Modelling ground deformation in Tenerife (Canary Islands) during 2003-2010

2021 ◽  
Author(s):  
Monika Przeor ◽  
Luca D'Auria ◽  
Susi Pepe ◽  
Pietro Tizzani
Keyword(s):  
Time Series ◽  
Ground Deformation ◽  
Point Of View ◽  
Analytical Models ◽  
Volcanic Complex ◽  
Statistical Tool ◽  
Noise Component ◽  
Envisat Asar ◽  
Tectonic Features ◽  
Teide Volcano

<p>Tenerife is the biggest island of the Canaries and one of the most active from the volcanological point of view. The island is geologically complex, and its main volcano-tectonic features are three volcanic rifts and the composite volcanic complex of Teide-Las Cañadas. The latter is located in the central part of the island at the intersection of Tenerife principal rifts. Teide volcano, with its 3718 m of elevation constitutes the most prominent topographical feature of the island. Being a densely populated active volcanic island, Tenerife is characterised by a high volcanic risk. For this reason, the island requires an advanced and efficient volcano monitoring system. Among the geophysical parameters that could be useful to forecast an oncoming volcanic eruption, the ground deformation is relevant for detecting the approach of magma to the surface.</p><p>This study aim is to analyse the ground deformation in the surroundings of the Teide-Las Cañadas complex.  For this purpose, we studied the ground deformation of Tenerife by using a set of Synthetic Aperture Radar (SAR) images acquired between 2003 and 2010 by the ENVISAT ASAR sensor and processed through a DInSAR-SBAS technique. The DInSAR SBAS time series revealed a ground deformation in the central part of the island, coinciding with the Teide volcano. A similar deformation was already evidenced by Fernández et al. (2009) from 2004 to 2005.</p><p>We investigated the source of this ground deformation by applying the statistical tool of Independent Component Analysis (ICA) to the dataset. ICA allowed separating the spatial patterns of deformation into four components. We attributed three of them to an actual ground deformation, while the fourth seems to be only related to the noise component of data. The first component (ICA1) displays a spatial pattern localised in Teide volcano neighbourhoods and consists of a ground uplift of few centimetres. The deformation associated with this component starts in 2005 and persists along the rest of the time series. The second component (ICA2) of the ground deformation is localised in the South/South-West part of Las Cañadas rim while the third component (ICA3) is localised to the East of Teide volcano. We performed inverse modelling to analyse the source of the ground deformation related to ICA1 to retrieve the location, the geometry and the temporal evolution of this source. The inversion was based on analytical models of ground deformation as well as on Finite-Element-Modelling. The result showed that the ground deformation is associated with a shallow sill-like structure, located beneath Teide volcano, possibly reflecting a hydrothermal reservoir. The knowledge of this source geometry could be of significant interest to better understand ground deformation data of possible future volcanic crisis. </p>

scholarly journals Long-range ground deformation monitoring by InSAR analysis

2015 ◽  
Vol 372 ◽  
pp. 343-346 ◽  
Author(s):  
S. Rokugawa ◽  
T. Nakamura
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
Envisat Asar ◽  
Series Analysis ◽  
Kanto District

Abstract. InSAR (Interferometric Synthetic Aperture Radar) analysis is an effective technique to map 3-dimensional surface deformation with high spatial resolution. The aim of this study was to evaluate the capability of InSAR analysis when applied to ground monitoring of an environmental disaster. We performed a time series InSAR analysis using ENVISAT/ASAR and ALOS/PALSAR data and commercial software to investigate subsidence around the Kanto District of Japan. We also investigated techniques for efficient early detection of landslides in Kyushu using time series analysis that incorporated synthetic aperture radar (SAR) images. ENVISAT/ASAR data acquired from 2003–2010 and ALOS/PALSAR data acquired from 2006–2011 were used to detect poorly expressed geomorphological deformation by conducting time series analyses of periodically acquired SAR data. In addition, to remove noise caused by geographical feature stripes or phase retardation, we applied median filtering, histogram extraction processing, and clarification of the displacement with a Laplacian filter. The main functions of the InSAR time series analysis are the calculation of phase differences between two images and the inversion with smoothness constraint for the estimation of deformation along the line of sight. The results enabled us to establish criteria for the selection of suitable InSAR data pairs, and provided the final error estimation of the derived surface deformation. The results of the analysis in the Kanto District suggested that localized areas of uplift and subsidence have occurred at irregular intervals in this area. Furthermore, the method offers the possibility of early warning of environmental disasters such as landslide and abrupt subsidence. Our results confirm the effectiveness of InSAR analysis for the monitoring of ground deformation over wide areas via the detection of localized subsidence and landslides.

