A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Source
2.3. Methods
2.3.1. Flowchart
2.3.2. Pre-Processing
2.3.3. Multi-Date PCA for Enhancement Change Information
2.3.4. Hybrid Classifier for Extraction Change Information
2.3.5. Post-Classification Comparison Change Detection
2.3.6. Accuracy Assessment
3. Results
3.1. Urban Expansion and Green Space Change Detection for 2006–2016
3.2. Urban Expansion and Green Space Change Detection for 2003–2006
3.3. Urban Expansion and Green Space Change Detection for 2000–2003
3.4. Urban Expansion and Green Space Change Detection for 1996–2000
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Acquisition Date | Sensor | Instrument | Spectral Mode | Spectral Resolution (μm) | Spatial Resolution (m) |
---|---|---|---|---|---|
25-03-2016 | Sentinel-2A | MSI | XS | 0.46–0.52 0.54–0.58 0.65–0.68 0.79–0.90 | 10 |
21-12-2006 | SPOT-5 | HRG | XS | 0.50–0.90 0.61–0.68 0.78–0.89 | 10 |
1.58–1.75 | 20 | ||||
06-03-2003 | SPOT-5 | HRG | XS | 0.50–0.90 0.61–0.68 0.78–0.89 | 10 |
1.58–1.75 | 20 | ||||
29-03-2000 | SPOT-2 | HRV | XS | 0.50–0.90 0.61–0.68 0.78–0.89 | 20 |
22-04-1996 | SPOT-3 | HRV | PAN | 0.51–0.73 | 10 |
Acquisition Date | Method | Number of Ground Control Points (GCPs) | Total RMS |
---|---|---|---|
06-03-2003 | Orthorectification | 22 | 0.4264 |
06-03-2003 | Polynomial Transformation | 22 | 0.6132 |
25-03-2016 | Orthorectification | 28 | 0.4085 |
21-12-2006 | Orthorectification | 30 | 0.4275 |
29-03-2000 | Orthorectification | 26 | 0.4191 |
22-04-1996 | Orthorectification | 27 | 0.4291 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 133 | 1 | - | 1 | 2 | 7 | 1 | - | - | - | - | 145 | 93.66 | 91.72 |
2. Or | 2 | 65 | 1 | - | - | - | 2 | - | - | - | - | 70 | 91.55 | 92.86 |
3. Fo | 1 | 2 | 98 | - | - | - | - | - | - | - | 1 | 102 | 97.03 | 96.08 |
4. Wa | - | - | - | 89 | 1 | - | - | 2 | 1 | - | - | 93 | 89.90 | 95.70 |
5. Ur | 1 | - | - | 2 | 132 | 2 | - | - | - | - | - | 137 | 95.65 | 96.35 |
6. Cr to Ur | 2 | - | - | - | 1 | 74 | - | - | 1 | 1 | - | 79 | 79.57 | 93.67 |
7. Or to Ur | - | 1 | - | - | - | 4 | 52 | 1 | - | - | - | 58 | 92.86 | 89.66 |
8. Wa to Ur | 1 | - | - | 5 | 1 | 2 | - | 53 | - | - | - | 62 | 92.98 | 85.48 |
9. Cr to Wa | 2 | - | - | 2 | 1 | 3 | - | 1 | 60 | - | - | 69 | 96.77 | 86.96 |
10. Fo to Ur | - | 1 | 2 | - | - | 1 | 1 | - | - | 51 | 1 | 57 | 98.08 | 89.47 |
11. Fo to Or | - | 1 | - | - | - | - | - | - | - | - | 57 | 58 | 96.61 | 98.28 |
Total | 142 | 71 | 101 | 99 | 138 | 93 | 56 | 57 | 62 | 52 | 59 | 930 | - | - |
Overall accuracy = 92.90%; Kappa coefficient = 0.92 Cr—Cropland; Ur—Urban land Or—Orchard; Wa—Water; Fo—Forest. |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 130 | 2 | 2 | 2 | 1 | 8 | 1 | - | - | - | - | 146 | 91.55 | 89.04 |
