Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions
Abstract
:1. Introduction
2. SfM–TLS Data Fusion
3. Data and Methods
3.1. Study Areas
3.1.1. Belgian Study Area
3.1.2. Italian Study Area
3.2. Data Acquisition
3.2.1. SfM Surveys
3.2.2. TLS Surveys
3.3. Data Processing
3.3.1. SfM Processing
- GCP solution: The traditional solution of the GCP coordinates (evaluating the level of GCP uncertainty before including these data to avoid adversely affecting data accuracy [58]) was employed to scale and georeference the SfM-derived point cloud. This result was obtained by using a seven-parameter linear similarity transformation, through locating and manually marking GCPs on at least two photographs. In this case, some of the GCPs (one-third) were used as control points (CPs) to provide an independent measure of accuracy.
- PPK solution: The camera positions from PPK data encoded in the images were used. Here, no information on GCPs was exploited.
3.3.2. TLS Processing
3.4. Coregistration and Data Fusion
3.5. DTM Generation
3.6. Data Analysis
4. Results and Discussion
4.1. SfM Outputs
4.2. Coregistration Process
4.3. Data Fusion
4.4. DTM Error Assesment
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Study Area | Area Covered (ha) | Number of Images | Flight Height (m) | GSD (m) | Number of GCPs (CPs) 1 | GNSS Positional Accuracy (X, Y—Z) (m) |
---|---|---|---|---|---|---|
Belgium | 18 | 1219 | 20–45 | 0.005–0.015 | 40 (13) | <0.05 |
Italy | 3.5 | 632 | 25–35 | 0.006–0.008 | 56 (18) | 0.03–0.04 |
Study Area | Number of Scans | Mean Distance between Scans (m) | Accuracy (m) | Maximum Range Mode (m) | Scan Rate (Points/s) | Image Resolution (Mpixels) | Number of Targets |
---|---|---|---|---|---|---|---|
Belgium | 7 | 70 | 1.6 mm@10 | 120 | 1,000,000 | 4 | 20 |
Italy | 6 | 65 | 1.6 mm@10 | 270–570 1 | 250,000–500,000 1 | 4 | 16 |
Solution Type | Accuracy | Precision | Registration | ||||||
---|---|---|---|---|---|---|---|---|---|
MAE (m) | RMSE3D 1 (m) | SDE (m) | RMSE3D 1 (m) | Cameras 2 (m) | |||||
X | Y | Z | CPs | X | Y | Z | GCPs | ||
Italy | |||||||||
GCP | 0.013 | 0.014 | 0.019 | 0.034 | 0.010 | 0.011 | 0.014 | 0.031 | - |
Belgium | |||||||||
GCP | 0.014 | 0.015 | 0.052 | 0.070 | 0.013 | 0.011 | 0.025 | 0.068 | - |
PPK | 0.016 | 0.017 | 0.060 | 0.072 | 0.012 | 0.012 | 0.026 | - | 0.088 |
PPK + 1GCP | 0.016 | 0.016 | 0.058 | 0.071 | 0.012 | 0.012 | 0.025 | 0.072 | 0.088 |
M3C2 Distance | Non-Coregistered Point Clouds | Coregistered Point Clouds | ||||
---|---|---|---|---|---|---|
Accuracy | Precision | Accuracy | Precision | |||
Solution Type | MAE (m) | ME (m) | SDE (m) | MAE (m) | ME (m) | SDE (m) |
Italy | ||||||
GCP | 0.169 | 0.169 | 0.006 | 0.048 | −0.027 | 0.069 |
Belgium | ||||||
GCP | 0.209 | 0.218 | 0.120 | 0.080 | 0.018 | 0.102 |
PPK | 0.246 | −0.246 | 0.155 | 0.106 | 0.019 | 0.132 |
PPK + 1GCP | 0.219 | −0.208 | 0.177 | 0.069 | 0.004 | 0.089 |
Solution Type | MAE (m) | ME (m) | SDE (m) | RMSE (m) | Median 1 (m) | NMAD 2 (m) |
---|---|---|---|---|---|---|
Italy | ||||||
GCP | 0.024 | −0.017 | 0.026 | 0.040 | −0.022 | 0.035 |
Belgium | ||||||
GCP | 0.063 | −0.033 | 0.073 | 0.075 | −0.038 | 0.069 |
PPK | 0.095 | −0.095 | 0.035 | 0.101 | −0.079 | 0.099 |
PPK+1GCP | 0.063 | −0.062 | 0.034 | 0.080 | −0.054 | 0.078 |
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Cucchiaro, S.; Fallu, D.J.; Zhang, H.; Walsh, K.; Van Oost, K.; Brown, A.G.; Tarolli, P. Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions. Remote Sens. 2020, 12, 1946. https://doi.org/10.3390/rs12121946
Cucchiaro S, Fallu DJ, Zhang H, Walsh K, Van Oost K, Brown AG, Tarolli P. Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions. Remote Sensing. 2020; 12(12):1946. https://doi.org/10.3390/rs12121946
Chicago/Turabian StyleCucchiaro, Sara, Daniel J. Fallu, He Zhang, Kevin Walsh, Kristof Van Oost, Antony G. Brown, and Paolo Tarolli. 2020. "Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions" Remote Sensing 12, no. 12: 1946. https://doi.org/10.3390/rs12121946