scholarly journals Ground Deformation Analysis Using InSAR and Backpropagation Prediction with Influencing Factors in Erhai Region, China

2019 ◽  
Vol 11 (10) ◽  
pp. 2853 ◽  
Author(s):  
Yuyi Wang ◽  
Yahui Guo ◽  
Shunqiang Hu ◽  
Yong Li ◽  
Jingzhe Wang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Influencing Factors ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Continuous Increase ◽  
Building Area ◽  
Mean Square Errors ◽  
Cumulative Precipitation ◽  
Aperture Radar

The long continuity of Interferometric Synthetic Aperture Radar (InSAR) can provide high space and resolution data for ground deformation investigations. The ground deformation in this paper appeared in the city’s development, although it is close to the Erhai region, which is different from a water-deficient city. Therefore, the analysis and prediction of ground deformation using a new method is required. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) images from 2015 to 2018 were used to study the characteristics of ground deformation in the Erhai region using the Small Baseline Subset Interferometric SAR (SBAS-InSAR) technique. The results were cross-validated using ascending and descending direction images to ensure the accuracy. In addition, the results showed that there was little ground deformation in the northern part of the Erhai region, while there was obvious ground deformation in the southern part. Four influencing factors—including the building area, water level, cumulative precipitation, and cumulative temperature of the southern Erhai region—were used together to predict the cumulative ground deformation using back-propagation (BP). The R of all the involved data was 0.966, and the root mean square errors (RMSEs) between the simulated values using BP and the true measured values were 3.063, 1.003, and 1.119, respectively. The results showed that BP has great potential in predicting the change tendency of ground deformation with high precision. The main reason for ground deformation is the continuous increase of building area; the water level followed. The cumulative precipitation and cumulative temperature are the reasons for the seasonal ground deformation. Some countermeasures and suggestions are given to face the challenge of serious ground deformation.

scholarly journals Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series

2014 ◽  
Vol 41 (17) ◽  
pp. 6123-6130 ◽  
Author(s):  
Sergey V. Samsonov ◽  
Alexander P. Trishchenko ◽  
Kristy Tiampo ◽  
Pablo J. González ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Aperture Radar

scholarly journals Multi-Sensor InSAR Analysis of Progressive Land Subsidence over the Coastal City of Urayasu, Japan

2018 ◽  
Vol 10 (8) ◽  
pp. 1304 ◽  
Author(s):  
Yusupujiang Aimaiti ◽  
Fumio Yamazaki ◽  
Wen Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Survey Data ◽  
Land Subsidence ◽  
Ground Deformation ◽  
Tohoku Earthquake ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
The 2011 Tohoku Earthquake ◽  
L Band ◽  
Aperture Radar

In earthquake-prone areas, identifying patterns of ground deformation is important before they become latent risk factors. As one of the severely damaged areas due to the 2011 Tohoku earthquake in Japan, Urayasu City in Chiba Prefecture has been suffering from land subsidence as a part of its land was built by a massive land-fill project. To investigate the long-term land deformation patterns in Urayasu City, three sets of synthetic aperture radar (SAR) data acquired during 1993–2006 from European Remote Sensing satellites (ERS-1/-2 (C-band)), during 2006–2010 from the Phased Array L-band Synthetic Aperture Radar onboard the Advanced Land Observation Satellite (ALOS PALSAR (L-band)) and from 2014–2017 from the ALOS-2 PALSAR-2 (L-band) were processed by using multitemporal interferometric SAR (InSAR) techniques. Leveling survey data were also used to verify the accuracy of the InSAR-derived results. The results from the ERS-1/-2, ALOS PALSAR and ALOS-2 PALSAR-2 data processing showed continuing subsidence in several reclaimed areas of Urayasu City due to the integrated effects of numerous natural and anthropogenic processes. The maximum subsidence rate of the period from 1993 to 2006 was approximately 27 mm/year, while the periods from 2006 to 2010 and from 2014 to 2017 were approximately 30 and 18 mm/year, respectively. The quantitative validation results of the InSAR-derived deformation trend during the three observation periods are consistent with the leveling survey data measured from 1993 to 2017. Our results further demonstrate the advantages of InSAR measurements as an alternative to ground-based measurements for land subsidence monitoring in coastal reclaimed areas.