2. Or | 3 | 63 | 2 | - | - | 1 | 2 | - | - | - | 1 | 72 | 86.30 | 87.50 |
3. Fo | 2 | 2 | 94 | - | - | - | 1 | - | - | - | 1 | 100 | 93.07 | 94.00 |
4. Wa | 1 | - | - | 90 | 1 | - | - | 3 | 2 | - | - | 97 | 90.91 | 92.78 |
5. Ur | 2 | 1 | - | 1 | 128 | 3 | - | - | - | 1 | - | 136 | 94.12 | 94.12 |
6. Cr to Ur | 1 | - | - | - | 2 | 72 | - | 1 | 3 | 2 | - | 81 | 76.60 | 88.89 |
7. Or to Ur | - | 1 | - | - | 1 | 3 | 50 | 1 | - | - | - | 56 | 89.29 | 89.29 |
8. Wa to Ur | 1 | - | - | 4 | 1 | 2 | - | 51 | - | - | - | 59 | 89.47 | 86.44 |
9. Cr to Wa | 2 | - | - | 2 | 1 | 3 | - | 1 | 57 | - | - | 66 | 91.94 | 86.36 |
10. Fo to Ur | - | 1 | 2 | - | 1 | 2 | 1 | - | - | 49 | 1 | 57 | 94.23 | 85.96 |
11. Fo to Or | - | 3 | 1 | - | - | - | 1 | - | - | - | 55 | 60 | 94.83 | 91.67 |
Total | 142 | 73 | 101 | 99 | 136 | 94 | 56 | 57 | 62 | 52 | 58 | 930 | - | - |
Overall accuracy = 90.22%; Kappa coefficient = 0.89 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||||
1. Cr | 145 | - | - | 2 | 3 | 9 | 1 | - | - | - | 160 | 94.16 | 90.63 |
2. Or | 1 | 67 | - | - | - | - | 1 | - | - | - | 69 | 93.06 | 97.10 |
3. Fo | - | 1 | 101 | - | - | - | - | - | - | - | 102 | 98.06 | 99.02 |
4. Wa | - | - | - | 100 | 1 | 1 | - | 1 | - | - | 103 | 86.96 | 97.09 |
5. Ur | 1 | - | - | 1 | 171 | 2 | - | - | - | - | 175 | 95.00 | 97.71 |
6. Cr to Ur | 3 | - | - | - | 1 | 63 | - | - | 3 | - | 70 | 74.12 | 90.00 |
7. Or to Ur | - | 3 | - | 2 | 1 | 4 | 50 | - | - | - | 60 | 96.15 | 83.33 |
8. Wa to Ur | 1 | - | - | 7 | 2 | 1 | - | 56 | - | - | 67 | 96.55 | 83.58 |
9. Cr to Wa | 3 | - | - | 3 | 1 | 5 | - | 1 | 51 | - | 64 | 94.44 | 79.69 |
10. Fo to Ur | - | 1 | 2 | - | - | - | - | - | - | 57 | 60 | 100.00 | 95.00 |
Total | 154 | 72 | 103 | 115 | 180 | 85 | 52 | 58 | 54 | 57 | 930 | - | - |
Overall accuracy = 92.58%; Kappa coefficient = 0.92 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||||
1. Cr | 140 | 1 | - | 2 | 4 | 10 | 1 | - | - | - | 158 | 90.91 | 88.61 |
2. Or | 2 | 64 | 2 | - | - | - | 2 | - | - | - | 70 | 88.89 | 91.43 |
3. Fo | 1 | 3 | 99 | - | - | - | - | - | - | - | 103 | 96.12 | 96.12 |
4. Wa | 1 | - | - | 99 | 1 | 1 | - | 1 | 1 | - | 104 | 86.09 | 95.19 |
5. Ur | 1 | - | - | 1 | 167 | 3 | - | - | 1 | - | 173 | 92.78 | 96.53 |
6. Cr to Ur | 3 | - | - | 0 | 3 | 61 | - | - | 4 | - | 71 | 71.76 | 85.92 |
7. Or to Ur | - | 3 | - | 2 | 1 | 1 | 48 | - | - | - | 55 | 92.31 | 87.27 |
8. Wa to Ur | 1 | - | - | 8 | 2 | 1 | - | 56 | - | 1 | 69 | 96.55 | 81.16 |
9. Cr to Wa | 5 | - | - | 3 | 2 | 8 | - | 1 | 48 | - | 67 | 88.89 | 71.64 |
