scholarly journals Mapping and Characterizing Displacements of Landslides with InSAR and Airborne LiDAR Technologies: A Case Study of Danba County, Southwest China

2021 ◽  
Vol 13 (21) ◽  
pp. 4234
Author(s):  
Qiang Xu ◽  
Chen Guo ◽  
Xiujun Dong ◽  
Weile Li ◽  
Huiyan Lu ◽  
...  
Keyword(s):  
Surface Deformation ◽  
Deformation Monitoring ◽  
Airborne Lidar ◽  
Mountainous Area ◽  
Deformation Characteristics ◽  
Detection And Identification ◽  
Geomorphic Features ◽  
Sbas Insar ◽  
Surrounding Areas ◽  
And Control

Interferometric synthetic aperture radar (InSAR) technology is known as one of the most effective methods for active landslide identification and deformation monitoring in large areas, and thus it is conducive to preventing and mitigating the losses caused by landslides. However, great uncertainty inevitably exists due to influences of complex terrains, dense vegetations, and atmospheric interferences in the southwestern mountainous area of China, and this is associated with false or erroneous judgment during the process of landslide identification. In this study, a landslide identification method is put forward by integrating InSAR technology and airborne light detection and ranging (LiDAR) technology. Via this method, surface deformation characteristics detected by InSAR technology and micro-geomorphic features reflected by LiDAR technology were used to identify and map landslides of large areas. Herein, the method was applied to process 224 Sentinel-1 images covering Danba County and its surrounding areas (540 km2) from October 2014 to September 2020. Firstly, 44 active landslides with total areas of 59 km2 were detected by stacking InSAR technology. Then, major regions up to 135 km2 were validated by data gained from the airborne LiDAR technology. Particularly, several large landslides with lengths and/or widths of more than 2 km were found. Further, the precipitation data were integrated with the above results to analyze the temporal deformation characteristics of three typical landslides from major regions via SBAS InSAR technology. The key findings were as follows: (1) The combination of InSAR and LiDAR technologies could improve the accuracy of landslide detection and identification; (2) there was a significant correlation between temporal deformation characteristics of some landslides and monthly rainfall, with an obvious hysteretic effect existing between the initiation timing of rainfall and that of deformation; (3) the results of this study will be important guidance for the prevention and control of geological hazards in Danba County and areas with similar complex geomorphological conditions by helping effectively identify and map landslides.

scholarly journals Surface Deformation Monitoring of a Section of Gongyu Expressway Based on SBAS-InSAR Technology

2021 ◽  
Vol 233 ◽  
pp. 01149
Author(s):  
Ying Yang ◽  
Yifang Sun ◽  
Shihong Wu ◽  
Xuegang Dong ◽  
Hanyao Huang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Tibet Plateau ◽  
Seasonal Effect ◽  
Climate Conditions ◽  
Sar Data ◽  
Sbas Insar

It is difficult to monitor the surface deformation along the expressway for the critical climate conditions in Tibet plateau. In this paper, based on sentinel-1A SAR data, the surface deformation along the Gongyu expressway was tried to evaluate using time-series SBAS-InSAR method. The results indicate that the surface deformation in most regions is within the safe acquirement of the expressway. Moreover, the surface deformation indicates a strong seasonal effect. Finally, two special spots with dangerous surface deformation are identified along the expressway.

scholarly journals Characteristics of the Residual Surface Deformation of Multiple Abandoned Mined-Out Areas Based on a Field Investigation and SBAS-InSAR: A Case Study in Jilin, China

2020 ◽  
Vol 12 (22) ◽  
pp. 3752
Author(s):  
Donghui Chen ◽  
Huie Chen ◽  
Wen Zhang ◽  
Chen Cao ◽  
Kuanxing Zhu ◽  
...  
Keyword(s):  
Surface Deformation ◽  
Field Investigation ◽  
Kriging Interpolation ◽  
Deformation Characteristics ◽  
Entire Area ◽  
Mining Areas ◽  
Small Baseline Subset ◽  
Local Construction ◽  
Small Baseline ◽  
Sbas Insar