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

2014 ◽  
Vol 150 ◽  
pp. 66-81 ◽  
Author(s):  
Jin-Woo Kim ◽  
Zhong Lu ◽  
John W. Jones ◽  
C.K. Shum ◽  
Hyongki Lee ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Freshwater Marsh ◽  
Synthetic Aperture ◽  
Radar Backscatter ◽  
L Band ◽  
Aperture Radar

scholarly journals Production-Induced Subsidence at the Los Humeros Geothermal Field Inferred from PS-InSAR

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Eszter Békési ◽  
Peter A. Fokker ◽  
Joana E. Martins ◽  
Jon Limberger ◽  
Damien Bonté ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Geothermal Field ◽  
Synthetic Aperture ◽  
Fluid Extraction ◽  
Volume Changes ◽  
Geomechanical Properties ◽  
Reservoir Compartmentalization ◽  
Aperture Radar

Surface deformation due to fluid extraction can be detected by satellite-based geodetic sensors, providing important insights on subsurface geomechanical properties. In this study, we use Differential Interferometric Synthetic Aperture Radar (DInSAR) observations to measure ground deformation due to fluid extraction at the Los Humeros Geothermal Field (Puebla, Mexico). Our main goal is to reveal the pressure distribution in the reservoir and to identify reservoir compartmentalization, which can be important aspects for optimizing the production of the field. The result of the PS-InSAR (Persistent Scatterer by Synthetic Aperture Radar Interferometry) analysis shows that the subsidence at the LHGF was up to 8 mm/year between April 2003 and March 2007, which is small relative to the produced volume of 5×106 m3/year. The subsidence pattern indicates that the geothermal field is controlled by sealing faults separating the reservoir into several blocks. To assess if this is the case, we relate surface movements with volume changes in the reservoir through analytical solutions for different types of nuclei of strain. We constrain our models with the movements of the PS points as target observations. Our models imply small volume changes in the reservoir, and the different nuclei of strain solutions differ only slightly. These findings suggest that the pressure within the reservoir is well supported and that reservoir recharge is taking place.

scholarly journals Long-Term Water Surface Area Monitoring and Derived Water Level Using Synthetic Aperture Radar (SAR) at Altevatn, a Medium-Sized Arctic Lake

2019 ◽  
Vol 11 (23) ◽  
pp. 2780 ◽  
Author(s):  
Hannah Vickers ◽  
Eirik Malnes ◽  
Kjell-Arild Høgda
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Lake Water ◽  
Clustering Algorithm ◽  
Independent Solution ◽  
Microwave Remote Sensing ◽  
Synthetic Aperture ◽  
Arctic Lake ◽  
Water Cover ◽  
Aperture Radar

Monitoring water storage in lakes and reservoirs is critical to water resource management, especially in a changing climate. Satellite microwave remote sensing offers a weather and light-independent solution for mapping water cover over large scales. We have used 13 years of synthetic aperture radar (SAR) data from three different sensors (Sentinel-1, RADARSAT-2, and Envisat advanced synthetic aperture radar (ASAR)) to develop a method for mapping surface water cover and thereby estimating the lake water extent (LWE). The method uses the unsupervised K-means clustering algorithm together with specific post-processing techniques to create binary maps of the water area. We have specifically tested and validated the method at Altevatn, a medium-sized arctic lake in Northern Norway, by using in-situ measurements of the water level. The multi-sensor SAR LWE time series were used in conjunction with the water level measurements to derive the lake hypsometry while at the same time quantifying the accuracy of our method. For Altevatn lake we estimated LWE with a root mean squared error (RMSE) of 0.89 km2 or 1.4% of the mean LWE, while the inferred lake water level (LWL) was associated with an RMSE of 0.40 m, or 2.5% of the maximum annual variation. We foresee that there is potential to further develop the algorithm by generalizing its use to other lakes worldwide and automating the process such that near real-time monitoring of LWE may be possible.

scholarly journals Two-Dimensional Ship Velocity Estimation Based on KOMPSAT-5 Synthetic Aperture Radar Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1474 ◽  
Author(s):  
Minyoung Back ◽  
Donghan Kim ◽  
Sang-Wan Kim ◽  
Joong-Sun Won
Keyword(s):  
Synthetic Aperture Radar ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Synthetic Aperture ◽  
Minimum Size ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Synthetic Aperture Radar Data ◽  
Mean Square Errors ◽  
Aperture Radar

