Offline-Online Change Detection for Sentinel-1 InSAR Time Series

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, much information is lost by simply fitting a line through the time series. Thanks to regular acquisitions across most of the the world by the ESA Sentinel-1 satellite constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a simple statistical approach for detecting offsets and gradient changes in InSAR time series. Our key assumption is that 5 years of Sentinel-1 data is sufficient to calculate the population standard deviation of the detection variables. Our offset detector identifies statistically significant peaks in the first, second and third difference series. The gradient change detector identifies statistically significant movements in the second derivative series. We exploit the high spatial resolution of Sentinel-1 data and the spatial continuity of geophysical deformation signals to filter out false positive detections that arise due to signal noise. When combined with near-real time processing of InSAR data these detectors, particularly the gradient change, could be used to detect incipient ground deformation associated with geophysical phenomena, for example from landslides or volcanic eruptions.

Download Full-text

Offline-Online Change Detection for Sentinel-1 InSAR Time Series

Remote Sensing ◽

10.3390/rs13091656 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1656

Author(s):

Ekbal Hussain ◽

Alessandro Novellino ◽

Colm Jordan ◽

Luke Bateson

Keyword(s):

Time Series ◽

Real Time ◽

Ground Deformation ◽

Volcanic Eruptions ◽

Deformation Monitoring ◽

Real Time Processing ◽

Spatial Continuity ◽

Time Deformation ◽

Population Standard Deviation ◽

Gradient Change

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, much information is lost by simply fitting a line through the time series. Thanks to regular acquisitions across most of the the world by the ESA Sentinel-1 satellite constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a statistical approach for detecting offsets and gradient changes in InSAR time series. Our key assumption is that 5 years of Sentinel-1 data is sufficient to calculate the population standard deviation of the detection variables. Our offset detector identifies statistically significant peaks in the first, second and third difference series. The gradient change detector identifies statistically significant movements in the second derivative series. We exploit the high spatial resolution of Sentinel-1 data and the spatial continuity of geophysical deformation signals to filter out false positive detections that arise due to signal noise. When combined with near-real time processing of InSAR data these detectors, particularly the gradient change, could be used to detect incipient ground deformation associated with geophysical phenomena, for example from landslides or volcanic eruptions.

Download Full-text

Offline-Online Change Detection for Sentinel-1 InSAR Time Series

10.5194/egusphere-egu21-11673 ◽

2021 ◽

Author(s):

Alessandro Novellino ◽

Ekbal Hussain ◽

Colm Jordan ◽

Luke Bateson

Keyword(s):

Time Series ◽

Real Time ◽

Ground Deformation ◽

Volcanic Eruptions ◽

Deformation Monitoring ◽

Real Time Processing ◽

Spatial Continuity ◽

Time Deformation ◽

Population Standard Deviation ◽

Gradient Change

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, new tools are needed for automatically and regularly identifying changes in the time series. Thanks to regular acquisitions across most of the world by the ESA Sentinel-1 satellites constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a statistical approach for detecting offsets and gradient changes in InSAR time series. Our key assumption is that 5 years of Sentinel-1 data is sufficient to calculate the population standard deviation of the detection variables. Our offset detector identifies statistically significant peaks in the first, second and third difference series. The gradient change detector identifies statistically significant movements in the second derivative series. We exploit the high spatial resolution of Sentinel-1 data and the spatial continuity of geophysical deformation signals to filter out false positive detections that arise due to signal noise. When combined with near-real time processing of InSAR data these detectors, particularly the gradient change, could be used to detect incipient ground deformation associated with geohazards such as landslides or volcanic eruptions.

Download Full-text

Towards synergy of GNSS and InSAR mining deformation monitoring with Sentinel-1 data

10.5194/egusphere-egu21-11416 ◽

2021 ◽

Author(s):

Damian Tondaś ◽

Maya Ilieva ◽

Witold Rohm ◽

Jan Kapłon

Keyword(s):

