A Novel Method of Monitoring Surface Subsidence Law Based on Probability Integral Model Combined with Active and Passive Remote Sensing Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.2. Probability Integration Method
2.3. Geometry Principle
2.4. UAV Subsidence Monitoring
2.5. Data Fusion Method
3. Results
3.1. Data Fusion Result
3.2. UAV and InSAR Result
4. Discussion
4.1. Comparative Analysis of Data from InSAR, UAV, and GNSS
4.2. Analysis of Observation Method and Subsidence Law
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | UAV | Camera | Course Overlap% | Lateral Overlap% | Row Height | Collection Date |
---|---|---|---|---|---|---|
1 | Trimble UX5 | SONY A5100 | 80 | 80 | 23 | 9 June 18 |
2 | 4 September 18 | |||||
3 | 16 October 18 | |||||
4 | 16 April 19 |
No. | Product | Beam Model | Polarization | Resolution/(m) | Acquisition Date | Pixel Center | Mean Incident Angle (°) |
---|---|---|---|---|---|---|---|
(Rng × Az) | Lat-Lng (°) | ||||||
1 | SLC | Wide Multi-look Fine | HH | 2.6 × 2.4 | 9 June 18 | 39.5841–110.5944 | 35.2230 |
2 | 27 July 18 | 39.5852–110.5950 | 35.2232 | ||||
3 | 20 August 18 | 39.5851–110.5961 | 35.2224 | ||||
4 | 24 November 18 | 39.591–110.5977 | 35.2128 | ||||
5 | 11 January 19 | 39.5892–110.5969 | 35.2129 | ||||
6 | 4 February 19 | 39.5627–110.5903 | 35.2124 | ||||
7 | 28 February 19 | 39.5729–110.5952 | 35.2165 | ||||
8 | 24 March 19 | 39.5899–110.5995 | 35.2207 | ||||
9 | 17 April 19 | 39.5880–110.5955 | 35.2223 |
No. | InSAR (m) | UAV (m) | Fusion (m) | GNSS (m) | InSAR/GNSS (m) | UAV/GNSS (m) | Fusion/GNSS (m) |
---|---|---|---|---|---|---|---|
1 | −0.051 | −0.042 | −0.187 | −0.174 | −0.123 | −0.132 | 0.013 |
2 | −0.062 | −1.158 | −1.409 | −1.304 | −1.242 | −0.146 | 0.105 |
3 | −0.106 | −1.297 | −1.495 | −1.388 | −1.282 | −0.091 | 0.107 |
4 | −0.152 | −2.52 | −2.628 | −2.542 | −2.39 | −0.022 | 0.086 |
5 | −0.098 | −0.096 | −0.154 | −0.111 | −0.013 | −0.015 | 0.043 |
6 | −0.113 | −0.475 | −0.561 | −0.507 | −0.394 | −0.032 | 0.054 |
7 | −0.034 | −0.091 | −0.156 | −0.077 | −0.043 | 0.014 | 0.079 |
8 | −0.131 | −0.01 | −0.284 | −0.164 | −0.033 | −0.154 | 0.12 |
9 | −0.178 | −2.131 | −2.529 | −2.323 | −2.145 | −0.192 | 0.206 |
10 | −0.150 | −2.646 | −2.724 | −2.668 | −2.518 | −0.022 | 0.056 |
11 | −0.047 | −1.817 | −1.925 | −1.857 | −1.81 | −0.04 | 0.068 |
12 | −0.087 | −1.235 | −1.291 | −1.146 | −1.059 | 0.089 | 0.145 |
Medium Error | 1.426 | 0.099 | 0.103 |
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Wang, R.; Wu, K.; He, Q.; He, Y.; Gu, Y.; Wu, S. A Novel Method of Monitoring Surface Subsidence Law Based on Probability Integral Model Combined with Active and Passive Remote Sensing Data. Remote Sens. 2022, 14, 299. https://doi.org/10.3390/rs14020299
Wang R, Wu K, He Q, He Y, Gu Y, Wu S. A Novel Method of Monitoring Surface Subsidence Law Based on Probability Integral Model Combined with Active and Passive Remote Sensing Data. Remote Sensing. 2022; 14(2):299. https://doi.org/10.3390/rs14020299
Chicago/Turabian StyleWang, Rui, Kan Wu, Qimin He, Yibo He, Yuanyuan Gu, and Shuang Wu. 2022. "A Novel Method of Monitoring Surface Subsidence Law Based on Probability Integral Model Combined with Active and Passive Remote Sensing Data" Remote Sensing 14, no. 2: 299. https://doi.org/10.3390/rs14020299