Urban land and infrastructure deformation monitoring by satellite radar interferometry

Transcription

1 Urban land and infrastructure deformation monitoring by satellite radar interferometry Lei Zhang and Xiaoli Ding Department of Land Surveying and Geo-Informatics (LSGI) The Hong Kong Polytechnic University Acknowledgement Allen Liang, Songbo Wu, Yanan Du and Shona Tang

2 Introduction InSAR Group at HKPolyU is working on Development of advanced InSAR processing algorithms to enhance the data quality, estimation accuracy and reliability, processing efficiency and technique applicability. Application of the developed InSAR technique to study the phenomena/events related to deformation/change associated with infrastructure instability and natural hazards. 2

3 Introduction Satellite Synthetic Aperture Radar Phase Phas e All-day and all-weather Large scale and spatial continuity High precision and no need of ground instruments Intensity Intensity 3

4 Introduction Spaceborne SAR Systems (Source:Alberto Moreira) 4

5 Introduction (Source:Alberto Moreira) 5

6 Introduction Pass 1 Pass 2 Ground deformation: 9 mm C band (~5.6cm) Phase phase shift: degrees Interferometric Synthetic Aperture Radar (InSAR): phase measurement 6

7 Introduction Phase image Amplitude image Image 1: Oct. 4, 1995 Image 2: Oct. 9, 1997 A 1 A φ 1 = 4π λ r 1 + ε 1 φ 2 = 4π λ r 2 + ε 2 7

8 Introduction Phase+amplitude images Interferometric Phase (phase difference): 4 ( r1 r2) 1 2 ( 1 2) Assume 1 2 4π(r 1 r 2 ሻ φ = φ 1 φ 2 = λ i i i i i i l, m topo, l, m defo, l, m atmo, l, m orbit, l, m noise, l, m N 2 8

9 Introduction 9

10 Introduction Underground activity Landslide Volcano Hilley et al., 2004, Science Pass 1Wicks et al., 2002, Science Pass 2 Earthquake Bawden et al., 2001, Science Massonnet et al., 1993, Nature Glacier Tectonics Goldstein et al., 1993, Science Wright et al., 2004, Science 10

11 Introduction InSAR measurements contains unwanted signals Error sources 11

12 TCPInSAR Temporarily Coherent Point InSAR - TCPInSAR Developed by InSAR group/polyu Unsupervised retrieval of ground deformation from radar data with high reliability and accuracy Wide applicability 12

13 TCPInSAR Du, Y.N., Zhang, L., Feng, G.C., Lu, Z., and Sun, Q. (2017). On the accuracy of topographic residuals retrieved by MTInSAR. IEEE Transactions on Geoscience and Remote Sensing. Chen, Z.W., Zhang, L., and Zhang, G. (2016). An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas. Sensors, 16(9), Zhang, L., Ding, X.L., Lu, Z. (2015), Ground deformation mapping by fusion of multi-temporal interferometric synthetic aperture radar images: a review, International Journal of Image and Data Fusion, DOI: / Zhang, L., Ding, X.L, Lu, Z., Jung, H.S., Hu, J., Feng, G.C. (2014), A novel multi-temporal InSAR model for joint estimation of deformation rates and orbital errors, IEEE Trans. Geos. Rem. Sens., 52(6): Zhang, L., Ding, X.L., and Lu, Z. (2013), Fusion of GPS and InSAR Measurements by Constrained Least Squares: an Alternative Way for the Suppression of Atmospheric Artifacts, 3rd IWIDF, Changbaishan, Jilin. Zhang, L., Lu, Z., Ding, X.L., Jung, H.S., Feng, G.C. and Lee, C.W. (2012) Mapping ground surface deformation using temporarily coherent point SAR interferometry: Application to Los Angeles Basin, Remote Sensing of Environments. 117, pp Zhang, L., Ding, X.L, Lu, Z. (2011) Ground settlement monitoring based on temporarily coherent points between two SAR acquisitions, ISPRS Journal of Photogrammetry and Remote Sensing, 66(1): Zhang, L., Ding, X.L., and Lu, Z. (2011), Modeling the PSInSAR time-series without phase unwrapping, IEEE Trans. Geos. Rem. Sens., 49(1): Zhang, L., Ding, X.L., and Lu, Z. (2011), Deformation rate estimation on changing landscapes using Temporarily Coherent Point InSAR, Fringe2011, Italy. 13

14 Applications Urban DEM reconstruction Data: TerraSAR-X Resolution: 3m Accuracy: sub-meter 14

15 DEM reconstruction over large areas by TCPInSAR 15

16 Applications Urban ground deformation mapping Area: Tianjin, China Period: to Data: 42 TerraSAR-X (3m) IFG:

17 Applications Urban ground deformation mapping Area: Shenzhen, China Period: Data: Cosmo-SkyMed (3m) Significant Subsidence: 17

18 Applications Urban ground deformation mapping Area: Kowloon, Hong Kong Period: Data: 80 Cosmo-SkyMed (3m) 18

19 Applications Reclaimed land monitoring 19

20 Applications Reclaimed land monitoring (one color cycle represents 1.83cm) 20

21 Applications Reclaimed land monitoring 21

22 Applications Reclaimed land settlement Datasets:: CSK (3m) 22

23 Applications Infrastructure stability monitoring 23

24 Applications Infrastructure stability Monitroing 24

25 Applications Natural hazard monitoring Data:L band ALOS/PALSAR data(>350 images) Period:

26 Applications Regional Surveillance 清境地区 26

27 Applications Natural hazard monitoring China Nepal Friendship Highway 27

28 Applications Natural hazards monitoring 28

29 Applications Natural hazards monitoring 29

30 Limitations However, InSAR is not a real-time monitoring tool and can only provide us 1D deformation map Solution: Integration with GNSS Anchor Monitoring System developed at LSGI/PolyU 30

31 Limitations However, InSAR is not a real-time monitoring tool and can only provide us 1D deformation map Integration with GNSS- Anchor Monitoring System Applications of Anchor Monitoring System 31

32 Conclusion Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. SAR has entered into a golden age. More than 15 spaceborne SAR sensors are being operated today and more than 10 new SAR systems will be launched within the next few years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring. Thanks to the advanced processing algorithms, InSAR technique is becoming more and more reliable and is qualified for routine deformation monitoring, especially over large areas. 32