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Special Issue "Earth Observations for Geohazards"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 June 2016)

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Guest Editor
Prof. Dr. Zhenhong Li

School of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
Website | E-Mail
Phone: +44 (0) 191 208 5704
Interests: InSAR atmospheric correction models, advanced InSAR time series techniques, high-rate GNSS, landslides (slope instability), stability monitoring of man-made infrastructure
Guest Editor
Dr. Roberto Tomas

Department of Civil Engineering, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain
Website | E-Mail
Interests: land subsidence; landslides; InSAR; LiDAR; building monitoring

Special Issue Information

Dear Colleagues,

Geohazards cause enormous human and economic losses and disruption, which continue to grow worldwide. Earthquakes represent one of the most devastating geohazards in terms of human suffering and economic damage, but a major cause of casualties, infrastructural damage, and economic losses, is the secondary hazard of landslides. Volcanic eruptions also represent a significant proportion of geohazards, and major eruptions can modulate regional or global atmospheric composition and climate in detrimental ways. Land subsidence due to anthropogenic processes, such as extraction of groundwater, gas, oil, and coal, is another worldwide geohazard that affects wide areas, causing infrastructure damage and increasing flood risk. Earth Observations (EO) from space and aircraft, combined with complementary terrestrial observations and with physical models, have been used to monitor geohazards and are revolutionizing our understanding of how the Earth system works. An important aspect of space-based (and airborne) EO is that we can investigate areas in which ground observations are not possible due to physical or political constraints.

This Special Issue invites innovative EO methods and applications on monitoring and modeling geohazards. Submissions are encouraged to cover a broad range of topics, which may include, but are not limited to, the following activities:

• EO algorithm development, automation, implementation, and validation

• EO for crustal deformation and earthquake cycle

• EO and landslide hazards

• remote sensing volcano activities

• the use of EO for investigating fracking

• EO for mining subsidence

• groundwater related subsidence from EO

• EO and geohazard damage assessment

Prof. Zhenhong Li
Dr Roberto Tomas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SAR processing
  • interferometry
  • time series analysis
  • photogrammetry
  • multi-spectral
  • Global Navigation Satellite System (GNSS)
  • earthquake
  • landslide
  • volcanic eruption
  • fracking
  • mining subsidence
  • groundwater-related subsidence
  • damage assessment

Published Papers (44 papers)

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Editorial

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Open AccessEditorial Earth Observations for Geohazards: Present and Future Challenges
Remote Sens. 2017, 9(3), 194; doi:10.3390/rs9030194
Received: 22 February 2017 / Revised: 22 February 2017 / Accepted: 22 February 2017 / Published: 24 February 2017
Cited by 4 | PDF Full-text (918 KB) | HTML Full-text | XML Full-text
Abstract
Earth Observations (EO) encompasses different types of sensors (e.g., Synthetic Aperture Radar, Laser Imaging Detection and Ranging, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in
[...] Read more.
Earth Observations (EO) encompasses different types of sensors (e.g., Synthetic Aperture Radar, Laser Imaging Detection and Ranging, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO data have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works. This Special Issue presents a collection of scientific contributions focusing on innovative EO methods and applications for monitoring and modeling geohazards, consisting of four Sections: (1) earthquake hazards; (2) landslide hazards; (3) land subsidence hazards; and (4) new EO techniques and services. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Research

