Data collections of ESA DUE GlobPermafrost and ESA CCI+ Permafrost

2020 ◽  
Author(s):  
Annett Bartsch ◽  
Keyword(s):  
Time Series ◽  
Information System ◽  
Land Surface ◽  
Surface Deformation ◽  
Data Access ◽  
Active Layer Thickness ◽  
Rock Glacier ◽  
Borehole Data ◽  
Data Repositories ◽  
The Impact

<p>A Permafrost Information System (PerSys) based on satellite data has been setup as part of the ESA DUE GlobPermafrost project (2016-2019, www.globpermafrost.info). This includes a data catalogue as well as a WebGIS, both linked to the Pangaea repository for easy data access.</p><p>The thematic products available include InSAR-based land surface deformation maps, rock glacier velocity fields, spatially distributed permafrost model outputs, land surface properties and changes, and ground-fast lake ice. Extended permafrost modelling (time series) is implemented in the new ESA CCI+ Permafrost project (2018-2021, http://cci.esa.int/Permafrost), which will provide the key for our understanding of the changes of surface features over time. Special emphasis in CCI+ Permafrost is on the evaluation and development of land surface models to gain better understanding of the impact of climate change on permafrost and land-atmosphere exchange. Additional focus will be on documentation of kinematics from rock glaciers in several mountain regions across the world supporting the International Permafrost Association (IPA) action group ‘rock glacier kinematics as an essential climate variable’.</p><p>We will present the Permafrost Information System including the time series (2003-2017) of the first version of ground temperatures and active layer thickness for the entire Arctic from the ESA CCI+ Permafrost project. Further on, details on the user requirements collection process will be provided. Ground temperature is calculated for 0, 1m, 2m, 5m, and 10 m depth and has been assessed based on a range of borehole data. A survey regarding data repositories containing for validation relevant borehole data has been conducted. The records have been evaluated for the project purpose and harmonized. The resulting database will be eventually also made publicly available.</p>

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

scholarly journals INSAR TIME SERIES INVESTIGATION OF LAND SURFACE DEFORMATION IN AZAR OIL FIELD

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 733-736
Author(s):  
Z. Mirzaii ◽  
M. Hasanlou ◽  
S. Samieie-Esfahany ◽  
M. Rojhani ◽  
P. Ajourlou
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Surface Deformation ◽  
Oil Extraction ◽  
Oil Field ◽  
Oil Exploration ◽  
Persistent Scatterer Interferometry ◽  
Maximum Displacement ◽  
Envisat Asar ◽  
Persistent Scatterers

Abstract. Time-series interferometric synthetic aperture radar (InSAR) has developed as an influential method to measure various surface deformations. One of the generations of time-series InSAR methodologies is Persistent Scatterer Interferometry (PSI) that focuses on targets with a high correlation over time. In this study, we have measured the surface deformation in Azar Oil Field utilizing time series analysis. Azar Oil Field is one of Iran's oil fields. This oil field is located in the east of the city of Mehran, Ilam province. The reservoir of this oil field is shared by Iraq oil field whose name is Badra where oil extraction started in 201409. While Iran started oil exploration in 201709, Iraq has maximized its oil exploration ever since. The subsidence is mainly observed in the vicinity of the oil field. The Stanford Method for Persistent Scatterers (StaMPS) package has been employed to process 20 descending ENVISAT-ASAR images collected between 2003 and 2009, as well as 50 descending Sentinel-1A satellite images collected between 2014 and 2019. Sentinel-1 images bring new improvements due to their wide coverage and high revisiting time, which allows us to make a wide area processing. Due to the high depth of oil wells (4,300 meters), as well as the stone type of the region’s bed in some areas, we needed to calculate the magnitude of subsidence. The results show the maximum displacement rate in this area is 18 mm between 2014 and 2019 in the radar line of sight direction, but no subsidence took place between 2003 and 2009 .The results of the study confirm typical patterns of subsidence induced by oil extraction. Also, since 2017, with the onset of Iran’s oil extraction and the intensification of Iraq's oil exploration, subsidence has taken place with a steeper slope. The displacement of the area before and after this date is modelled with two lines.

scholarly journals Application of an improved clustering approach on GPS height time series at CMONOC stations in Southwestern China