Residual surface deformation resulting from abandoned mined-out areas can lead to severe damage to ground structures (e.g., buildings and infrastructure in mining areas) and the local ecological environment. Long-term monitoring and analyses of surface deformation characteristics of abandoned mined-out areas are significant for preventing potential disasters. In this study, a detailed field investigation first was conducted in Ying’an and Baoshan coal mines located in Jilin Province, China, to survey mining-induced disasters in the mining areas. Based on the 40 Sentinel-1A images acquired from 14 February 2017 to 17 May 2020, small baseline subset interferometry synthetic aperture radar (SBAS-InSAR) technology was employed to obtain the time-series residual surface deformation. Validation of the SBAS-derived results is performed by comparing with the results obtained via leveling measurements. The root mean square error (RMSE) between SBAS-derived and leveling measurements results was found to be 1.144 mm, reflecting a fairly good agreement. Furthermore, the ordinary Kriging interpolation approach was adopted to obtain information on the deformation across the entire area. The spatial–temporal evolution characteristics of the derived subsidence bowls in multiple mined-out areas were revealed. The deformation characteristics for the abandoned mined-out areas in different periods were not completely consistent. Finally, the potential mechanism underlying the inconsistency in the subsidence associated with underground coal exploitation is analyzed. The findings of this study can provide insights into local construction and ecological improvement as well as guidance for the prediction of deformation in abandoned mined-out areas.

scholarly journals Ground deformation monitoring using RADARSAT-2 DInSAR-MSBAS at the Aquistore CO2 storage site in Saskatchewan (Canada)

2014 ◽  
Vol XL-1 ◽  
pp. 81-87
Author(s):  
M. Czarnogorska ◽  
S. Samsonov ◽  
D. White
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Deformation Monitoring ◽  
Airborne Lidar ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Storage Site ◽  
Monitoring Techniques ◽  
Aperture Radar

The research objectives of the Aquistore CO<sub>2</sub> storage project are to design, adapt, and test non-seismic monitoring methods for measurement, and verification of CO<sub>2</sub> storage, and to integrate data to determine subsurface fluid distributions, pressure changes and associated surface deformation. Aquistore site is located near Estevan in Southern Saskatchewan on the South flank of the Souris River and west of the Boundary Dam Power Station and the historical part of Estevan coal mine in southeastern Saskatchewan, Canada. Several monitoring techniques were employed in the study area including advanced satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) technique, GPS, tiltmeters and piezometers. The targeted CO<sub>2</sub> injection zones are within the Winnipeg and Deadwood formations located at > 3000 m depth. An array of monitoring techniques was employed in the study area including advanced satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) with established corner reflectors, GPS, tiltmeters and piezometers stations. We used airborne LIDAR data for topographic phase estimation, and DInSAR product geocoding. Ground deformation maps have been calculated using Multidimensional Small Baseline Subset (MSBAS) methodology from 134 RADARSAT-2 images, from five different beams, acquired during 20120612&ndash;20140706. We computed and interpreted nine time series for selected places. MSBAS results indicate slow ground deformation up to 1 cm/year not related to CO<sub>2</sub> injection but caused by various natural and anthropogenic causes.

scholarly journals Automatic Interferogram Selection for SBAS-InSAR Based on Deep Convolutional Neural Networks

2021 ◽  
Vol 13 (21) ◽  
pp. 4468
Author(s):  
Yufang He ◽  
Guangzong Zhang ◽  
Hermann Kaufmann ◽  
Guochang Xu
Keyword(s):  
Surface Deformation ◽  
Classical Method ◽  
Local Deformation ◽  
Classification Performance ◽  
Selection Method ◽  
Deformation Monitoring ◽  
Image Feature ◽  
Deep Convolutional Neural Networks ◽  
High Quality ◽  
Sbas Insar

