Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Description
2.2. Domain Adaptation Networks
2.2.1. The U-Net Architecture
2.2.2. The Domain Adaptation Network
2.2.3. The D-CORAL Domain Adaptation Network
2.3. Experimental Set-Up
3. Results
3.1. Unsupervised Domain Adaptation Results
3.2. Fine-Tuning Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. A Methodology to Produce the Historical Orthomosaics
Label | X Error (m) | Y Error (m) | Z Error (m) | XY Error (m) | XYZ Error (m) |
---|---|---|---|---|---|
point 1b | 3.414 | 9.482 | 10.163 | 10.078 | 14.313 |
point 2b * | −6.755 | 4.333 | −5.242 | 8.025 | 9.585 |
point 4b * | 11.369 | 0.919 | 15.110 | 11.406 | 18.932 |
point 5b * | −7.235 | 5.415 | 4.807 | 9.037 | 10.236 |
point 6b * | −9.505 | −1.061 | −15.532 | 9.565 | 18.240 |
point 7b * | −11.769 | −6.309 | −15.839 | 13.354 | 20.717 |
point 9b | −15.336 | −1.060 | 9.025 | 15.372 | 17.826 |
point 10b | 20.457 | 0.891 | 8.558 | 20.477 | 22.193 |
point 11b * | 3.163 | −3.832 | −0.283 | 4.969 | 4.977 |
point 12b * | 5.309 | 2.824 | 9.575 | 6.013 | 11.306 |
point 13b * | −11.498 | −7.404 | −1.221 | 13.675 | 13.730 |
point 14b * | 4.258 | −8.760 | −10.187 | 9.740 | 14.094 |
point 15b * | 14.127 | 4.565 | −8.930 | 14.846 | 17.325 |
point 16b * | −18.834 | −6.824 | −7.904 | 20.032 | 21.535 |
point 1 * | 2.478 | 3.885 | −8.516 | 4.608 | 9.683 |
point 2 * | −3.605 | −8.769 | 8.037 | 9.481 | 12.429 |
point 3 * | 12.600 | −14.801 | −7.462 | 19.438 | 20.821 |
point 4 * | 5.189 | −2.580 | 6.400 | 5.795 | 8.634 |
point 5 * | 4.878 | −3.134 | 11.871 | 5.798 | 13.211 |
point 6 * | 9.286 | 8.257 | 10.528 | 12.425 | 16.286 |
point 7 * | 15.700 | 8.438 | 10.178 | 17.823 | 20.525 |
point 8 * | 11.459 | 0.783 | −2.382 | 11.486 | 11.730 |
point 9 * | −18.172 | 12.862 | 11.192 | 22.263 | 24.918 |
point 10 * | −15.418 | 11.483 | −3.310 | 19.224 | 19.507 |
point 11 * | 0.231 | 2.820 | −4.672 | 2.829 | 5.462 |
point 12 * | −32.857 | 5.203 | −1.095 | 33.266 | 33.285 |
point 13 * | 12.522 | 7.157 | 5.794 | 14.423 | 15.543 |
point 14 | 24.354 | 13.152 | 13.609 | 27.679 | 30.843 |
point 15 | 15.121 | 12.907 | 5.236 | 19.881 | 20.559 |
point 16 | −18.571 | −1.010 | −22.021 | 18.598 | 28.824 |
point 17 | −14.467 | −19.705 | −26.199 | 24.446 | 35.833 |
point 18 * | −2.337 | −11.347 | 14.526 | 11.585 | 18.580 |
point 19 * | −1.907 | 3.032 | −7.031 | 3.581 | 7.890 |
point 20 | 0.885 | 14.277 | 3.106 | 14.305 | 14.638 |
point 21 | −4.874 | 12.142 | 1.021 | 13.084 | 13.124 |
point 22 | −4.813 | 4.648 | −9.204 | 6.691 | 11.379 |
point 23 | −0.185 | −9.206 | 16.397 | 9.207 | 18.806 |
point 24 | −10.286 | 7.173 | −1.423 | 12.540 | 12.620 |
point 25 | 9.475 | −5.874 | 14.731 | 11.148 | 18.474 |
point 26 | −7.180 | −10.746 | −6.214 | 12.924 | 14.340 |
point 27 | 1.830 | 27.020 | 8.350 | 27.082 | 28.340 |