Jump to: Editorial

Open AccessArticle DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey
Remote Sens. 2017, 9(1), 83; doi:10.3390/rs9010083
Received: 30 June 2016 / Revised: 5 January 2017 / Accepted: 10 January 2017 / Published: 17 January 2017
Cited by 1 | PDF Full-text (33574 KB) | HTML Full-text | XML Full-text
Abstract
In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial
[...] Read more.
In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial sectors in Turkey. We present a multi-source data approach aimed at investigating the complex and fragile environment of this area which is heavily affected by groundwater drawdown and ground subsidence. In particular, in order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002–2010 period. The produced ground deformation maps and associated time-series allow us to detect a wide land subsidence extending for about 1200 km2 and measure vertical displacements reaching up to 10 cm in the observed time interval. DInSAR results, complemented with climatic, stratigraphic and piezometric data as well as with land-cover changes information, allow us to give more insights on the impact of climate changes and human activities on groundwater resources depletion and land subsidence. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China
Remote Sens. 2016, 8(11), 951; doi:10.3390/rs8110951
Received: 9 June 2016 / Revised: 6 November 2016 / Accepted: 8 November 2016 / Published: 16 November 2016
Cited by 2 | PDF Full-text (26592 KB) | HTML Full-text | XML Full-text
Abstract
High-intensity coal mining (large mining height, shallow mining depth, and rapid advancing) frequently causes large-scale ground damage within a short period of time. Understanding mining subsidence under high-intensity mining can provide a basis for mining-induced damage assessment, land remediation in a subsidence area,
[...] Read more.
High-intensity coal mining (large mining height, shallow mining depth, and rapid advancing) frequently causes large-scale ground damage within a short period of time. Understanding mining subsidence under high-intensity mining can provide a basis for mining-induced damage assessment, land remediation in a subsidence area, and ecological reconstruction in vulnerable ecological regions in Western China. In this study, the mining subsidence status of Shendong Coalfield was investigated and analyzed using two-pass differential interferometric synthetic aperture radar (DInSAR) technology based on high-resolution synthetic aperture radar data (RADARSAT-2 precise orbit, multilook fine, 5 m) collected from 20 January 2012 to June 2013. Surface damages in Shendong Coalfield over a period of 504 days under open-pit mining and underground mining were observed. Ground deformation of the high-intensity mining working faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield was monitored using small baseline subset (SBAS) InSAR technology. (1) DInSAR detected and located 85 ground deformation areas (including ground deformations associated with past-mining activity). The extent of subsidence in Shendong Coalfield presented a progressive increase at an average monthly rate of 13.09 km2 from the initial 54.98 km2 to 225.20 km2, approximately, which accounted for 7% of the total area of Shendong Coalfield; (2) SBAS-InSAR reported that the maximum cumulative subsidence area reached 5.58 km2 above the working faces 22201-1/2. The advance speed of ground destruction (7.9 m/day) was nearly equal to that of underground mining (8.1 m/day). Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements
Remote Sens. 2016, 8(11), 937; doi:10.3390/rs8110937
Received: 25 August 2016 / Revised: 4 November 2016 / Accepted: 7 November 2016 / Published: 10 November 2016
Cited by 7 | PDF Full-text (49569 KB) | HTML Full-text | XML Full-text
Abstract
Because of the advantages of low cost, large coverage and short revisit cycle, Landsat 8 images have been widely applied to monitor earth surface movements. However, there are few systematic studies considering the error source characteristics or the improvement of the deformation field
[...] Read more.
Because of the advantages of low cost, large coverage and short revisit cycle, Landsat 8 images have been widely applied to monitor earth surface movements. However, there are few systematic studies considering the error source characteristics or the improvement of the deformation field accuracy obtained by Landsat 8 image. In this study, we utilize the 2013 Mw 7.7 Balochistan, Pakistan earthquake to analyze error spatio-temporal characteristics and elaborate how to mitigate error sources in the deformation field extracted from multi-temporal Landsat 8 images. We found that the stripe artifacts and the topographic shadowing artifacts are two major error components in the deformation field, which currently lack overall understanding and an effective mitigation strategy. For the stripe artifacts, we propose a small spatial baseline (<200 m) method to avoid the stripe artifacts effect on the deformation field. We also propose a small radiometric baseline method to reduce the topographic shadowing artifacts and radiometric decorrelation noises. Those performances and accuracy evaluation show that these two methods are effective in improving the precision of deformation field. This study provides the possibility to detect subtle ground movement with higher precision caused by earthquake, melting glaciers, landslides, etc., with Landsat 8 images. It is also a good reference for error source analysis and corrections in deformation field extracted from other optical satellite images. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery
Remote Sens. 2016, 8(11), 887; doi:10.3390/rs8110887
Received: 30 June 2016 / Revised: 9 October 2016 / Accepted: 24 October 2016 / Published: 27 October 2016
Cited by 3 | PDF Full-text (4860 KB) | HTML Full-text | XML Full-text
Abstract
Compared with optical sensors, Synthetic Aperture Radar (SAR) can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST), whose azimuth resolution
[...] Read more.
Compared with optical sensors, Synthetic Aperture Radar (SAR) can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST), whose azimuth resolution was improved to 0.24 m, was introduced for various applications. This data source made it possible to extract detailed information from individual buildings. In this paper, we present a new concept for individual building damage assessment using a post-event sub-meter very high resolution (VHR) SAR image and a building footprint map. With the building footprint map, the original footprints of buildings can be located in the SAR image. Based on the building imaging analysis of a building in the SAR image, the features in the building footprint can be extracted to identify standing and collapsed buildings. Three machine learning classifiers, including random forest (RF), support vector machine (SVM) and K-nearest neighbor (K-NN), are used in the experiments. The results show that the proposed method can obtain good overall accuracy, which is above 80% with the three classifiers. The efficiency of the proposed method is demonstrated based on samples of buildings using descending and ascending sub-meter VHR ST images, which were all acquired from the same area in old Beichuan County, China. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessFeature PaperArticle InSAR Observation and Numerical Modeling of the Earth-Dam Displacement of Shuibuya Dam (China)
Remote Sens. 2016, 8(10), 877; doi:10.3390/rs8100877
Received: 30 June 2016 / Revised: 19 September 2016 / Accepted: 13 October 2016 / Published: 23 October 2016
Cited by 1 | PDF Full-text (13628 KB) | HTML Full-text | XML Full-text
Abstract
How to accurately determine the mechanical parameters of rockfill is one of the key issues of concrete-face rockfill dams. Parameter back-analysis using internal or external monitoring data has been proven to be an efficient way to solve this problem. However, traditional internal or
[...] Read more.
How to accurately determine the mechanical parameters of rockfill is one of the key issues of concrete-face rockfill dams. Parameter back-analysis using internal or external monitoring data has been proven to be an efficient way to solve this problem. However, traditional internal or external monitoring methods have limitations in efficiency and long-term monitoring. In this paper, the displacement of the Shuibuya concrete-face rockfill dam is monitored by the space-borne Interferometric Synthetic Aperture Radar (InSAR) time series method. Using the InSAR results and the finite element method, the back-analysis of the mechanical parameters of the rockfill dam is investigated, and the back-analysis results of InSAR and levelling are compared. A high correlation of 0.99 for the displacement results generated from InSAR and the levelling offers good agreement between the two methods. The agreement provides confidence that the external InSAR monitoring measurement allows producing a reliable back-analysis and captures the displacement properties of the dam. Based on the identified parameters from the InSAR results, the dam displacement is predicted. The prediction of the maximum settlement of the dam is 2.332 m by the end of 2020, according to the dam displacement characteristics, which agrees well with the results derived from the recorded internal monitoring data. Therefore, the external monitoring results from the InSAR observation can be used as a supplement for traditional monitoring methods to analyse the parameters of the dam. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring
Remote Sens. 2016, 8(10), 874; doi:10.3390/rs8100874
Received: 29 June 2016 / Revised: 9 October 2016 / Accepted: 17 October 2016 / Published: 23 October 2016
Cited by 3 | PDF Full-text (9363 KB) | HTML Full-text | XML Full-text
Abstract
Early detection and early warning are of great importance in giant landslide monitoring because of the unexpectedness and concealed nature of large-scale landslides. In China, the western mountainous areas are prone to landslides and feature many giant complex landslides, especially following the Wenchuan
[...] Read more.
Early detection and early warning are of great importance in giant landslide monitoring because of the unexpectedness and concealed nature of large-scale landslides. In China, the western mountainous areas are prone to landslides and feature many giant complex landslides, especially following the Wenchuan Earthquake in 2008. This work concentrates on a new technique, known as the “hybrid-SAR technique”, that combines both phase-based and amplitude-based methods to detect and monitor large-scale landslides in Li County, Sichuan Province, southwestern China. This work aims to develop a robust methodological approach to promptly identify diverse landslides with different deformation magnitudes, sliding modes and slope geometries, even when the available satellite data are limited. The phase-based and amplitude-based techniques are used to obtain the landslide displacements from six TerraSAR-X Stripmap descending scenes acquired from November 2014 to March 2015. Furthermore, the application circumstances and influence factors of hybrid-SAR are evaluated according to four aspects: (1) quality of terrain visibility to the radar sensor; (2) landslide deformation magnitude and different sliding mode; (3) impact of dense vegetation cover; and (4) sliding direction sensitivity. The results achieved from hybrid-SAR are consistent with in situ measurements. This new hybrid-SAR technique for complex giant landslide research successfully identified representative movement areas, e.g., an extremely slow earthflow and a creeping region with a displacement rate of 1 cm per month and a typical rotational slide with a displacement rate of 2–3 cm per month downwards and towards the riverbank. Hybrid-SAR allows for a comprehensive and preliminary identification of areas with significant movement and provides reliable data support for the forecasting and monitoring of landslides. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy
Remote Sens. 2016, 8(10), 852; doi:10.3390/rs8100852
Received: 15 July 2016 / Revised: 18 August 2016 / Accepted: 11 October 2016 / Published: 20 October 2016