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Shuguang Wu ◽  
Zhao Li ◽  
Houpu Li ◽  
Guigen Nie ◽  
Jingnan Liu ◽  
...  
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Clustering Algorithm ◽  
Surface Deformation ◽  
Correlation Coefficients ◽  
Significant Negative Correlation ◽  
Southwestern China ◽  
Three Gorges ◽  
The Three Gorges ◽  
Deformation Features

AbstractThe hydrological, geological and meteorological conditions in southwestern China are relatively complex, so that the land surface deformation presents various features. Using 58 Crustal Movement Observation Network of China (CMONOC) stations across four provinces in Southwestern China, we adopt an improved clustering algorithm to classify 49 stations into 12 clusters with different similarity levels. Our results show that the average annual signals of GPS stations within each cluster have strong consistency, while obvious differences exist among the 12 clusters, indicating that clustering algorithm helps to describe surface deformation features more accurately in regions with complex conditions. We then combine other earth observation techniques, such as the Gravity Recovery and Climate Experiment (GRACE) satellite datasets and surface loading models (SLM), and observe that GPS, GRACE and SLM have strong correlation in their monthly displacement series at GPS stations. After excluding non-clustered stations according to our previous clustering results, the correlation coefficients of GPS/GRACE and GPS/SLM are enhanced. Also, the RMS reduction rates of GPS coordinate time series have been improved after deducting displacements obtained from GRACE and SLM, thus the clustering algorithm proves to be effective in improving the consistency of three techniques in joint detection of surface deformation. Moreover, the vertical displacements of four riverside GPS stations in the Three Gorges Reservoir (TGR) area show significant negative correlation with water level of TGR, hence we conclude that the Three Gorges Dam (TGD) may directly affect the consistency of GPS annual signals of its upstream and downstream GPS stations. Graphical Abstract

scholarly journals LAND SUBSIDENCE MONITORING USING PS-InSAR TECHNIQUE FOR L-BAND SAR DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 995-997 ◽  
Author(s):  
S. Thapa ◽  
R. S. Chatterjee ◽  
K. B. Singh ◽  
D. Kumar
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Land Surface ◽  
Surface Deformation ◽  
Underground Mining ◽  
Ground Surface ◽  
Sar Interferometry ◽  
Persistent Scatterer Interferometry ◽  
Long Time ◽  
Subsidence Monitoring

Differential SAR-Interferometry (D-InSAR) is one of the potential source to measure land surface motion induced due to underground coal mining. However, this technique has many limitation such as atmospheric in homogeneities, spatial de-correlation, and temporal decorrelation. Persistent Scatterer Interferometry synthetic aperture radar (PS-InSAR) belongs to a family of time series InSAR technique, which utilizes the properties of some of the stable natural and anthropogenic targets which remain coherent over long time period. In this study PS-InSAR technique has been used to monitor land subsidence over selected location of Jharia Coal field which has been correlated with the ground levelling measurement. This time series deformation observed using PS InSAR helped us to understand the nature of the ground surface deformation due to underground mining activity.

scholarly journals Approximation of the process of changes in deformation of land surface using artificial neural networks

2018 ◽  
Vol 55 ◽  
pp. 00009
Author(s):  
Maria Mrówczyńska ◽  
Jacek Sztubecki
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Land Surface ◽  
Reference System ◽  
Surface Deformation ◽  
Copper Mining ◽  
Vertical Displacements ◽  
Artificial Neural ◽  
The Stability ◽  
The Impact

Artificial neural networks are an interesting method for modelling phenomena, including spatial phenomena, which are difficult to describe with known mathematical models. The properties of neural networks enable their practical application for solving such problems as: approximation, interpolation, identification and classification of patterns, compression, prediction, etc. The article presents the use of multilayer feedforward artificial neural networks for describing the process of changes in land surface deformation in the area of the Legnica-Głogów Copper Mining Centre, located in the southern part of the Fore Sudetic Monocline. Results provided by geodesic monitoring, which consists of land surveying and interpreting data obtained in this way, are undoubtedly significant in terms of identifying the impact of mining on the land surface the results of measurements carried out by precise levelling in the years 19672014 were used to determine changes in land deformation in the Legnica-Głogów Copper Mining Centre. The concept of a flexible reference system was used to assess the stability of points in the measurement and control network stabilized in order to determine vertical displacements. However, the reference system itself was identified on the basis of the critical value of the increment of the square of the norm of corrections to the observations.