point 28 | 0.531 | 3.849 | −1.587 | 3.886 | 4.198 |
point 29 | 4.043 | −9.259 | 2.476 | 10.103 | 10.402 |
point 30 | −0.248 | −4.221 | −11.690 | 4.228 | 12.432 |
point 31 | 8.532 | −33.427 | −4.353 | 34.499 | 34.772 |
point 32 | 6.098 | −8.682 | −14.070 | 10.609 | 17.622 |
point 33 | −9.640 | −16.103 | −1.320 | 18.768 | 18.815 |
point 34 | 5.560 | −9.205 | −2.927 | 10.754 | 11.145 |
point 35 | −10.319 | 5.718 | −19.248 | 11.797 | 22.576 |
point 36 | 7.716 | 7.628 | 11.264 | 10.850 | 15.639 |
point 37 | −3.609 | −4.374 | 0.014 | 5.671 | 5.671 |
RMSE | 11.267 | 10.171 | 10.253 | 15.178 | 18.317 |
RMSE * | 11.937 | 7.072 | 9.111 | 13.875 | 16.599 |
Label | X Error (m) | Y Error (m) | Z Error (m) | XY Error (m) | XYZ Error (m) |
---|---|---|---|---|---|
GCP01 | 5.921 | −1.088 | 2.568 | 6.020 | 6.545 |
GCP02 | 6.657 | −5.622 | −4.152 | 8.713 | 9.652 |
GCP03 | 3.288 | −0.270 | −4.614 | 3.299 | 5.672 |
GCP04 | −26.120 | 7.834 | 3.178 | 27.269 | 27.454 |
GCP05 | 2.794 | −3.783 | −0.755 | 4.703 | 4.763 |
GCP06 | 4.143 | 2.316 | 5.284 | 4.746 | 7.102 |
GCP07 | 2.000 | 0.381 | −1.497 | 2.036 | 2.527 |
GCP08 | −2.499 | 0.873 | 5.282 | 2.647 | 5.908 |
GCP09 | −1.990 | −0.082 | 0.872 | 1.992 | 2.174 |
GCP10 | 23.171 | 5.186 | −4.376 | 23.745 | 24.145 |
GCP11 | −4.471 | −2.118 | 3.156 | 4.947 | 5.868 |
GCP12 | −4.477 | −8.620 | −5.717 | 9.713 | 11.271 |
GCP13 | −7.450 | 5.992 | −3.027 | 9.560 | 10.028 |
GCP14 | −10.464 | −0.739 | 0.733 | 10.490 | 10.515 |
GCP15 | 5.092 | 2.185 | −4.333 | 5.541 | 7.034 |
GCP16 | 4.448 | −4.314 | 7.488 | 6.196 | 9.719 |
RMSE | 9.998 | 4.186 | 4.038 | 10.839 | 11.566 |
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METHOD | Source | Goma-Gisenyi | Bukavu |
---|---|---|---|
Target | Bukavu | Goma-Gisenyi | |
Target only (upper-bound) % | - | 91.28 | 94.50 |
DANN % | - | 61.30 | 74.78 |
D-CORAL % | - | 62.56 | 73.00 |
Source only (lower-bound) % | - | 62.04 | 72.54 |
- | - | - | U-Net (Upper-Bound) | DANN | D-CORAL | U-Net (Lower-Bound) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Goma-Gisenyi ->Bukavu | Bukavu (Target) | PA % | UA % | F1 % | PA % | UA % | F1 % | PA % | UA % | F1 % | PA % | UA % | F1 % | |
BD | Class 1 | 86.1 | 66.4 | 75 | 9.7 | 56.4 | 17 | 7.2 | 62.9 | 13 | 12.7 | 56.9 | 21 | |
HV | Class 2 | 97.1 | 94.5 | 96 | 61.8 | 53.7 | 58 | 63.0 | 53.9 | 58 | 65.7 | 53.3 | 59 | |
MBLV | Class 3 | 90.8 | 95.9 | 93 | 55.4 | 37.8 | 45 | 58.7 | 39.7 | 47 | 51.3 | 39.7 | 45 | |
Class 4 | 90.1 | 96.7 | 93 | 61.9 | 68.1 | 65 | 61.7 | 70.9 | 66 | 62.7 | 69.9 | 66 | ||
Class 5 | 92 | 88.6 | 90 | 74.5 | 78.1 | 76 | 77.2 | 78.2 | 78 | 74.9 | 75.7 | 75 | ||
Class 6 | 80.3 | 85.0 | 83 | 72.8 | 76.2 | 74 | 75.9 | 76.0 | 76 | 71.1 | 76.9 | 74 | ||
Bukavu->Goma-Gisenyi | Goma (Target) | - | - | - | - | - | - | - | - | - | - | - | - | |