Cited by 2 | PDF Full-text (23765 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a methodology taking advantage of the GPOD-SBAS service to study the surface deformation information over high mountain regions. Indeed, the application of the advanced DInSAR over the arduous regions represents a demanding task. We implemented an iterative selection procedure of
[...] Read more.
This paper presents a methodology taking advantage of the GPOD-SBAS service to study the surface deformation information over high mountain regions. Indeed, the application of the advanced DInSAR over the arduous regions represents a demanding task. We implemented an iterative selection procedure of the most suitable SAR images, aimed to preserve the largest number of SAR scenes, and the fine-tuning of several advanced configuration parameters. This method is aimed at minimizing the temporal decorrelation effects, principally due to snow cover, and maximizing the number of coherent targets and their spatial distribution. The methodology is applied to the Valle d’Aosta (VDA) region, Northern Italy, an alpine area characterized by high altitudes, complex morphology, and susceptibility to different mass wasting phenomena. The approach using GPOD-SBAS allows for the obtainment of mean deformation velocity maps and displacement time series relative to the time period from 1992 to 2000, relative to ESR-1/2, and from 2002 to 2010 for ASAR-Envisat. Our results demonstrate how the DInSAR application can obtain reliable information of ground displacement over time in these regions, and may represent a suitable instrument for natural hazards assessment. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake
Remote Sens. 2016, 8(10), 868; doi:10.3390/rs8100868
Received: 5 August 2016 / Revised: 26 September 2016 / Accepted: 17 October 2016 / Published: 20 October 2016
Cited by 4 | PDF Full-text (9400 KB) | HTML Full-text | XML Full-text
Abstract
Remote sensing continues to be an invaluable tool in earthquake damage assessments and emergency response. This study evaluates the effectiveness of multilayer feedforward neural networks, radial basis neural networks, and Random Forests in detecting earthquake damage caused by the 2010 Port-au-Prince, Haiti 7.0
[...] Read more.
Remote sensing continues to be an invaluable tool in earthquake damage assessments and emergency response. This study evaluates the effectiveness of multilayer feedforward neural networks, radial basis neural networks, and Random Forests in detecting earthquake damage caused by the 2010 Port-au-Prince, Haiti 7.0 moment magnitude (Mw) event. Additionally, textural and structural features including entropy, dissimilarity, Laplacian of Gaussian, and rectangular fit are investigated as key variables for high spatial resolution imagery classification. Our findings show that each of the algorithms achieved nearly a 90% kernel density match using the United Nations Operational Satellite Applications Programme (UNITAR/UNOSAT) dataset as validation. The multilayer feedforward network was able to achieve an error rate below 40% in detecting damaged buildings. Spatial features of texture and structure were far more important in algorithmic classification than spectral information, highlighting the potential for future implementation of machine learning algorithms which use panchromatic or pansharpened imagery alone. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques
Remote Sens. 2016, 8(10), 837; doi:10.3390/rs8100837
Received: 30 June 2016 / Revised: 20 September 2016 / Accepted: 29 September 2016 / Published: 13 October 2016
Cited by 4 | PDF Full-text (52269 KB) | HTML Full-text | XML Full-text
Abstract
This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many
[...] Read more.
This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many environmental applications like landslide research. The methodology starts with the execution of UAV flights to acquire very high resolution images, which are oriented and georeferenced by means of aerial triangulation, bundle block adjustment and Structure from Motion (SfM) techniques, using ground control points (GCPs) as well as points transferred between flights. After Digital Surface Models (DSMs) and orthophotographs were obtained, both differential models and displacements at DSM check points between campaigns were calculated. Vertical and horizontal displacements in the range of a few decimeters to several meters were respectively measured. Finally, as the landslide occurred in an olive grove which presents a regular pattern, a semi-automatic approach to identifying and determining horizontal displacements between olive tree centroids was also developed. In conclusion, the study shows that landslide monitoring can be carried out with the required accuracy—in the order of 0.10 to 0.15 m—by means of the combination of non-invasive techniques such as UAV, photogrammetry and geographic information system (GIS). Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake
Remote Sens. 2016, 8(9), 759; doi:10.3390/rs8090759
Received: 14 July 2016 / Revised: 27 August 2016 / Accepted: 9 September 2016 / Published: 14 September 2016
Cited by 1 | PDF Full-text (12684 KB) | HTML Full-text | XML Full-text
Abstract
Remote sensing (RS) images play a significant role in disaster emergency response. Web2.0 changes the way data are created, making it possible for the public to participate in scientific issues. In this paper, an experiment is designed to evaluate the reliability of crowdsourcing
[...] Read more.
Remote sensing (RS) images play a significant role in disaster emergency response. Web2.0 changes the way data are created, making it possible for the public to participate in scientific issues. In this paper, an experiment is designed to evaluate the reliability of crowdsourcing buildings collapse assessment in the early time after an earthquake based on aerial remote sensing image. The procedure of RS data pre-processing and crowdsourcing data collection is presented. A probabilistic model including maximum likelihood estimation (MLE), Bayes’ theorem and expectation-maximization (EM) algorithm are applied to quantitatively estimate the individual error-rate and “ground truth” according to multiple participants’ assessment results. An experimental area of Yushu earthquake is provided to present the results contributed by participants. Following the results, some discussion is provided regarding accuracy and variation among participants. The features of buildings labeled as the same damage type are found highly consistent. This suggests that the building damage assessment contributed by crowdsourcing can be treated as reliable samples. This study shows potential for a rapid building collapse assessment through crowdsourcing and quantitatively inferring “ground truth” according to crowdsourcing data in the early time after the earthquake based on aerial remote sensing image. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Second-Order Polynomial Equation-Based Block Adjustment for Orthorectification of DISP Imagery
Remote Sens. 2016, 8(8), 680; doi:10.3390/rs8080680
Received: 4 July 2016 / Revised: 12 August 2016 / Accepted: 17 August 2016 / Published: 22 August 2016
Cited by 1 | PDF Full-text (5914 KB) | HTML Full-text | XML Full-text
Abstract
Due to the lack of ground control points (GCPs) and parameters of satellite orbits, as well as the interior and exterior orientation parameters of cameras in historical declassified intelligence satellite photography (DISP) imagery, a second order polynomial equation-based block adjustment model is proposed
[...] Read more.
Due to the lack of ground control points (GCPs) and parameters of satellite orbits, as well as the interior and exterior orientation parameters of cameras in historical declassified intelligence satellite photography (DISP) imagery, a second order polynomial equation-based block adjustment model is proposed for orthorectification of DISP imagery. With the proposed model, 355 DISP images from four missions and five orbits are orthorectified, with an approximate accuracy of 2.0–3.0 m. The 355 orthorectified images are assembled into a seamless, full-coverage mosaic image map of the karst area of Guangxi, China. The accuracy of the mosaicked image map is within 2.0–4.0 m when compared to 78 checkpoints measured by Real–Time Kinematic (RTK) GPS surveys. The assembled image map will be delivered to the Guangxi Geological Library and released to the public domain and the research community. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis
Remote Sens. 2016, 8(8), 686; doi:10.3390/rs8080686
Received: 30 June 2016 / Revised: 5 August 2016 / Accepted: 16 August 2016 / Published: 22 August 2016
Cited by 6 | PDF Full-text (11998 KB) | HTML Full-text | XML Full-text
Abstract
Recent improvement to Advanced Differential Interferometric SAR (A-DInSAR) time series quality enhances the knowledge of various geohazards. Ground motion studies need an appropriate methodology to exploit the great potential contained in the A-DInSAR time series. Here, we propose a methodology to analyze multi-sensors
[...] Read more.
Recent improvement to Advanced Differential Interferometric SAR (A-DInSAR) time series quality enhances the knowledge of various geohazards. Ground motion studies need an appropriate methodology to exploit the great potential contained in the A-DInSAR time series. Here, we propose a methodology to analyze multi-sensors and multi-temporal A-DInSAR data for the geological interpretation of areas affected by land subsidence/uplift and seasonal movements. The methodology was applied in the plain area of the Oltrepo Pavese (Po Plain, Italy) using ERS-1/2 and Radarsat data, processed using the SqueeSAR™ algorithm, and covering time spans, respectively, from 1992 to 2000 and from 2003 to 2010. The test area is a representative site of the Po Plain, affected by various geohazards and characterized by moderate rates of motion, ranging from −10 to 4 mm/yr. Different components of motion were recognized: linear, non-linear, and seasonal deformational behaviors. Natural and man-induced processes were identified such as swelling/shrinkage of clayey soils, land subsidence due to load of new buildings, moderate tectonic uplift, and seasonal ground motion due to seasonal groundwater level variations. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks
Remote Sens. 2016, 8(8), 675; doi:10.3390/rs8080675
Received: 6 April 2016 / Revised: 25 July 2016 / Accepted: 15 August 2016 / Published: 20 August 2016
Cited by 3 | PDF Full-text (16851 KB) | HTML Full-text | XML Full-text
Abstract
The coordinated development of the Beijing-Tianjin-Hebei has become a national strategy with Beijing and Tianjin as twin engines driving the regional development. However, the Beijing-Tianjin-Hebei region has suffered dramatic ground subsidence during last two to three decades, mainly due to long-term groundwater withdrawal.
[...] Read more.
The coordinated development of the Beijing-Tianjin-Hebei has become a national strategy with Beijing and Tianjin as twin engines driving the regional development. However, the Beijing-Tianjin-Hebei region has suffered dramatic ground subsidence during last two to three decades, mainly due to long-term groundwater withdrawal. Although, annual spirit leveling has been conducted routinely in some parts of Beijing and Tianjin, and InSAR technique has also been used to monitor ground subsidence in some local areas of the region, there is a lack of a complete survey of ground subsidence over the whole region. In this paper, we report a research on mapping ground subsidence in the Beijing-Tianjin-Hebei region over a long time span from 1992 to 2014. Three SAR datasets from four satellites are used: ERS-1/2 SAR images from 1992 to 2000, ENVISAT ASAR images from 2003 to 2010, and RADARSAT-2 images from 2012 to 2014. An improved multi-temporal InSAR method, namely “Multiple-master Coherent Target Small-Baseline InSAR” (MCTSB-InSAR), has been developed to process the datasets. A unique feature of MCTSB-InSAR is the adjustment process useful for wide area monitoring which provides an integrated solution for both calibration of InSAR-derived deformation and the harmonization of the deformation estimates from overlapping SAR frames. Three maps of the subsidence rate corresponding to the three periods over the wide Beijing-Tianjin-Hebei region are generated, with respective accuracy of 8.7 mm/year (1992–2000), 4.7 mm/year (2003–2010), and 5.4 mm/year (2012–2014) validated by more than 120 leveling measurements. The spatial-temporal characteristics of the development of ground subsidence in Beijing and Tianjin are analyzed. This research represents a first-ever effort on mapping ground subsidence over very large area and over long time span in China. The result is of significance to serve the decision-making on ground subsidence mitigation in the Beijing-Tianjin-Hebei region. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys
Remote Sens. 2016, 8(8), 670; doi:10.3390/rs8080670
Received: 10 June 2016 / Revised: 10 August 2016 / Accepted: 16 August 2016 / Published: 19 August 2016
Cited by 2 | PDF Full-text (10328 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this paper, we propose an advanced methodology to perform three-dimensional (3D) Finite Element (FE) modeling to investigate the kinematical evolution of a slow landslide phenomenon. Our approach benefits from the effective integration of the available geological, geotechnical and satellite datasets to perform
[...] Read more.
In this paper, we propose an advanced methodology to perform three-dimensional (3D) Finite Element (FE) modeling to investigate the kinematical evolution of a slow landslide phenomenon. Our approach benefits from the effective integration of the available geological, geotechnical and satellite datasets to perform an accurate simulation of the landslide process. More specifically, we fully exploit the capability of the advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) technique referred to as the Small BAseline Subset (SBAS) approach to provide spatially dense surface displacement information. Subsequently, we analyze the physical behavior characterizing the observed landslide phenomenon by means of an inverse analysis based on an optimization procedure. We focus on the Ivancich landslide phenomenon, which affects a residential area outside the historical center of the town of Assisi (Central Italy). Thanks to the large amount of available information, we have selected this area as a representative case study highlighting the capability of advanced 3D FE modeling to perform effective risk analyses of slow landslide processes and accurate urban development planning. In particular, the FE modeling is constrained by using the data from 7 litho-stratigraphic cross-sections and 62 stratigraphic boreholes; and the optimization procedure is carried out using the SBAS-DInSAR retrieved results by processing 39 SAR images collected by the Cosmo-SkyMed (CSK) constellation in the 2009–2012 time span. The achieved results allow us to explore the spatial and temporal evolution of the slow-moving phenomenon and via comparison with the geomorphological data, to derive a synoptic view of the kinematical activity of the urban area affected by the Ivancich landslide. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas
Remote Sens. 2016, 8(8), 659; doi:10.3390/rs8080659
Received: 1 June 2016 / Revised: 5 August 2016 / Accepted: 10 August 2016 / Published: 17 August 2016
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Abstract
Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR)
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Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR) techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs), (high coherence features) to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process. Full article
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Open AccessArticle Coastal Subsidence Monitoring Associated with Land Reclamation Using the Point Target Based SBAS-InSAR Method: A Case Study of Shenzhen, China
Remote Sens. 2016, 8(8), 652; doi:10.3390/rs8080652
Received: 30 May 2016 / Revised: 27 July 2016 / Accepted: 5 August 2016 / Published: 13 August 2016
Cited by 4 | PDF Full-text (15955 KB) | HTML Full-text | XML Full-text
Abstract
Shenzhen, the first special economic zone of China, has witnessed earth-shaking changes since the late 1980s. In the past 35 years, about 80 km2 of land has been reclaimed from the sea in Shenzhen. In order to investigate coastal vertical land motions
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Shenzhen, the first special economic zone of China, has witnessed earth-shaking changes since the late 1980s. In the past 35 years, about 80 km2 of land has been reclaimed from the sea in Shenzhen. In order to investigate coastal vertical land motions associated with land reclamation, we proposed an elaborated Point Target (PT) based Small Baseline Subset InSAR (SBAS-InSAR) strategy to process an ENVISAT ASAR ascending and descending orbits dataset both acquired from 2007 to 2010. This new strategy can not only select high density PTs but also generate a reliable InSAR measurement with full spatial resolution. The inter-comparison between InSAR-derived deformation velocities from different orbits shows a good self-consistency of the results extracted by the elaborated PT-based SBAS-InSAR strategy. The InSAR measurements show that the reclaimed land is undergoing remarkable coastal subsidence (up to 25 mm/year), especially at the Shenzhen Airport, Bao’an Center, Qianhai Bay and Shenzhen Bay. By analyzing the results together with land reclamation evolution, we conclude that the ground deformation is expected to continue in the near future, which will amplify the regional sea level rise. Full article
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Open AccessArticle Time-Dependent Afterslip of the 2009 Mw 6.3 Dachaidan Earthquake (China) and Viscosity beneath the Qaidam Basin Inferred from Postseismic Deformation Observations
Remote Sens. 2016, 8(8), 649; doi:10.3390/rs8080649
Received: 30 June 2016 / Revised: 31 July 2016 / Accepted: 3 August 2016 / Published: 10 August 2016
Cited by 2 | PDF Full-text (6574 KB) | HTML Full-text | XML Full-text | Correction
Abstract
The 28 August 2009 Mw 6.3 Dachaidan (DCD) earthquake occurred at the Qaidam Basin’s northern side. To explain its postseismic deformation time series, the method of modeling them with a combination model of afterslip and viscoelastic relaxation is improved to simultaneously assess the
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The 28 August 2009 Mw 6.3 Dachaidan (DCD) earthquake occurred at the Qaidam Basin’s northern side. To explain its postseismic deformation time series, the method of modeling them with a combination model of afterslip and viscoelastic relaxation is improved to simultaneously assess the time-dependent afterslip and the viscosity. The coseismic slip model in the layered model is first inverted, showing a slip pattern close to that in the elastic half-space. The postseismic deformation time series can be explained by the combination model, with a total root mean square (RMS) misfit of 0.37 cm. The preferred time-dependent afterslip mainly occurs at a depth from the surface to about 9.1 km underground and increases with time, indicating that afterslip will continue after 28 July 2010. By 334 days after the main shock, the moment released by the afterslip is 0.91 × 1018 N∙m (Mw 5.94), approximately 24.3% of that released by the coseismic slip. The preferred lower bound of the viscosity beneath the Qaidam Basin’s northern side is 1 × 1019 Pa·s, close to that beneath its southern side. This result also indicates that the viscosity structure beneath the Tibet Plateau may vary laterally. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method
Remote Sens. 2016, 8(8), 624; doi:10.3390/rs8080624
Received: 2 May 2016 / Revised: 3 July 2016 / Accepted: 21 July 2016 / Published: 28 July 2016
Cited by 5 | PDF Full-text (10210 KB) | HTML Full-text | XML Full-text
Abstract
Landslide monitoring is important for geological disaster prevention, where Synthetic Aperture Radar (SAR) images have been widely used. Compared with the Interferometric SAR (InSAR) technique, intensity-based offset tracking methods (e.g., Normalized Cross-Correlation method) can overcome the limitation of InSAR’s maximum detectable displacement. The
[...] Read more.
Landslide monitoring is important for geological disaster prevention, where Synthetic Aperture Radar (SAR) images have been widely used. Compared with the Interferometric SAR (InSAR) technique, intensity-based offset tracking methods (e.g., Normalized Cross-Correlation method) can overcome the limitation of InSAR’s maximum detectable displacement. The normalized cross-correlation (NCC) method, based on single-channel SAR images, estimates azimuth and range displacement by using statistical correlation between the matching windows of two SAR images. However, the matching windows—especially for the boundary area of landslide—always contain pixels with different moving characteristics, affecting the precision of displacement estimation. Based on the advantages of polarimetric scattering properties, this paper proposes a fully polarimetric SAR (PolSAR) offset tracking method for improvement of the precision of landslide displacement estimation. The proposed method uses the normalized inner product (NIP) of the two temporal PolSAR Pauli scattering vectors to evaluate their similarity, then retrieve the surface displacement of the Slumgullion landslide located in southwestern Colorado, USA. A pair of L-band fully polarimetric SAR images acquired by the Jet Propulsion Laboratory’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected for experiment. The results show that the Slumgullion landslide’s moving velocity during the monitoring time ranges between 1.6–10.9 mm/d, with an average velocity of 6.3 mm/d. Compared with the classical NCC method, results of the proposed method present better performance in the sub-pixel estimation. Furthermore, it performs better when estimating displacement in the area around the landslide boundaries. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion
Remote Sens. 2016, 8(6), 519; doi:10.3390/rs8060519
Received: 3 May 2016 / Revised: 1 June 2016 / Accepted: 14 June 2016 / Published: 22 June 2016
Cited by 5 | PDF Full-text (13973 KB) | HTML Full-text | XML Full-text
Abstract
Determining the relationship between crustal movement and faulting in thrust belts is essential for understanding the growth of geological structures and addressing the proposed models of a potential earthquake hazard. A Mw 5.9 earthquake occurred on 21 January 2016 in Menyuan, NE Qinghai
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Determining the relationship between crustal movement and faulting in thrust belts is essential for understanding the growth of geological structures and addressing the proposed models of a potential earthquake hazard. A Mw 5.9 earthquake occurred on 21 January 2016 in Menyuan, NE Qinghai Tibetan plateau. We combined satellite interferometry from Sentinel-1A Terrain Observation with Progressive Scans (TOPS) images, historical earthquake records, aftershock relocations and geological data to determine fault seismogenic structural geometry and its relationship with the Lenglongling faults. The results indicate that the reverse slip of the 2016 earthquake is distributed on a southwest dipping shovel-shaped fault segment. The main shock rupture was initiated at the deeper part of the fault plane. The focal mechanism of the 2016 earthquake is quite different from that of a previous Ms 6.5 earthquake which occurred in 1986. Both earthquakes occurred at the two ends of a secondary fault. Joint analysis of the 1986 and 2016 earthquakes and aftershocks distribution of the 2016 event reveals an intense connection with the tectonic deformation of the Lenglongling faults. Both earthquakes resulted from the left-lateral strike-slip of the Lenglongling fault zone and showed distinct focal mechanism characteristics. Under the shearing influence, the normal component is formed at the releasing bend of the western end of the secondary fault for the left-order alignment of the fault zone, while the thrust component is formed at the restraining bend of the east end for the right-order alignment of the fault zone. Seismic activity of this region suggests that the left-lateral strike-slip of the Lenglongling fault zone plays a significant role in adjustment of the tectonic deformation in the NE Tibetan plateau. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling
Remote Sens. 2016, 8(6), 532; doi:10.3390/rs8060532
Received: 5 February 2016 / Revised: 24 May 2016 / Accepted: 14 June 2016 / Published: 22 June 2016
Cited by 1 | PDF Full-text (15942 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A Mw 7.1 earthquake struck the Eastern Anatolia, near the city of Van (Turkey), on 23 October 2011. We investigated the coseismic surface displacements using the InSAR technique, exploiting adjacent ENVISAT tracks and COSMO-SkyMed images. Multi aperture interferometry was also applied, measuring ground
[...] Read more.
A Mw 7.1 earthquake struck the Eastern Anatolia, near the city of Van (Turkey), on 23 October 2011. We investigated the coseismic surface displacements using the InSAR technique, exploiting adjacent ENVISAT tracks and COSMO-SkyMed images. Multi aperture interferometry was also applied, measuring ground displacements in the azimuth direction. We solved for the fault geometry and mechanism, and we inverted the slip distribution employing a numerical forward model that includes the available regional structural data. Results show a horizontally elongated high slip area (7–9 m) at 12–17 km depth, while the upper part of the fault results unruptured, enhancing its seismogenic potential. We also investigated the post-seismic phase acquiring most of the available COSMO-SkyMed, ENVISAT and TERRASAR-X SAR images. The computed afterslip distributions show that the shallow section of the fault underwent considerable aseismic slip during the early days after the mainshock, of tens of centimeters. Our results support the hypothesis of a seismogenic potential reduction within the first 8–10 km of the fault through the energy release during the post-seismic phase. Despite non-optimal data coverage and coherence issues, we demonstrate that useful information about the Van earthquake could still be retrieved from SAR data through detailed analysis. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Source Parameters of the 2003–2004 Bange Earthquake Sequence, Central Tibet, China, Estimated from InSAR Data
Remote Sens. 2016, 8(6), 516; doi:10.3390/rs8060516
Received: 23 March 2016 / Revised: 3 June 2016 / Accepted: 14 June 2016 / Published: 18 June 2016
Cited by 2 | PDF Full-text (40326 KB) | HTML Full-text | XML Full-text
Abstract
A sequence of Ms ≥ 5.0 earthquakes occurred in 2003 and 2004 in Bange County, Tibet, China, all with similar depths and focal mechanisms. However, the source parameters, kinematics and relationships between these earthquakes are poorly known because of their moderately-sized magnitude and
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A sequence of Ms ≥ 5.0 earthquakes occurred in 2003 and 2004 in Bange County, Tibet, China, all with similar depths and focal mechanisms. However, the source parameters, kinematics and relationships between these earthquakes are poorly known because of their moderately-sized magnitude and the sparse distribution of seismic stations in the region. We utilize interferometric synthetic aperture radar (InSAR) data from the European Space Agency’s Envisat satellite to determine the location, fault geometry and slip distribution of three large events of the sequence that occurred on 7 July 2003 (Ms 6.0), 27 March 2004 (Ms 6.2), and 3 July 2004 (Ms 5.1). The modeling results indicate that the 7 July 2003 event was a normal-faulting event with a right-lateral slip component, the 27 March 2004 earthquake was associated with a normal fault striking northeast–southwest and dipping northwest with a moderately oblique right-lateral slip, and the 3 July 2004 event was caused by a normal fault. A calculation of the static stress changes on the fault planes demonstrates that the third earthquake may have been triggered by the previous ones. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
Open AccessArticle Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry
Remote Sens. 2016, 8(6), 468; doi:10.3390/rs8060468
Received: 6 April 2016 / Revised: 5 May 2016 / Accepted: 23 May 2016 / Published: 2 June 2016
Cited by 13 | PDF Full-text (52170 KB) | HTML Full-text | XML Full-text
Abstract
Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images
[...] Read more.
Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Continent-Wide 2-D Co-Seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data: Correction of Azimuth Co-Registration Error
Remote Sens. 2016, 8(5), 376; doi:10.3390/rs8050376
Received: 29 February 2016 / Revised: 25 April 2016 / Accepted: 28 April 2016 / Published: 4 May 2016
Cited by 7 | PDF Full-text (4153 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this study, we mapped the co-seismic deformation of the 2015 Mw 8.3 Illapel, Chile earthquake with multiple Sentinel-1A TOPS data frames from both ascending and descending geometries. To meet the requirement of very high co-registration precision, an improved spectral diversity method was
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In this study, we mapped the co-seismic deformation of the 2015 Mw 8.3 Illapel, Chile earthquake with multiple Sentinel-1A TOPS data frames from both ascending and descending geometries. To meet the requirement of very high co-registration precision, an improved spectral diversity method was proposed to correct the co-registration slope error in the azimuth direction induced by multiple Sentinel-1A TOPS data frames. All phase jumps that appear in the conventional processing method have been corrected after applying the proposed method. The 2D deformation fields in the east-west and vertical directions are also resolved by combing D-InSAR and Offset Tracking measurements. The results reveal that the east-west component dominated the 2D displacement, where up to 2 m displacement towards the west was measured in the coastal area. Vertical deformations ranging between −0.25 and 0.25 m were found. The 2D displacements imply the collision of the Nazca plate squeezed the coast, which shows good accordance with the geological background of the region. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Spatiotemporal Characterization of Land Subsidence and Uplift (2009–2010) over Wuhan in Central China Revealed by TerraSAR-X InSAR Analysis
Remote Sens. 2016, 8(4), 350; doi:10.3390/rs8040350
Received: 10 March 2016 / Revised: 11 April 2016 / Accepted: 14 April 2016 / Published: 20 April 2016
Cited by 4 | PDF Full-text (5084 KB) | HTML Full-text | XML Full-text
Abstract
The effects of ground deformation pose a significant geo-hazard to the environment and infrastructure in Wuhan, the most populous city in Central China, in the eastern Jianghan Plain at the intersection of the Yangtze and Han rivers. Prior to this study, however, rates
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The effects of ground deformation pose a significant geo-hazard to the environment and infrastructure in Wuhan, the most populous city in Central China, in the eastern Jianghan Plain at the intersection of the Yangtze and Han rivers. Prior to this study, however, rates and patterns of region-wide ground deformation in Wuhan were little known. Here we employ multi-temporal SAR interferometry to detect and characterize spatiotemporal variations of ground deformation in major metropolitan areas in Wuhan. A total of twelve TerraSAR-X images acquired during 2009–2010 are used in the InSAR time series analysis. InSAR-derived results are validated by levelling survey measurements and reveal a distinct subsidence pattern within six zones in major commercial and industrial areas, with a maximum subsidence rate up to −67.3 mm/year. A comparison analysis between subsiding patterns and urban developments as well as geological conditions suggests that land subsidence in Wuhan is mainly attributed to anthropogenic activities, natural compaction of soft soil, and karst dissolution of subsurface carbonate rocks. However, anthropogenic activities related to intensive municipal construction and industrial production have more significant impacts on the measured subsidence than natural factors. Moreover, remarkable signals of secular land uplift are found along both banks of the Yangtze River, especially along the southern bank, with deformation rates ranging mostly from +5 mm/year to +17.5 mm/year. A strong temporal correlation is highlighted between the detected displacement evolutions and the water level records of the Yangtze River, inferring that this previously unknown deformation phenomenon is likely related to seasonal fluctuations in water levels of the Yangtze River. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Coseismic Fault Model of Mw 8.3 2015 Illapel Earthquake (Chile) Retrieved from Multi-Orbit Sentinel1-A DInSAR Measurements
Remote Sens. 2016, 8(4), 323; doi:10.3390/rs8040323
Received: 28 January 2016 / Revised: 25 March 2016 / Accepted: 7 April 2016 / Published: 12 April 2016
Cited by 7 | PDF Full-text (26872 KB) | HTML Full-text | XML Full-text
Abstract
On 16 September 2015, a Mw 8.3 interplate thrust earthquake ruptured offshore the Illapel region (Chile). Here, we perform coseismic slip fault modeling based on multi-orbit Sentinel 1-A (S1A) data. To do this, we generate ascending and descending S1A interferograms, whose combination allows
[...] Read more.
On 16 September 2015, a Mw 8.3 interplate thrust earthquake ruptured offshore the Illapel region (Chile). Here, we perform coseismic slip fault modeling based on multi-orbit Sentinel 1-A (S1A) data. To do this, we generate ascending and descending S1A interferograms, whose combination allows us to retrieve the EW and vertical components of deformation. In particular, the EW displacement map highlights a westward displacement of about 210 cm, while the vertical map shows an uplift of about 25 cm along the coast, surrounded by a subsidence of about 20 cm. Following this analysis, we jointly invert the multi-orbit S1A interferograms by using an analytical approach to search for the coseismic fault parameters and related slip values. Most of the slip occurs northwest of the epicenter, with a maximum located in the shallowest 20 km. Finally, we refine our modeling approach by exploiting the Finite Element method, which allows us to take geological and structural complexities into account to simulate the slip along the slab curvature, the von Mises stress distribution, and the principal stress axes orientation. The von Mises stress distribution shows a close similarity to the depth distribution of the aftershock hypocenters. Likewise, the maximum principal stress orientation highlights a compressive regime in correspondence of the deeper portion of the slab and an extensional regime at its shallower segment; these findings are supported by seismological data. Full article
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Open AccessArticle Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data
Remote Sens. 2016, 8(4), 307; doi:10.3390/rs8040307
Received: 29 January 2016 / Revised: 29 March 2016 / Accepted: 31 March 2016 / Published: 6 April 2016
Cited by 5 | PDF Full-text (13251 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR) data-based landslide detection approaches
[...] Read more.
Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR) data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR) SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth’s landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia. Full article
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Open AccessArticle Pi-SAR-L2 Observation of the Landslide Caused by Typhoon Wipha on Izu Oshima Island
Remote Sens. 2016, 8(4), 282; doi:10.3390/rs8040282
Received: 24 December 2015 / Revised: 16 March 2016 / Accepted: 22 March 2016 / Published: 29 March 2016
Cited by 1 | PDF Full-text (7953 KB) | HTML Full-text | XML Full-text
Abstract