scholarly journals Hazard Implications of the 2016 Mw 5.0 Cushing, OK Earthquake from a Joint Analysis of Damage and InSAR Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1715 ◽  
Author(s):  
Magali Barba-Sevilla ◽  
Bridger Baird ◽  
Abbie Liel ◽  
Kristy Tiampo
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Critical Infrastructure ◽  
European Space Agency ◽  
Significant Risk ◽  
Surface Displacement ◽  
Earthquake Sequence ◽  
Joint Analysis ◽  
Oil Storage ◽  
The Impact

The Cushing Hub in Oklahoma, one of the largest oil storage facilities in the world, is federally designated as critical national infrastructure. In 2014, the formerly aseismic city of Cushing experienced a Mw 4.0 and 4.3 induced earthquake sequence due to wastewater injection. Since then, an M4+ earthquake sequence has occurred annually (October 2014, September 2015, November 2016). Thus far, damage to critical infrastructure has been minimal; however, a larger earthquake could pose significant risk to the Cushing Hub. In addition to inducing earthquakes, wastewater injection also threatens the Cushing Hub through gradual surface uplift. To characterize the impact of wastewater injection on critical infrastructure, we use Differential Interferometric Synthetic Aperture Radar (DInSAR), a satellite radar technique, to observe ground surface displacement in Cushing before and during the induced Mw 5.0 event. Here, we process interferograms of Single Look Complex (SLC) radar data from the European Space Agency (ESA) Sentinel-1A satellite. The preearthquake interferograms are used to create a time series of cumulative surface displacement, while the coseismic interferograms are used to invert for earthquake source characteristics. The time series of surface displacement reveals 4–5.5 cm of uplift across Cushing over 17 months. The coseismic interferogram inversion suggests that the 2016 Mw 5.0 earthquake is shallower than estimated from seismic inversions alone. This shallower source depth should be taken into account in future hazard assessments for regional infrastructure. In addition, monitoring of surface deformation near wastewater injection wells can be used to characterize the subsurface dynamics and implement measures to mitigate damage to critical installations.

Drought-induced rapid subsidence in the Central Valley and its impact on the California Aqueduct

2020 ◽  
Author(s):  
Megan Miller ◽  
Cathleen Jones
Keyword(s):  
Time Series ◽  
Spatial Resolution ◽  
Land Surface ◽  
Surface Deformation ◽  
Central Valley ◽  
Drought Period ◽  
Aquifer Storage ◽  
Aquifer Systems ◽  
Level Data ◽  
L Band

<p>California’s Central Valley is the site of a complex heterogeneous aquifer system composed of alternating layers of coarse sediments and fine-grained confining material. Confined and semi-confined aquifer systems experience groundwater fluctuations coupled with elastic and inelastic land surface deformation. Data from the UAVSAR L-band synthetic aperture radar acquired between May 29, 2013 and November 27, 2018 were used to generate a high resolution deformation time series, and identify and track the development of a small subsidence feature that developed immediately adjacent to the California Aqueduct. By the end of the time series, the feature surface area that subsided 10 cm or more was 4452 hectares. The California Aqueduct supports Central Valley agriculture and large urban populations in Southern California, and a 10.5+ km segment of the aqueduct subsided 10 cm or more due to this one subsidence feature.  The Central Valley experienced a persistent drought starting in 2012, followed abruptly by a wet period from December 2016 to February 2018. The data were analyzed for the drought period in conjunction with hydraulic head level data from nearby wells to solve for aquifer storage parameters and volume storage loss.  We found the inelastic volume storage loss was 7.1x10<sup>6</sup> m<sup>3</sup>, or an average rate of 7x10<sup>3</sup> m<sup>3</sup>/day.</p><p>Compared to satellite SARs, UAVSAR has a higher spatial resolution (<2 m ground resolution) and signal-to-noise ratio. Because of these factors along with spatial averaging to reduce phase noise, accuracy is increased and temporal decorrelation is reduced, so a greater proportion of the scene produces useful measurements while maintaining a spatial resolution of 7mx7m. The resolution achieved with UAVSAR time series processing allows for modeling and monitoring localized subsidence features affecting the aqueduct that were not previously observed by satellite. The data, analysis, model, and results are described in this presentation.  It is notable that UAVSAR is a prototype for the L-band SAR to be launched on the NASA-ISRO SAR Mission (NISAR) in 2022.  In that context, we also discuss and compare the expected performance of the two instruments and highlight how these technologies can be used to study aquifer properties in areas where water level data are sparse in both space and time.</p>

