of Sentinel-2) | |
Reflectance of SWIR 2 band (B12 of Sentinel-2) | |
PMLI_NIR | Equation (1) in this study |
PMLI_SWIR | Equation (2) in this study |
PMLI_ND | Equation (3) in this study |
PML index (PMLI) | [15] |
Normalized Difference Vegetation Index (NDVI) | [40] |
Normalized Difference Water Index (NDWI) | [41] |
Time | Class | HS | GY |
---|---|---|---|
April | PML | 128 | 0 |
May | PML | 102 | 0 |
June | PML | 176 | 201 |
non-PML (a part of spring maize fields used for training) | 146 | 0 | |
non-PML (used for validation) | 252 | 254 |
OA(%) | Kappa | PA of PML (%) | UA of PML (%) | PA of non-PML(%) | PA of non-PML(%) | ||
---|---|---|---|---|---|---|---|
In HS | |||||||
MTPML | PMLI | 86.68 | 0.7266 | 85.8 | 82.51 | 87.30 | 89.80 |
PMLI_NIR | 90.19 | 0.7942 | 82.95 | 92.41 | 95.24 | 88.89 | |
PMLI_SWIR | 89.25 | 0.7814 | 92.05 | 83.51 | 87.30 | 94.02 | |
PMLI_ND | 88.08 | 0.7499 | 80.11 | 89.81 | 93.65 | 87.08 | |
RF | 91.59 | 0.8266 | 90.34 | 89.33 | 92.46 | 93.20 | |
SUPML | 83.64 | 0.6581 | 76.14 | 82.72 | 88.89 | 84.21 | |
In GY | |||||||
MTPML | PMLI | 83.74 | 0.6766 | 91.04 | 76.57 | 77.95 | 91.67 |
PMLI_NIR | 85.49 | 0.7062 | 84.08 | 83.25 | 86.61 | 87.30 | |
PMLI_SWIR | 85.27 | 0.7038 | 87.06 | 81.02 | 83.86 | 89.12 | |
PMLI_ND | 85.27 | 0.7019 | 84.08 | 82.84 | 86.22 | 87.25 | |
RF | 87.47 | 0.7456 | 85.07 | 86.36 | 89.37 | 88.33 |
MTPML | ||||||
---|---|---|---|---|---|---|
RF | PMLI_NIR | PMLI_SWIR | PMLI_ND | PMLI | ||
MTPML | PMLI_NIR | 1.34 (N) | ||||
PMLI_SWIR | 1.71 (N) | 0.59 (N) | ||||
PMLI_ND | 2.79 (S+) | 1.48 (N) | 0.78 (N) | |||
PMLI | 3.13 (S+) | 2.02 (S+) | 3.32 (S+) | 1.06 (N) | ||
SUPML | 3.71 (S+) | 3.02 (S+) | 2.31 (S+) | 1.93 (N) | 1.20 (N) |
MTPML | |||||
---|---|---|---|---|---|
RF | PMLI_NIR | PMLI_SWIR | PMLI_ND | ||
MTPML | PMLI_NIR | 1.41 (N) | |||
PMLI_SWIR | 1.51 (N) | 0.28 (N) | |||
PMLI_ND | 1.54 (N) | 1.00 (N) | 0.00 (N) | ||
PMLI | 2.65 (S+) | 1.15 (N) | 1.04 (N) | 1.00 (N) |
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Share and Cite
Hao, P.; Chen, Z.; Tang, H.; Li, D.; Li, H. New Workflow of Plastic-Mulched Farmland Mapping using Multi-Temporal Sentinel-2 data. Remote Sens. 2019, 11, 1353. https://doi.org/10.3390/rs11111353
Hao P, Chen Z, Tang H, Li D, Li H. New Workflow of Plastic-Mulched Farmland Mapping using Multi-Temporal Sentinel-2 data. Remote Sensing. 2019; 11(11):1353. https://doi.org/10.3390/rs11111353
Chicago/Turabian StyleHao, Pengyu, Zhongxin Chen, Huajun Tang, Dandan Li, and He Li. 2019. "New Workflow of Plastic-Mulched Farmland Mapping using Multi-Temporal Sentinel-2 data" Remote Sensing 11, no. 11: 1353. https://doi.org/10.3390/rs11111353