Pi-SAR-L2 full polarimetic data observed in four different observational directions over a landslide area on Izu Oshima Island, induced by Typhoon Wipha on 16 October 2013, were analyzed to clarify the most appropriate L-band full polarimetric parameters and observational direction to detect a
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Pi-SAR-L2 full polarimetic data observed in four different observational directions over a landslide area on Izu Oshima Island, induced by Typhoon Wipha on 16 October 2013, were analyzed to clarify the most appropriate L-band full polarimetric parameters and observational direction to detect a landslide area. Japanese airborne Pi-SAR-L2 and PiSAR-L data were used in this analysis. Several L-band full polarimetric parameters, including backscattering coefficient (σ°), coherence between two polarimetric states, four-component decomposition parameters (double-bounce/volume/surface/helix scattering), and eigenvalue decomposition parameters (entropy/α/anisotropy), were calculated to determine the most appropriate parameters for detecting landslide areas. The change in land cover from forest before the disaster to bare soil after the disaster was detected well by α, and coherence between HH and VV. Observational data from the bottom to the top of the landslide detected the landslide well, whereas observations from the opposite sides were not as useful, indicating that a smaller local incident angle is better to distinguish landslide and forested areas. Soil from the landslide intruded into the urban areas; however, none of the full polarimetric parameters showed any significant differences between the landslide-affected urban areas after the disaster and unaffected areas before the disaster. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Complex Deformation Monitoring over the Linfen–Yuncheng Basin (China) with Time Series InSAR Technology
Remote Sens. 2016, 8(4), 284; doi:10.3390/rs8040284
Received: 16 January 2016 / Revised: 7 March 2016 / Accepted: 21 March 2016 / Published: 28 March 2016
Cited by 1 | PDF Full-text (6886 KB) | HTML Full-text | XML Full-text
Abstract
The Linfen–Yuncheng basin is an area prone to geological disasters, such as surface subsidence, ground fissuring, fault activity, and earthquakes. For the purpose of disaster prevention and mitigation, Interferometric Synthetic Aperture Radar (InSAR) was used to map ground deformation in this area. After
[...] Read more.
The Linfen–Yuncheng basin is an area prone to geological disasters, such as surface subsidence, ground fissuring, fault activity, and earthquakes. For the purpose of disaster prevention and mitigation, Interferometric Synthetic Aperture Radar (InSAR) was used to map ground deformation in this area. After the ground deformation characteristics over the Linfen–Yuncheng basin were obtained, the cross-correlations among regional ground subsidence, fault activity, and underground water level were analyzed in detail. Additionally, an area of abnormal deformation was found and examined. Through time series deformation monitoring and mechanism inversion, we found that the abnormal deformation was related mainly to excessive groundwater exploitation. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing
Remote Sens. 2016, 8(4), 272; doi:10.3390/rs8040272
Received: 27 October 2015 / Revised: 7 March 2016 / Accepted: 11 March 2016 / Published: 26 March 2016
Cited by 3 | PDF Full-text (21777 KB) | HTML Full-text | XML Full-text
Abstract
Disaster change mapping, which can provide accurate and timely changed information (e.g., damaged buildings, accessibility of road and the shelter sites) for decision makers to guide and support a plan for coordinating emergency rescue, is critical for early disaster rescue. In this paper,
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Disaster change mapping, which can provide accurate and timely changed information (e.g., damaged buildings, accessibility of road and the shelter sites) for decision makers to guide and support a plan for coordinating emergency rescue, is critical for early disaster rescue. In this paper, we focus on optical remote sensing data to propose an automatic procedure to reduce the impacts of optical data limitations and provide the emergency information in the early phases of a disaster. The procedure utilizes a series of new methods, such as an Optimizable Variational Model (OptVM) for image fusion and a scale-invariant feature transform (SIFT) constraint optical flow method (SIFT-OFM) for image registration, to produce product maps including cloudless backdrop maps and change-detection maps for catastrophic event regions, helping people to be aware of the whole scope of the disaster and assess the distribution and magnitude of damage. These product maps have a rather high accuracy as they are based on high precision preprocessing results in spectral consistency and geometric, which compared with traditional fused and registration methods by visual qualitative or quantitative analysis. The procedure is fully automated without any manual intervention to save response time. It also can be applied to many situations. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Anatomy of Subsidence in Tianjin from Time Series InSAR
Remote Sens. 2016, 8(3), 266; doi:10.3390/rs8030266
Received: 15 December 2015 / Revised: 10 March 2016 / Accepted: 14 March 2016 / Published: 22 March 2016
Cited by 2 | PDF Full-text (12141 KB) | HTML Full-text | XML Full-text
Abstract
Groundwater is a major source of fresh water in Tianjin Municipality, China. The average rate of groundwater extraction in this area for the last 20 years fluctuates between 0.6 and 0.8 billion cubic meters per year. As a result, significant subsidence has been
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Groundwater is a major source of fresh water in Tianjin Municipality, China. The average rate of groundwater extraction in this area for the last 20 years fluctuates between 0.6 and 0.8 billion cubic meters per year. As a result, significant subsidence has been observed in Tianjin. In this study, C-band Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) images and L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data were employed to recover the Earth’s surface evolution during the period between 2007 and 2009 using InSAR time series techniques. Similar subsidence patterns can be observed in the overlapping area of the ASAR and PALSAR mean velocity maps with a maximum radar line of sight rate of ~170 mm·year−1. The west subsidence is modeled for ground water volume change using Mogi source array. Geological control by major faults on the east subsidence is analyzed. Storage coefficient of the east subsidence is estimated by InSAR displacements and temporal pattern of water level changes. InSAR has proven a useful tool for subsidence monitoring and displacement interpretation associated with underground water usage. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site
Remote Sens. 2016, 8(3), 237; doi:10.3390/rs8030237
Received: 10 December 2015 / Revised: 26 January 2016 / Accepted: 4 March 2016 / Published: 12 March 2016
Cited by 5 | PDF Full-text (9685 KB) | HTML Full-text | XML Full-text
Abstract
This work concerns a proposal of the integration of InSAR (Interferometric Synthetic Aperture Radar) data acquired by ground-based (GB) and satellite platforms. The selected test site is the Åknes rockslide, which affects the western Norwegian coast. The availability of GB-InSAR and satellite InSAR
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This work concerns a proposal of the integration of InSAR (Interferometric Synthetic Aperture Radar) data acquired by ground-based (GB) and satellite platforms. The selected test site is the Åknes rockslide, which affects the western Norwegian coast. The availability of GB-InSAR and satellite InSAR data and the accessibility of a wide literature make the landslide suitable for testing the proposed procedure. The first step consists of the organization of a geodatabase, performed in the GIS environment, containing all of the available data. The second step concerns the analysis of satellite and GB-InSAR data, separately. Two datasets, acquired by RADARSAT-2 (related to a period between October 2008 and August 2013) and by a combination of TerraSAR-X and TanDEM-X (acquired between July 2010 and October 2012), both of them in ascending orbit, processed applying SBAS (Small BAseline Subset) method, are available. GB-InSAR data related to five different campaigns of measurements, referred to the summer seasons of 2006, 2008, 2009, 2010 and 2012, are available, as well. The third step relies on data integration, performed firstly from a qualitative point of view and later from a semi-quantitative point of view. The results of the proposed procedure have been validated by comparing them to GPS (Global Positioning System) data. The proposed procedure allowed us to better define landslide sectors in terms of different ranges of displacements. From a qualitative point of view, stable and unstable areas have been distinguished. In the sector concerning movement, two different sectors have been defined thanks to the results of the semi-quantitative integration step: the first sector, concerning displacement values higher than 10 mm, and the 2nd sector, where the displacements did not exceed a 10-mm value of displacement in the analyzed period. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Interseismic Deformation of the Altyn Tagh Fault Determined by Interferometric Synthetic Aperture Radar (InSAR) Measurements
Remote Sens. 2016, 8(3), 233; doi:10.3390/rs8030233
Received: 27 November 2015 / Revised: 29 February 2016 / Accepted: 4 March 2016 / Published: 11 March 2016
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Abstract
The Altyn Tagh Fault (ATF) is one of the major left-lateral strike-slip faults in the northeastern area of the Tibetan Plateau. In this study, the interseismic deformation across the ATF at 85°E was measured using 216 interferograms from 33 ENVISAT advanced synthetic aperture
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The Altyn Tagh Fault (ATF) is one of the major left-lateral strike-slip faults in the northeastern area of the Tibetan Plateau. In this study, the interseismic deformation across the ATF at 85°E was measured using 216 interferograms from 33 ENVISAT advanced synthetic aperture radar images on a descending track acquired from 2003 to 2010, and 66 interferograms from 15 advanced synthetic aperture radar images on an ascending track acquired from 2005 to 2010. To retrieve the pattern of interseismic strain accumulation, a global atmospheric model (ERA-Interim) provided by the European Center for Medium Range Weather Forecast and a global network orbital correction approach were applied to remove atmospheric effects and the long-wavelength orbital errors in the interferograms. Then, the interferometric synthetic aperture radar (InSAR) time series with atmospheric estimation model was used to obtain a deformation rate map for the ATF. Based on the InSAR velocity map, the regional strain rates field was calculated for the first time using the multi-scale wavelet method. The strain accumulation is strongly focused on the ATF with the maximum strain rate of 12.4 × 10−8/year. We also show that high-resolution 2-D strain rates field can be calculated from InSAR alone, even without GPS data. Using a simple half-space elastic screw dislocation model, the slip-rate and locking depth were estimated with both ascending and descending surface velocity measurements. The joint inversion results are consistent with a left-lateral slip rate of 8.0 ± 0.7 mm/year on the ATF and a locking depth of 14.5 ± 3 km, which is in agreement with previous results from GPS surveys and ERS InSAR results. Our results support the dynamic models of Asian deformation requiring low fault slip rate. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach
Remote Sens. 2016, 8(3), 231; doi:10.3390/rs8030231
Received: 22 December 2015 / Revised: 19 February 2016 / Accepted: 4 March 2016 / Published: 11 March 2016
Cited by 5 | PDF Full-text (13512 KB) | HTML Full-text | XML Full-text
Abstract