Geographic Information System-Based Digital Catalog for Managing Subsurface Geotechnical and Geologic Data

2003 ◽  
Vol 1821 (1) ◽  
pp. 90-96
Author(s):  
Anne I. Veeger ◽  
Daniel P. Murray ◽  
O. Don Hermes ◽  
Jon C. Boothroyd ◽  
Nasir Hamidzada
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Rhode Island ◽  
Relational Database ◽  
Land Surface ◽  
Geographic Information ◽  
Transportation Systems ◽  
Borehole Data ◽  
Organic Sediment ◽  
Geologic Data

Knowledge of surface and subsurface geology and geotechnical properties is fundamental to planning, developing, and modernizing transportation systems. Through dynamic coupling of readily available areal geographic information system coverages and subsurface borehole data stored in a relational database, a spatially referenced digital catalog of borehole data was created for two pilot areas in Rhode Island. The borehole database was populated with data derived from Rhode Island Department of Transportation geotechnical reports and supplemental data from the U.S. Geological Survey groundwater site inventory system and local storm water and sewer projects. Most of these data were previously maintained in paper format, making historical or interproject data comparisons virtually impossible. Unification of these data in a single relational database yields two primary benefits: ( a) historical data are readily accessible for review and therefore can be incorporated easily into the planning stages of new projects and ( b) sophisticated analysis of the region becomes possible with access to data from multiple projects with both spatial and temporal coverage. Geologic data include bedrock geology, surface outcrops, unconsolidated materials, soil type, topographic and orthophotographic base maps, and location of boreholes and wells. Subsurface data include land surface elevation, depth to water table, depth to bedrock, presence of fill, high and low blow-count zones, and organic sediment. The digital catalog is distributed on a CD-ROM that includes ArcView project files and an Access relational database. The borehole data are also accessible through the Internet, with retrieval access for all users and data entry privileges for registered users.

scholarly journals Investigating Ground Subsidence and the Causes over the Whole Jiangsu Province, China Using Sentinel-1 SAR Data

2021 ◽  
Vol 13 (2) ◽  
pp. 179
Author(s):  
Yonghong Zhang ◽  
Hongan Wu ◽  
Mingju Li ◽  
Yonghui Kang ◽  
Zhong Lu
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Surface Deformation ◽  
Underground Mining ◽  
Ground Deformation ◽  
Ground Surface ◽  
Data Retrieval ◽  
Field Work ◽  
Jiangsu Province ◽  
Ground Subsidence

Interferometric synthetic aperture radar (InSAR) mapping of localized ground surface deformation has become an important tool to manage subsidence-related geohazards. However, monitoring land surface deformation using InSAR at high spatial resolution over a large region is still a formidable task. In this paper, we report a research on investigating ground subsidence and the causes over the entire 107, 200 km2 province of Jiangsu, China, using time-series InSAR. The Sentinel-1 Interferometric Wide-swath (IW) images of 6 frames are used to map ground subsidence over the whole province for the period 2016–2018. We present processing methodology in detail, with emphasis on the three-level co-registration scheme of S-1 data, retrieval of mean subsidence velocity (MSV) and subsidence time series, and mosaicking of multiple frames of results. The MSV and subsidence time series are generated for 9,276,214 selected coherent pixels (CPs) over the Jiangsu territory. Using 688 leveling measurements in evaluation, the derived MSV map of Jiangsu province shows an accuracy of 3.9 mm/year. Moreover, subsidence causes of the province are analyzed based on InSAR-derived subsidence characteristics, historical optical images, and field-work findings. Main factors accounting for the observed subsidence include: underground mining, groundwater withdrawal, soil consolidations of marine reclamation, and land-use transition from agricultural (paddy) to industrial land. This research demonstrates not only the capability of S-1 data in mapping ground deformation over wide areas in coastal and heavily vegetated region of China, but also the potential of inferring valuable knowledge from InSAR-derived results.

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