BD | Class 1 | 79.6 | 59.2 | 68 | 19.6 | 4.8 | 8 | 13.5 | 7.97 | 10 | 9.1 | 2.4 | 4 | |
HV | Class 2 | 96.1 | 97.4 | 97 | 78.9 | 98.2 | 88 | 75.0 | 98.6 | 85 | 74.1 | 98.5 | 85 | |
MBLV | Class 3 | 90.2 | 93.9 | 92 | 25.1 | 59.6 | 35 | 26.5 | 57.5 | 36 | 27.0 | 55.5 | 36 | |
Class 4 | 92.3 | 89.8 | 91 | 86.5 | 44.1 | 58 | 87.2 | 42.1 | 57 | 85.5 | 41.7 | 56 | ||
Class 5 | 92.4 | 88.8 | 91 | 88.4 | 69.8 | 78 | 88.7 | 67.9 | 77 | 90.5 | 68.2 | 78 | ||
Class 6 | 98.2 | 93.2 | 96 | 81.8 | 86 | 84 | 82.8 | 84.4 | 84 | 84.1 | 86.7 | 85 |
- | Bukavu Target | |||||
---|---|---|---|---|---|---|
Number of Samples | 300 | 450 | 600 | |||
- | OA % | F1 % | OA % | F1 % | OA % | F1 % |
U-Net (upper bound- only target training) | 79.66 | 74.4 | 81.40 | 76.6 | 82.99 | 78.2 |
DANN (150 from source + rest from target) | 76.91 | 73.4 | 82.19 | 77.8 | 83.16 | 79 |
D-CORAL (150 from source + rest from target) | 78.78 | 73.8 | 80.67 | 76.4 | 82.27 | 77.6 |
U-Net (lower bound—only source) | 63.27 | 58.4 | 62.81 | 57.4 | 62.84 | 57.4 |
- | Goma-Gisenyi Target | |||||
---|---|---|---|---|---|---|
Number of Samples | 300 | 450 | 600 | |||
- | OA % | F1 % | OA % | F1 % | OA % | F1 % |
U-Net (upper bound- only target training) | 87.49 | 79.8 | 89.15 | 82.4 | 89.16 | 83.8 |
DANN (150 from source + rest from target) | 87.78 | 79.8 | 88.59 | 83 | 89.70 | 84.4 |
D-CORAL (150 from source + rest from target) | 86.94 | 80.4 | 88.94 | 84 | 89.17 | 83.6 |
U-Net (lower bound—only source) | 72.28 | 55.6 | 72.76 | 58 | 72.21 | 54 |
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Mboga, N.; D’Aronco, S.; Grippa, T.; Pelletier, C.; Georganos, S.; Vanhuysse, S.; Wolff, E.; Smets, B.; Dewitte, O.; Lennert, M.; et al. Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa. ISPRS Int. J. Geo-Inf. 2021, 10, 523. https://doi.org/10.3390/ijgi10080523
Mboga N, D’Aronco S, Grippa T, Pelletier C, Georganos S, Vanhuysse S, Wolff E, Smets B, Dewitte O, Lennert M, et al. Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa. ISPRS International Journal of Geo-Information. 2021; 10(8):523. https://doi.org/10.3390/ijgi10080523
Chicago/Turabian StyleMboga, Nicholus, Stefano D’Aronco, Tais Grippa, Charlotte Pelletier, Stefanos Georganos, Sabine Vanhuysse, Eléonore Wolff, Benoît Smets, Olivier Dewitte, Moritz Lennert, and et al. 2021. "Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa" ISPRS International Journal of Geo-Information 10, no. 8: 523. https://doi.org/10.3390/ijgi10080523
APA StyleMboga, N., D’Aronco, S., Grippa, T., Pelletier, C., Georganos, S., Vanhuysse, S., Wolff, E., Smets, B., Dewitte, O., Lennert, M., & Wegner, J. D. (2021). Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa. ISPRS International Journal of Geo-Information, 10(8), 523. https://doi.org/10.3390/ijgi10080523