Automatic post-disaster mapping of building damage using remote sensing images is an important and time-critical element of disaster management. The characteristics of remote sensing images available immediately after the disaster are not certain, since they may vary in terms of capturing platform, sensor-view,
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Automatic post-disaster mapping of building damage using remote sensing images is an important and time-critical element of disaster management. The characteristics of remote sensing images available immediately after the disaster are not certain, since they may vary in terms of capturing platform, sensor-view, image scale, and scene complexity. Therefore, a generalized method for damage detection that is impervious to the mentioned image characteristics is desirable. This study aims to develop a method to perform grid-level damage classification of remote sensing images by detecting the damage corresponding to debris, rubble piles, and heavy spalling within a defined grid, regardless of the aforementioned image characteristics. The Visual-Bag-of-Words (BoW) is one of the most widely used and proven frameworks for image classification in the field of computer vision. The framework adopts a kind of feature representation strategy that has been shown to be more efficient for image classification—regardless of the scale and clutter—than conventional global feature representations. In this study supervised models using various radiometric descriptors (histogram of gradient orientations (HoG) and Gabor wavelets) and classifiers (SVM, Random Forests, and Adaboost) were developed for damage classification based on both BoW and conventional global feature representations, and tested with four datasets. Those vary according to the aforementioned image characteristics. The BoW framework outperformed conventional global feature representation approaches in all scenarios (i.e., for all combinations of feature descriptors, classifiers, and datasets), and produced an average accuracy of approximately 90%. Particularly encouraging was an accuracy improvement by 14% (from 77% to 91%) produced by BoW over global representation for the most complex dataset, which was used to test the generalization capability. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan
Remote Sens. 2016, 8(3), 199; doi:10.3390/rs8030199
Received: 14 January 2016 / Revised: 19 February 2016 / Accepted: 24 February 2016 / Published: 29 February 2016
Cited by 9 | PDF Full-text (7627 KB) | HTML Full-text | XML Full-text
Abstract
In this study, six different periods of digital terrain model (DTM) data obtained from various flight vehicles by using the techniques of aerial photogrammetry, airborne LiDAR (ALS), and unmanned aerial vehicles (UAV) were adopted to discuss the errors and applications of these techniques.
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In this study, six different periods of digital terrain model (DTM) data obtained from various flight vehicles by using the techniques of aerial photogrammetry, airborne LiDAR (ALS), and unmanned aerial vehicles (UAV) were adopted to discuss the errors and applications of these techniques. Error estimation provides critical information for DTM data users. This study conducted error estimation from the perspective of general users for mountain/forest areas with poor traffic accessibility using limited information, including error reports obtained from the data generation process and comparison errors of terrain elevations. Our results suggested that the precision of the DTM data generated in this work using different aircrafts and generation techniques is suitable for landslide analysis. Especially in mountainous and densely vegetated areas, data generated by ALS can be used as a benchmark to solve the problem of insufficient control points. Based on DEM differencing of multiple periods, this study suggests that sediment delivery rate decreased each year and was affected by heavy rainfall during each period for the Meiyuan Shan landslide area. Multi-period aerial photogrammetry and ALS can be effectively applied after the landslide disaster for monitoring the terrain changes of the downstream river channel and their potential impacts. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds
Remote Sens. 2016, 8(3), 189; doi:10.3390/rs8030189
Received: 29 October 2015 / Revised: 3 February 2016 / Accepted: 18 February 2016 / Published: 26 February 2016
Cited by 3 | PDF Full-text (13002 KB) | HTML Full-text | XML Full-text
Abstract
The rapid and accurate assessment of building damage states using only post-event remote sensing data is critical when performing loss estimation in earthquake emergency response. Damaged roof detection is one of the most efficient methods of assessing building damage. In particular, airborne LiDAR
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The rapid and accurate assessment of building damage states using only post-event remote sensing data is critical when performing loss estimation in earthquake emergency response. Damaged roof detection is one of the most efficient methods of assessing building damage. In particular, airborne LiDAR is often used to detect roofs damaged by earthquakes, especially for certain damage types, due to its ability to rapidly acquire accurate 3D information on individual roofs. Earthquake-induced roof damages are categorized into surface damages and structural damages based on the geometry features of the debris and the roof structure. However, recent studies have mainly focused on surface damage; little research has been conducted on structural damage. This paper presents an original 3D shape descriptor of individual roofs for detecting roofs with surface damage and roofs exhibiting structural damage by identifying spatial patterns of compact and regular contours for intact roofs, as well as jagged and irregular contours for damaged roofs. The 3D shape descriptor is extracted from building contours derived from airborne LiDAR point clouds. First, contour clusters are extracted from contours that are generated from a dense DSM of individual buildings derived from point clouds. Second, the shape chaos indexes of contour clusters are computed as the information entropy through a contour shape similarity measurement between two contours in a contour cluster. Finally, the 3D shape descriptor is calculated as the weighted sum of the shape chaos index of each contour cluster corresponding to an individual roof. Damaged roofs are detected solely using the 3D shape descriptor with the maximum entropy threshold. Experiments using post-event airborne LiDAR point clouds of the 2010 Haiti earthquake suggest that the proposed damaged roof detection technique using the proposed 3D shape descriptor can detect both roofs exhibiting surface damage and roofs exhibiting structural damage with a high accuracy. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique
Remote Sens. 2016, 8(3), 191; doi:10.3390/rs8030191
Received: 11 December 2015 / Revised: 7 February 2016 / Accepted: 16 February 2016 / Published: 26 February 2016
Cited by 10 | PDF Full-text (4748 KB) | HTML Full-text | XML Full-text
Abstract
Ground deformation contains important information that can be exploited to look into the dynamics of a geothermal system. In recent years, InSAR has manifested its strong power in the monitoring of ground deformation. In this paper, a multi-temporal InSAR algorithm, WLS InSAR, is
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Ground deformation contains important information that can be exploited to look into the dynamics of a geothermal system. In recent years, InSAR has manifested its strong power in the monitoring of ground deformation. In this paper, a multi-temporal InSAR algorithm, WLS InSAR, is employed to monitor and characterize the Yangbajing geothermal field in Tibet, China, using 51 ENVISAT/ASAR images acquired from two overlapping descending tracks. The results reveal that the WLS InSAR algorithm can suppress the adverse effects of seasonal oscillations, associated with the freezing-thawing cycle of the permafrost in the Qinghai-Tibet Plateau. Deformations of up to 2 cm/yr resulting from the exploitation of the geothermal resource have been detected in the southern part of the Yangbajing field between 2006 and 2010. A source model inversion of the subsurface geothermal fluids was carried out based on the elastic half-space theory using the accumulated deformations. It was found that most geothermal fluid loss has occurred in the southern part of the shallow reservoir as the pore space beneath the northern part of field was recharged by the ascending flow from the deep layers of the reservoir through well-developed faults in the region. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image
Remote Sens. 2016, 8(3), 171; doi:10.3390/rs8030171
Received: 25 November 2015 / Revised: 6 February 2016 / Accepted: 16 February 2016 / Published: 25 February 2016
Cited by 8 | PDF Full-text (4857 KB) | HTML Full-text | XML Full-text
Abstract
After an earthquake, rapidly and accurately obtaining building damage information can help to effectively guide the implementation of the emergency rescue and can reduce disaster losses and casualties. Using a single post-earthquake fully-polarimetric synthetic aperture radar (PolSAR) image to interpret building damage information
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After an earthquake, rapidly and accurately obtaining building damage information can help to effectively guide the implementation of the emergency rescue and can reduce disaster losses and casualties. Using a single post-earthquake fully-polarimetric synthetic aperture radar (PolSAR) image to interpret building damage information not only involves a guaranteed data source but is also easy and can be rapidly implemented. This paper is focused on rapid building earthquake damage detection in urban areas using post-earthquake PolSAR data. In PolSAR images, the undamaged buildings parallel to satellite flight pass are different from the collapsed buildings, but the undamaged buildings divergent to satellite flight pass are very similar to collapsed buildings because of their volume scattering characteristics. In this paper, the method of polarization orientation angle (POA) compensation is employed to increase the scattering power of buildings divergent to satellite flight pass, and then Wishart supervised classification is implemented on the PolSAR data after POA compensation. In addition, the two parameters of normalized difference of the dihedral component (NDDC) and ρHHHV are proposed to improve the classification accuracy of the Wishart supervised classification, and both the undamaged buildings and collapsed buildings are determined. The study was carried out after the “4.14” Yushu earthquake in Yushu County, Qinghai province, China. The three damage levels are set for the urban area at the city block scale according to the values of the BBCR building damage index. The experimental results confirm that the scheme proposed in this paper can greatly improve the accuracy of the extraction of building damage information. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation
Remote Sens. 2016, 8(3), 179; doi:10.3390/rs8030179
Received: 2 December 2015 / Revised: 17 January 2016 / Accepted: 14 February 2016 / Published: 25 February 2016
Cited by 2 | PDF Full-text (10569 KB) | HTML Full-text | XML Full-text
Abstract
Time-series SAR/InSAR techniques have proven to be effective tools for measuring landslide movements over large regions. Prior studies of these techniques, however, have focused primarily on technical innovation and applications, leaving coupling analysis of slope displacements and trigging factors as an unexplored area