Time Series ◽

Real Time ◽

Laser Scanning ◽

Large Scale ◽

Ground Deformation ◽

Dimensional Space ◽

Satellite Navigation ◽

Deformation Monitoring ◽

North East ◽

The Impact

The determination of ground deformation may be carried out by applying various measurement methods such as levelling, laser scanning, satellite navigation systems, Synthetic Aperture Radar (SAR) and many others. In this work, we focus on the comparison of the deformation effects measured by Global Navigation Satellite Systems (GNSS) and satellite Interferometric SAR (InSAR) methods in the Upper-Silesian coal mining region (SW Poland).An unquestionable advantage of GNSS technology is the possibility of continuous monitoring of deformations in three-dimensional space. Moreover, the evolution of real-time (RT) techniques such as: near real-time (NRT), ultra-fast NRT or RT allows to obtain a high precise position determination with a relatively slight latency (ranging from a few seconds to less than one hour). The limitation of the satellite navigation technology is the spatial range of the measurements. The deformation can only be observed at the point where the GNSS antenna is located. Furthermore, the acquisition, installation and maintenance of the equipment may also involve high costs.In contrast to the GNSS technique, the InSAR methods enable measurement of the large-scale subsidence areas with possibility to use free products and software (e.g. Sentinel-1 and SNAP). The large-scale InSAR investigations provide a better overview of local terrain changes. Unfortunately, InSAR methods also have some limitations related to data acquisition technology: &#160;<ul><li>a few days latency in acquiring a new image,</li> <li>insensitivity to changes in the northern component,</li> <li>acquiring deformation only in the LOS direction.</li> </ul>The main goal of this research is to analyse the deformation results obtained using GNSS and InSAR methods with respect to the capabilities and limitations of these two techniques. We investigated the level of agreement of eight GNSS and InSAR time series in areas with no subsidence, together with results acquired on seven regions of mining deformation where the maximum subsidence velocity exceeds 50 cm/year. The mean RMS time series fitting error obtained in subsidence basin is more than 5 cm and in non-deformed areas is equal to 2 cm. The study also investigated the effect of coherence threshold levels (0.3 &#247; 0.6) with introduction of the northern GNSS component on the InSAR decomposition process. Assuming the same GNSS deformation value in each directions (north, east, and up), the impact of the northern component was estimated as 10% of the total LOS subsidence.

Download Full-text

Subsidence Monitoring of Fill Area in Yan’an New District Based on Sentinel-1A Time Series Imagery

Remote Sensing ◽

10.3390/rs13153044 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3044

Author(s):

Mingjie Liao ◽

Rui Zhang ◽

Jichao Lv ◽

Bin Yu ◽

Jiatai Pang ◽

...

Keyword(s):

Time Series ◽

Large Scale ◽

Ground Deformation ◽

Dynamic Change ◽

Deformation Monitoring ◽

Chinese Loess Plateau ◽

Ground Subsidence ◽

Shanxi Province ◽

Environment Change ◽

Loess Area

In recent years, many cities in the Chinese loess plateau (especially in Shanxi province) have encountered ground subsidence problems due to the construction of underground projects and the exploitation of underground resources. With the completion of the world’s largest geotechnical project, called “mountain excavation and city construction,” in a collapsible loess area, the Yan’an city also appeared to have uneven ground subsidence. To obtain the spatial distribution characteristics and the time-series evolution trend of the subsidence, we selected Yan’an New District (YAND) as the specific study area and presented an improved time-series InSAR (TS-InSAR) method for experimental research. Based on 89 Sentinel-1A images collected between December 2017 to December 2020, we conducted comprehensive research and analysis on the spatial and temporal evolution of surface subsidence in YAND. The monitoring results showed that the YAND is relatively stable in general, with deformation rates mainly in the range of −10 to 10 mm/yr. However, three significant subsidence funnels existed in the fill area, with a maximum subsidence rate of 100 mm/yr. From 2017 to 2020, the subsidence funnels enlarged, and their subsidence rates accelerated. Further analysis proved that the main factors induced the severe ground subsidence in the study area, including the compressibility and collapsibility of loess, rapid urban construction, geological environment change, traffic circulation load, and dynamic change of groundwater. The experimental results indicated that the improved TS-InSAR method is adaptive to monitoring uneven subsidence of deep loess area. Moreover, related data and information would provide reference to the large-scale ground deformation monitoring and in similar loess areas.

Download Full-text

Cooperating the BDS, GPS, GLONASS and strong-motion observations for real-time deformation monitoring

Geophysical Journal International ◽

10.1093/gji/ggx099 ◽

2017 ◽

Vol 209 (3) ◽

pp. 1408-1417 ◽

Cited By ~ 12

Author(s):

Rui Tu ◽

Jinhai Liu ◽

Cuixian Lu ◽

Rui Zhang ◽

Pengfei Zhang ◽

...

Keyword(s):

Real Time ◽

Strong Motion ◽

Deformation Monitoring ◽

Time Deformation

Download Full-text

Measurement of the Thermal Expansion for Space Structures Using Fiber Bragg Grating Sensors and Displacement Measuring Interferometers

Smart Materials, Adaptive Structures and Intelligent Systems, Volume 1 ◽

10.1115/smasis2008-479 ◽

2008 ◽

Author(s):

Hong-Il Kim ◽

Lae-Hyong Kang ◽

Jae-Hung Han

Keyword(s):

Fiber Bragg Grating ◽

Real Time ◽

Deformation Monitoring ◽

Space Environment ◽

Space Structures ◽

Bragg Grating ◽

Environment Change ◽

Time Deformation ◽

Fiber Bragg Grating Sensors ◽

Fbg Sensors

Dimensional stability of the space structures, such as large telescope mirrors or metering substructures, is very important because even extremely small deformations of these structures might degrade the optical performances. Therefore, precise deformation data of the space structures according to environment change are required to design these structures correctly. Also, real-time deformation monitoring of these structures in space environment is demanded to verify whether these structures are properly designed or manufactured. FBG (fiber Bragg grating) sensors are applicable to real time monitoring of the space structure because they can be embedded onto the structures with minimal weight penalty. In this research, therefore, thermal deformation measurement system for the space structures, composed of FBG sensors for real time strain measurement and DMI (displacement measuring interferometers) for accurate specimen expansion data acquisition, is developed. Thermal strains measured by distributed FBG sensors are evaluated by the comparison with the strains obtained by highly accurate DMI.

Download Full-text