The small baseline subset of spaceborne interferometric synthetic aperture radar (SBAS-InSAR) technology has become a classical method for monitoring slow deformations through time series analysis with an accuracy in the centimeter or even millimeter range. Thereby, the selection of high-quality interferograms calculated is one of the key operations for the method, since it mainly determines the credibility of the deformation information. Especially in the era of big data, the demand for an automatic and effective selection method of high-quality interferograms in SBAS-InSAR technology is growing. In this paper, a deep convolutional neural network (DCNN) for automatichigh-quality interferogram selection is proposed that provides more efficient image feature extraction capabilities and a better classification performance. Therefore， the ResNet50 (a kind of DCNN) is used to identify and delete interferograms that are severely contaminated. According to simulation experiments and calculated Sentinel-1A data of Shenzhen, China, the proposed approach can significantly separate interferograms affected by turbulences in the atmosphere and by the decorrelation phase. The remarkable performance of the DCNN method is validated by the analysis of the standard deviation of interferograms and the local deformation information compared with the traditional selection method. It is concluded that DCNN algorithms can automatically select high quality interferogram for the SBAS-InSAR method and thus have a significant impact on the precision of surface deformation monitoring.

scholarly journals GMO Genetic Elements Thesaurus (GMO-GET): a controlled vocabulary for the consensus designation of introduced or modified genetic elements in genetically modified organisms

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Paulien Adamse ◽  
Emilie Dagand ◽  
Karen Bohmert-Tatarev ◽  
Daniela Wahler ◽  
Manoela Miranda ◽  
...  
Keyword(s):  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
Controlled Vocabulary ◽  
Data Systems ◽  
Genetic Elements ◽  
Related Information ◽  
Detection And Identification ◽  
Unique Approach ◽  
The Subject ◽  
And Control

Abstract Background Various databases on genetically modified organisms (GMOs) exist, all with their specific focus to facilitate access to information needed for, e. g., the assistance in risk assessment, the development of detection and identification strategies or inspection and control activities. Each database has its unique approach towards the subject. Often these databases use different terminology to describe the GMOs. For adequate GMO addressing and identification and exchange of GMO-related information it is necessary to use commonly agreed upon concepts and terminology. Result A hierarchically structured controlled vocabulary describing the genetic elements inserted into conventional GMOs, and GMOs developed by the use of gen(om)e-editing is presented: the GMO genetic element thesaurus (GMO-GET). GMO-GET can be used for GMO-related documentation, including GMO-related databases. It has initially been developed on the basis of two GMO databases, i.e. the Biosafety Clearing-House and the EUginius database. Conclusion The use of GMO-GET will enable consistent and compatible information (harmonisation), also allowing an accurate exchange of information between the different data systems and thereby facilitating their interoperability. GMO-GET can also be used to describe genetic elements that are altered in organisms obtained through current targeted genome-editing techniques.

scholarly journals Application of Sentinel-1 and-2 Images in Measuring the Deformation of Kuh-e-Namak (Dashti) Namakier, Iran

2021 ◽  
Vol 13 (4) ◽  
pp. 785
Author(s):  
Sen Zhang ◽  
Qigang Jiang ◽  
Chao Shi ◽  
Xitong Xu ◽  
Yundi Gong ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Rock Salt ◽  
Rainy Season ◽  
Surface Deformation ◽  
Meteorological Data ◽  
Dry Season ◽  
Synthetic Aperture ◽  
Advantages And Disadvantages ◽  
Sbas Insar ◽  
Aperture Radar