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Time-series SAR/InSAR techniques have proven to be effective tools for measuring landslide movements over large regions. Prior studies of these techniques, however, have focused primarily on technical innovation and applications, leaving coupling analysis of slope displacements and trigging factors as an unexplored area of research. Linking potential landslide inducing factors such as hydrology to SAR/InSAR derived displacements is of crucial importance for understanding landslide deformation mechanisms and could support the development of early-warning systems for disaster mitigation and management. In this study, a sequential data assimilation method named the Ensemble Kalman filter (EnKF), is adopted to explore the response mechanisms of the Shuping landslide movement in relation to hydrological factors. Previous research on the Shuping landslide area shows that the reservoir water level and rainfall are the two main triggering factors in slope failures. To extract the time-series deformations for the Shuping landslide area, Pixel Offset Tracking (POT) technique with corner reflectors was adopted to process the TerraSAR-X StripMap (SM) and High-resolution Spotlight (HS) images. Considering that these triggering factors are the primary causes of displacement fluctuations in periodic displacement, time-series decomposition was carried out to extract the periodic displacement from the POT measurements. The correlations between the periodic displacement and the inducing factors were qualitatively estimated through a grey relational analysis. Based on this analysis, the EnKF method was adopted to explore the response relationships between the displacements and triggering factors. Preliminary results demonstrate the effectiveness of EnKF in studying deformation response mechanisms and understanding landslide development processes. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition
Remote Sens. 2016, 8(2), 95; doi:10.3390/rs8020095
Received: 21 October 2015 / Revised: 9 January 2016 / Accepted: 18 January 2016 / Published: 27 January 2016
Cited by 8 | PDF Full-text (16990 KB) | HTML Full-text | XML Full-text
Abstract
Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the basis for emergency disaster management. This study presents a comprehensive system that uses
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Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the basis for emergency disaster management. This study presents a comprehensive system that uses unmanned aerial vehicles (UAVs) and Semi-Global dense Matching (SGM) techniques to identify and extract landslide scarp data. The selected study area is located along a major highway in a mountainous region in Jordan, and contains creeping landslides induced by heavy rainfall. Field observations across the slope body and a deformation analysis along the highway and existing gabions indicate that the slope is active and that scarp features across the slope will continue to open and develop new tension crack features, leading to the downward movement of rocks. The identification of landslide scarps in this study was performed via a dense 3D point cloud of topographic information generated from high-resolution images captured using a low-cost UAV and a target-based camera calibration procedure for a low-cost large-field-of-view camera. An automated approach was used to accurately detect and extract the landslide head scarps based on geomorphological factors: the ratio of normalized Eigenvalues (i.e., λ1/λ2 ≥ λ3) derived using principal component analysis, topographic surface roughness index values, and local-neighborhood slope measurements from the 3D image-based point cloud. Validation of the results was performed using root mean square error analysis and a confusion (error) matrix between manually digitized landslide scarps and the automated approaches. The experimental results using the fully automated 3D point-based analysis algorithms show that these approaches can effectively distinguish landslide scarps. The proposed algorithms can accurately identify and extract landslide scarps with centimeter-scale accuracy. In addition, the combination of UAV-based imagery, 3D scene reconstruction, and landslide scarp recognition/extraction algorithms can provide flexible and effective tool for monitoring landslide scarps and is acceptable for landslide mapping purposes. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico
Remote Sens. 2015, 7(12), 17035-17050; doi:10.3390/rs71215868
Received: 23 August 2015 / Revised: 27 November 2015 / Accepted: 7 December 2015 / Published: 17 December 2015
Cited by 4 | PDF Full-text (3158 KB) | HTML Full-text | XML Full-text
Abstract
In this work we present an application of InSAR and gravimetric surveys for risk management related to land subsidence and surface ground faulting generation. A subsidence velocity map derived from the 2007–2011 ALOS SAR imagery and a sediment thicknesses map obtained from the
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In this work we present an application of InSAR and gravimetric surveys for risk management related to land subsidence and surface ground faulting generation. A subsidence velocity map derived from the 2007–2011 ALOS SAR imagery and a sediment thicknesses map obtained from the inversion of gravimetric data were integrated with a surface fault map to produce a subsidence hazard zoning in the city of Aguascalientes, Mexico. The resulting zoning is presented together with specific recommendations about geotechnical studies needed for further evaluation of surface faulting in these hazard zones. The derived zoning map consists in four zones including null hazard (stable terrain without subsidence), low hazard (areas prone to subsidence), medium hazard (zones with subsidence) and high hazard (zones with surface faulting). InSAR results displayed subsidence LOS velocities up to 10 cm/year and two subsidence areas unknown before this study. Gravimetric results revealed that the thicker sediment sequence is located toward north of Aguascalientes City reaching up to 600 m in thickness, which correspond to a high subsidence LOS velocity zone (up to 6 cm/year). Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment
Remote Sens. 2015, 7(12), 16183-16203; doi:10.3390/rs71215821
Received: 10 July 2015 / Revised: 10 November 2015 / Accepted: 19 November 2015 / Published: 2 December 2015
Cited by 3 | PDF Full-text (12592 KB) | HTML Full-text | XML Full-text
Abstract
Frequently occurring landslides in Ethiopia endanger rapidly expanding settlements and infrastructure. We investigated a large landslide on the western escarpment of the Main Ethiopian Rift close to Debre Sina. To understand the extent and amplitude of the movements, we derived vectors of horizontal
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Frequently occurring landslides in Ethiopia endanger rapidly expanding settlements and infrastructure. We investigated a large landslide on the western escarpment of the Main Ethiopian Rift close to Debre Sina. To understand the extent and amplitude of the movements, we derived vectors of horizontal displacements by feature matching of very high resolution satellite images (VHR). The major movements occurred in two phases, after the rainy seasons in 2005 and 2006 reaching magnitudes of 48 ± 10.1 m and 114 ± 7.2 m, respectively. The results for the first phase were supported by amplitude tracking using two Envisat/ASAR scenes from the 31 July 2004 and the 29 October 2005. Surface changes in vertical direction were analyzed by subtraction of a pre-event digital elevation model (DEM) from aerial photographs and post-event DEM from ALOS/PRISM triplet data. Furthermore, we derived elevation changes using satellite laser altimetry measurement acquired by the ICESat satellite. These analyses allowed us to delineate the main landslide, which covers an area of 6.5 km2, shallow landslides surrounding the main landslide body that increased the area to 8.5 km2, and the stable area in the lower part of the slope. We assume that the main triggering factor for such a large landslide was precipitation cumulated over several months and we suspect that the slope failure will progress towards the foot of the slope. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea
Remote Sens. 2015, 7(12), 15955-15968; doi:10.3390/rs71215814
Received: 30 September 2015 / Revised: 17 November 2015 / Accepted: 23 November 2015 / Published: 30 November 2015
Cited by 4 | PDF Full-text (5917 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Global Positioning System (GPS) has been proved to be a powerful tool for measuring co-seismic ground displacements with an application to seismic source inversion. Whereas most of the tsunamis are triggered by large earthquakes, GPS can contribute to the tsunami early warning system
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Global Positioning System (GPS) has been proved to be a powerful tool for measuring co-seismic ground displacements with an application to seismic source inversion. Whereas most of the tsunamis are triggered by large earthquakes, GPS can contribute to the tsunami early warning system (TEWS) by helping to obtain tsunami source parameters in near real-time. Toward the end of 2012, the second phase of the BeiDou Navigation Satellite System (BDS) constellation was accomplished, and BDS has been providing regional positioning service since then. Numerical results indicate that precision of BDS nowadays is equivalent to that of the GPS. Compared with a single Global Satellite Navigation System (GNSS), combined BDS/GPS real-time processing can improve accuracy and especially reliability of retrieved co-seismic displacements. In the present study, we investigate the potential of BDS to serve for the early warning system of tsunamis in the South China Sea region. To facilitate early warnings of tsunamis and forecasting capabilities in this region, we propose to distribute an array of BDS-stations along the Luzon Island (Philippines). By simulating an earthquake with Mw = 8 at the Manila trench as an example, we demonstrate that such an array will be able to detect earthquake parameters in real time with a high degree of accuracy and, hence, contribute to the fast and reliable tsunami early warning system in this region. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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Open AccessArticle InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy)
Remote Sens. 2015, 7(12), 16004-16023; doi:10.3390/rs71215812
Received: 25 August 2015 / Revised: 13 November 2015 / Accepted: 17 November 2015 / Published: 30 November 2015
Cited by 6 | PDF Full-text (4511 KB) | HTML Full-text | XML Full-text
Abstract
We applied the Small Baseline Subset multi-temporal InSAR technique (SBAS) to two SAR datasets acquired from 2003 up to 2013 by Envisat (ESA, European Space Agency) and COSMO-SkyMed (ASI, Italian Space Agency) satellites to investigate spatial and temporal patterns of land subsidence in
[...] Read more.
We applied the Small Baseline Subset multi-temporal InSAR technique (SBAS) to two SAR datasets acquired from 2003 up to 2013 by Envisat (ESA, European Space Agency) and COSMO-SkyMed (ASI, Italian Space Agency) satellites to investigate spatial and temporal patterns of land subsidence in the Sibari Plain (Southern Italy). Subsidence processes (up to ~20 mm/yr) were investigated comparing geological, hydrogeological, and land use information with interferometric results. We suppose a correlation between subsidence and thickness of the Plio-Quaternary succession suggesting an active role of the isostatic compensation. Furthermore, the active back thrusting in the Corigliano Gulf could trigger a flexural subsidence mechanism even if fault activity and earthquakes do not seem play a role in the present subsidence. In this context, the compaction of Holocene deposits contributes to ground deformation. Despite the rapid urbanization of the area in the last 50 years, we do not consider the intensive groundwater pumping and related water table drop as the main triggering cause of subsidence phenomena, in disagreement with some previous publications. Our interpretation for the deformation fields related to natural and anthropogenic factors would be a comprehensive and exhaustive justification to the complexity of subsidence processes in the Sibari Plain. Full article
(This article belongs to the Special Issue Earth Observations for Geohazards) Printed Edition available
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