10. Fo to Ur | - | 1 | 2 | - | - | - | 1 | - | - | 56 | 60 | 98.25 | 93.33 |
Total | 154 | 72 | 103 | 115 | 180 | 85 | 52 | 58 | 54 | 57 | 930 | - | - |
Overall accuracy = 90.11%; Kappa coefficient = 0.89 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 147 | 1 | - | 1 | 4 | 6 | - | - | 1 | - | - | 160 | 91.88 | 91.88 |
2. Or | 2 | 63 | 1 | - | - | - | - | - | - | - | - | 66 | 87.50 | 95.45 |
3. Fo | - | - | 90 | - | 1 | - | - | - | - | - | - | 91 | 90.91 | 98.90 |
4. Wa | - | 1 | - | 92 | 3 | - | - | - | 1 | - | - | 97 | 95.83 | 94.85 |
5. Ur | 1 | 1 | - | 1 | 121 | 1 | - | - | - | - | - | 125 | 80.13 | 96.80 |
6. Cr to Ur | 4 | - | - | - | 17 | 60 | 1 | 2 | - | - | 1 | 85 | 80.00 | 70.59 |
7. Or to Ur | - | - | - | - | - | 1 | 58 | - | - | - | 1 | 60 | 95.08 | 96.67 |
8. Wa to Ur | - | - | - | - | 4 | 2 | - | 55 | - | - | - | 61 | 96.49 | 90.16 |
9. Cr to Wa | 2 | - | - | 2 | 1 | - | - | - | 58 | - | - | 63 | 96.67 | 92.06 |
10. Cr to Or | 4 | 5 | - | - | - | 2 | - | - | - | 51 | - | 62 | 100.00 | 82.26 |
11. Fo to Ur | - | 1 | 8 | - | - | 3 | 2 | - | - | - | 46 | 160 | 95.83 | 76.67 |
Total | 160 | 72 | 99 | 96 | 151 | 75 | 61 | 57 | 60 | 51 | 48 | 930 | - | - |
Overall accuracy = 90.43%; Kappa coefficient = 0.89 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 141 | 2 | 1 | 1 | 7 | 7 | - | - | 1 | 1 | 161 | 88.13 | 87.58 | |
2. Or | 3 | 63 | 2 | - | - | - | 1 | - | - | 1 | - | 70 | 87.50 | 90.00 |
3. Fo | 1 | 1 | 88 | - | 1 | - | - | - | - | - | 1 | 92 | 88.89 | 95.65 |
4. Wa | 2 | 1 | - | 89 | 3 | - | - | - | 2 | - | 97 | 92.71 | 91.75 | |
5. Ur | 1 | 1 | - | 3 | 117 | 3 | - | 1 | - | - | 126 | 77.48 | 92.86 | |
6. Cr to Ur | 5 | - | - | - | 18 | 54 | 2 | 2 | 1 | - | 1 | 83 | 72.00 | 65.06 |
7. Or to Ur | 1 | 1 | 2 | - | - | 1 | 56 | - | - | - | 1 | 62 | 91.80 | 90.32 |
8. Wa to Ur | - | - | - | 1 | 4 | 3 | - | 53 | - | - | 1 | 62 | 92.98 | 85.48 |
9. Cr to Wa | 2 | - | - | 2 | 1 | - | - | 1 | 56 | - | - | 62 | 93.33 | 90.32 |
10. Cr to Or | 4 | 2 | - | - | - | 4 | - | - | - | 49 | - | 59 | 96.08 | 83.05 |
11. Fo to Ur | - | 1 | 6 | - | - | 3 | 2 | - | - | - | 44 | 56 | 91.67 | 78.57 |
Total | 160 | 72 | 99 | 96 | 151 | 75 | 61 | 57 | 60 | 51 | 48 | 930 | - | - |
Overall accuracy = 87.1%; Kappa coefficient = 0.86 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 183 | 5 | - | 1 | 1 | 1 | - | - | - | - | - | 191 | 89.27 | 95.81 |
2. Or | - | 62 | 2 | - | - | - | 1 | - | - | - | - | 65 | 89.86 | 95.38 |
3. Fo | - | - | 91 | - | - | - | - | - | - | - | 1 | 92 | 92.86 | 98.91 |
4. Wa | 1 | - | - | 88 | 1 | 1 | - | - | - | - | - | 91 | 95.65 | 96.70 |
5. Ur | - | - | - | - | 96 | 3 | - | - | - | - | - | 99 | 75.00 | 96.97 |