Kuh-e-Namak (Dashti) namakier is one of the most active salt diapirs along the Zagros fold–thrust belt in Iran. Its surface deformation should be measured to estimate its long-term kinematics. Ten Sentinel-2 optical images acquired between October 2016 and December 2019 were processed by using Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) method. Forty-seven Sentinel-1 ascending Synthetic Aperture Radar (SAR) images acquired between April 2017 and December 2019 were processed by using Small Baseline Subset Synthetic Aperture Radar Interferometry (SBAS-InSAR) method. The deformation of Kuh-e-Namak (Dashti) namakier was measured using both methods. Then, meteorological data were utilized to explore the relationship between the kinematics of the namakier and weather conditions and differences in macrodeformation behavior of various rock salt types. The advantages and disadvantages of COSI-Corr and SBAS-InSAR methods in measuring the deformation of the namakier were compared. The results show that: (1) The flank subsides in the dry season and uplifts in the rainy season, whereas the dome subsides in the rainy season and uplifts in the dry season. Under extreme rainfall conditions, the namakier experiences permanent plastic deformation. (2) The “dirty” rock salt of the namakier is more prone to flow than the “clean” rock salt in terms of macrodeformation behavior. (3) In the exploration of the kinematics of the namakier via the two methods, COSI-Corr is superior to SBAS-InSAR on a spatial scale, but the latter is superior to the former on a time scale.

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

scholarly journals Preliminary Identification of Geological Hazards from Songpinggou to Feihong in Mao County along the Minjiang River Using SBAS-InSAR Technique Integrated Multiple Spatial Analysis Methods

2021 ◽  
Vol 13 (3) ◽  
pp. 1017
Author(s):  
Kuanxing Zhu ◽  
Peihua Xu ◽  
Chen Cao ◽  
Lianjing Zheng ◽  
Yue Liu ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Surface Deformation ◽  
Hot Spot ◽  
Field Investigation ◽  
Geometric Distortion ◽  
Disaster Prevention ◽  
Geological Hazards ◽  
Visibility Analysis ◽  
Preliminary Identification ◽  
Sbas Insar

Landslides and collapses are common geological hazards in mountainous areas, posing significant threats to the lives and property of residents. Therefore, early identification of disasters is of great significance for disaster prevention. In this study, we used Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to process C-band Sentinel-1A images to monitor the surface deformation from Songpinggou to Feihong in Maoxian County, Sichuan Province. Visibility analysis was used to remove the influence of geometric distortion on the SAR images and retain deformation information in the visible area. Hot spot and kernel density analyses were performed on the deformation data, and 18 deformation clusters were obtained. Velocity and slope data were integrated, and 26 disaster areas were interpreted from the 18 deformation clusters, including 20 potential landslides and 6 potential collapses. A detailed field investigation indicated that potential landslides No. 6 and No. 8 had developed cracks and were severely damaged, with a high probability of occurrence. Potential collapse No. 22 had developed fissures, exposing a dangerous rock mass and posing significant threats to the lives and property of residents. This study shows that the proposed method that combines visibility analysis, InSAR deformation rates, and spatial analysis can quickly and accurately identify potential geological disasters and provide guidance for local disaster prevention and mitigation.

Survey and control of small mammal populations on two hardwood plantations in southern Ontario

1974 ◽  
Vol 50 (5) ◽  
pp. 181-185 ◽  
Author(s):  
Andrew Radvanyi
Keyword(s):  
Small Mammal ◽  
Late Summer ◽  
Control Measures ◽  
Effective Control ◽  
Southern Ontario ◽  
Live Trapping ◽  
Surrounding Areas ◽  
And Control ◽  
Rodent Populations ◽  
Ingredient Cost

Live trapping and tagging methods were employed to assess small mammal populations within two hardwood plantations in southern Ontario. Excessive girdling damage in past years to young planted trees necessitated an evaluation of rodent populations and development of effective control measures. The application of an anticoagulant rodenticide to oat groats bait broadcast over the study area at an ingredient cost of approximately three dollars per acre virtually wiped out the small mammals. Reinvasion from surrounding areas was, however, fairly rapid, particularly during late summer. Further research on longer term control measures using poisoned bait feeder stations is recommended.

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