Continuously accumulating information on vessels and their activities in coastal areas of interest is important for maintaining sustainable fisheries resources and coastal ecosystems. The speed, heading, sizes, and activities of vessels in certain seasons and at certain times of day are useful information for sustainable coastal management. This paper presents a two-dimensional vessel velocity estimation method using the KOMPSAT-5 (K5) X-band synthetic aperture radar (SAR) system and Doppler parameter estimation. The estimation accuracy was evaluated by two field campaigns in 2017 and 2018. The minimum size of the vessel and signal-to-clutter ratio (SCR) for optimum estimation were determined to be 20 m and 7.7 dB, respectively. The squared correlation coefficient R2 for vessel speed and heading angle were 0.89 and 0.97, respectively, and the root-mean-square errors of the speed and heading were 1.09 m/s (2.1 knots) and 17.9°, respectively, based on 19 vessels that satisfied the criteria of minimum size of vessel and SCR. Because the K5 SAR is capable of observing a selected coastal region every day by utilizing various modes, it is feasible to accumulate a large quantity of vessel data for coastal sea for eventual use in building a coastal traffic model.

scholarly journals The Extraction of Ocean Tidal Loading from ASAR Differential Interferograms

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 632 ◽  
Author(s):  
Wei Peng ◽  
Qijie Wang ◽  
Yunmeng Cao
Keyword(s):  
Synthetic Aperture Radar ◽  
The United States ◽  
Synthetic Aperture ◽  
Tectonic Deformation ◽  
Spatial Characteristics ◽  
Tide Model ◽  
Ocean Tidal Loading ◽  
Tidal Loading ◽  
Mean Square Errors ◽  
Aperture Radar

The spatiotemporal crustal non-tectonic deformation caused by ocean tidal loading (OTL) can reach the centimeters scale in coastal land areas. The temporal variation of the site OTL displacements can be estimated by the global positioning system (GPS) technique, but its spatial variation needs to be further determined. In this paper, in order to analyze the spatial characteristics of the OTL displacements, we propose a multi-scale decomposition method based on signal spatial characteristics to derive the OTL displacements from differential interferometric synthetic aperture radar (D-InSAR) measurements. The method was tested using long-term advanced synthetic aperture radar (ASAR) data and GPS reference site data from the Los Angeles Basin in the United States, and we compared the results with the FES2014b tide model. The experimental results showed that the spatial function of the OTL displacements in an ASAR image can be represented as a higher-order polynomial function, and the spatial trends of the OTL displacements determined by the InSAR and the GPS techniques are basically consistent with the FES2014b tide model. The root-mean-square errors of the differences between the spatial OTL displacements of these two methods and the FES2014b tide model are less than 0.8 mm. The results indicate that the OTL displacement extracted from InSAR data can accurately reflect the spatial characteristics of the OTL effect, which will help to improve the spatial resolution and accuracy of the OTL displacement in coastal areas.

Synthetic Aperture Radar Interferometry for Disaster Monitoring of Harbor Facilities

2017 ◽  
Vol 12 (3) ◽  
pp. 526-535 ◽  
Author(s):  
Ryo Natsuaki ◽  
◽  
Takuma Anahara ◽  
Tsuyoshi Kotoura ◽  
Yuudai Iwatsuka ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Ground Deformation ◽  
Volcanic Eruptions ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Disaster Monitoring ◽  
Hyogo Prefecture ◽  
Aperture Radar

In this paper, we present experimental results of the disaster monitoring of harbor facilities using spaceborne synthetic aperture radar interferometry (InSAR). The Advanced Land Observing Satellite-2 (ALOS-2 or DAICHI-2), operated by the Japan Aerospace Exploration Agency (JAXA), carries the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2). PALSAR-2 can observe disaster areas day and night, in any weather, at a resolution of approximately 3 m. ALOS-2 PALSAR-2 has been used to measure large-scale ground deformation e.g., after earthquakes and volcanic eruptions. However, its robustness for smaller targets, such as harbor facilities, has not yet been substantiated. Here, we measured the uplift of a breakwater model made of concrete armor units, and confirmed the sensor accuracy to be better than 2 cm standard deviation. We also analyzed the damage to the Nagata and Suma ports in Kobe city, Hyogo prefecture, Japan hit by the 11th Typhoon in 2014, and detected the damaged area using interferometric coherence analysis.

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