6. Cr to Ur | - | - | - | - | 7 | 69 | 1 | 2 | 1 | - | - | 80 | 74.19 | 86.25 |
7. Or to Ur | - | - | - | 2 | 5 | - | 54 | - | - | - | - | 61 | 91.53 | 88.52 |
8. Wa to Ur | - | - | - | 1 | 17 | 5 | - | 40 | - | - | - | 63 | 95.24 | 63.49 |
9. Cr to Wa | 18 | - | - | - | - | 6 | - | - | 42 | 1 | - | 67 | 95.45 | 62.69 |
10. Cr to Or | 3 | - | - | - | - | 8 | 3 | - | 1 | 45 | - | 60 | 95.74 | 75.00 |
11. Fo to Or | - | 2 | 5 | - | 1 | - | - | - | - | 1 | 52 | 61 | 98.11 | 85.25 |
Total | 205 | 69 | 98 | 92 | 128 | 93 | 59 | 42 | 44 | 47 | 53 | 930 | -- | -- |
Overall accuracy = 88.39%; Kappa coefficient = 0.87 |
Classes | Reference Data | Total | Producer’s Accuracy (%) | User’s Accuracy (%) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||||
1. Cr | 177 | 2 | - | 1 | 1 | 1 | - | - | - | - | - | 182 | 86.34 | 97.25 |
2. Or | 2 | 60 | 2 | - | - | - | 1 | - | - | - | - | 65 | 86.96 | 92.31 |
3. Fo | 1 | - | 90 | - | - | 1 | - | - | - | - | 2 | 94 | 91.84 | 95.74 |
4. Wa | 2 | - | - | 88 | 1 | 1 | - | 1 | - | - | - | 93 | 95.65 | 94.62 |
5. Ur | 2 | - | - | - | 95 | 5 | - | 1 | - | - | - | 103 | 74.22 | 92.23 |
6.Cr to Ur | 2 | - | - | - | 7 | 65 | 1 | 2 | 1 | - | - | 78 | 69.89 | 83.33 |
7. Or to Ur | - | 4 | - | 2 | 5 | - | 54 | - | - | - | - | 65 | 91.53 | 83.08 |
8. Wa to Ur | - | - | - | 1 | 18 | 6 | - | 38 | - | - | - | 63 | 90.48 | 60.32 |
9. Cr to Wa | 15 | - | - | - | - | 6 | - | - | 42 | 1 | - | 64 | 95.45 | 65.63 |
10. Cr to Or | 4 | - | - | - | - | 8 | 3 | - | 1 | 45 | - | 61 | 95.74 | 73.77 |
11. Fo to Or | - | 3 | 6 | - | 1 | - | - | - | - | 1 | 51 | 62 | 96.23 | 82.26 |
Total | 205 | 69 | 98 | 92 | 128 | 93 | 59 | 42 | 44 | 47 | 53 | 930 | -- | -- |
Overall accuracy = 86.56%; Kappa coefficient = 0.85 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Deng, J.; Huang, Y.; Chen, B.; Tong, C.; Liu, P.; Wang, H.; Hong, Y. A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images. Remote Sens. 2019, 11, 1230. https://doi.org/10.3390/rs11101230
Deng J, Huang Y, Chen B, Tong C, Liu P, Wang H, Hong Y. A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images. Remote Sensing. 2019; 11(10):1230. https://doi.org/10.3390/rs11101230
Chicago/Turabian StyleDeng, Jinsong, Yibo Huang, Binjie Chen, Cheng Tong, Pengbo Liu, Hongquan Wang, and Yang Hong. 2019. "A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images" Remote Sensing 11, no. 10: 1230. https://doi.org/10.3390/rs11101230
APA StyleDeng, J., Huang, Y., Chen, B., Tong, C., Liu, P., Wang, H., & Hong, Y. (2019). A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images. Remote Sensing, 11(10), 1230. https://doi.org/10.3390/rs11101230