Der Sommer und Herbst 2003 aus phänologischer Sicht | Summer and autumn 2003 from a phenological point of view

2004 ◽  
Vol 155 (5) ◽  
pp. 142-145 ◽  
Author(s):  
Claudio Defila
Keyword(s):  
Time Series ◽  
New Record ◽  
Point Of View ◽  
Late Spring ◽  
Mean Deviation ◽  
Leaf Shedding ◽  
The Mean ◽  
Very High ◽  
Selection Of

The record-breaking heatwave of 2003 also had an impact on the vegetation in Switzerland. To examine its influences seven phenological late spring and summer phases were evaluated together with six phases in the autumn from a selection of stations. 30% of the 122 chosen phenological time series in late spring and summer phases set a new record (earliest arrival). The proportion of very early arrivals is very high and the mean deviation from the norm is between 10 and 20 days. The situation was less extreme in autumn, where 20% of the 103 time series chosen set a new record. The majority of the phenological arrivals were found in the class «normal» but the class«very early» is still well represented. The mean precocity lies between five and twenty days. As far as the leaf shedding of the beech is concerned, there was even a slight delay of around six days. The evaluation serves to show that the heatwave of 2003 strongly influenced the phenological events of summer and spring.

GROUNDWATER TIME SERIES

1970 ◽  
Vol 1 (3) ◽  
pp. 181-205 ◽  
Author(s):  
ERIK ERIKSSON
Keyword(s):  
Time Series ◽  
Point Of View ◽  
Hydrologic Models ◽  
Physical Point ◽  
Run Off ◽  
Fort Collins ◽  
Statistical Sense ◽  
Full Benefit ◽  
Future Work ◽  
Prediction Problems

The term “stochastic hydrology” implies a statistical approach to hydrologic problems as opposed to classic hydrology which can be considered deterministic in its approach. During the International Hydrology Symposium, held 6-8 September 1967 at Fort Collins, a number of hydrology papers were presented consisting to a large extent of studies on long records of hydrological elements such as river run-off, these being treated as time series in the statistical sense. This approach is, no doubt, of importance for future work especially in relation to prediction problems, and there seems to be no fundamental difficulty for introducing the stochastic concepts into various hydrologic models. There is, however, some developmental work required – not to speak of educational in respect to hydrologists – before the full benefit of the technique is obtained. The present paper is to some extent an exercise in the statistical study of hydrological time series – far from complete – and to some extent an effort to interpret certain features of such time series from a physical point of view. The material used is 30 years of groundwater level observations in an esker south of Uppsala, the observations being discussed recently by Hallgren & Sands-borg (1968).

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

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

2021 ◽  
Vol 13 (15) ◽  
pp. 3044
Author(s):  
Mingjie Liao ◽  
Rui Zhang ◽  
Jichao Lv ◽  
Bin Yu ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ground Deformation ◽  
Dynamic Change ◽  
Deformation Monitoring ◽  
Chinese Loess Plateau ◽  
Ground Subsidence ◽  
Shanxi Province ◽  
Environment Change ◽  
Loess Area

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

scholarly journals Countrywide Monitoring of Ground Deformation Using InSAR Time Series: A Case Study from Qatar

2021 ◽  
Vol 13 (4) ◽  
pp. 702
Author(s):  
Mustafa Kemal Emil ◽  
Mohamed Sultan ◽  
Khaled Alakhras ◽  
Guzalay Sataer ◽  
Sabreen Gozi ◽  
...  
Keyword(s):  
Time Series ◽  
Arabian Peninsula ◽  
Ground Deformation ◽  
Anthropogenic Activities ◽  
Urban Centers ◽  
Alos Palsar ◽  
Groundwater Levels ◽  
Temporal Correlations ◽  
Time Series Approach ◽  
Sbas Insar

Over the past few decades the country of Qatar has been one of the fastest growing economies in the Middle East; it has witnessed a rapid increase in its population, growth of its urban centers, and development of its natural resources. These anthropogenic activities compounded with natural forcings (e.g., climate change) will most likely introduce environmental effects that should be assessed. In this manuscript, we identify and assess one of these effects, namely, ground deformation over the entire country of Qatar. We use the Small Baseline Subset (SBAS) InSAR time series approach in conjunction with ALOS Palsar-1 (January 2007 to March 2011) and Sentinel-1 (March 2017 to December 2019) synthetic aperture radar (SAR) datasets to assess ground deformation and conduct spatial and temporal correlations between the observed deformation with relevant datasets to identify the controlling factors. The findings indicate: (1) the deformation products revealed areas of subsidence and uplift with high vertical velocities of up to 35 mm/yr; (2) the deformation rates were consistent with those extracted from the continuously operating reference GPS stations of Qatar; (3) many inland and coastal sabkhas (salt flats) showed evidence for uplift (up to 35 mm/yr) due to the continuous evaporation of the saline waters within the sabkhas and the deposition of the evaporites in the surficial and near-surficial sabkha sediments; (4) the increased precipitation during Sentinel-1 period compared to the ALOS Palsar-1 period led to a rise in groundwater levels and an increase in the areas occupied by surface water within the sabkhas, which in turn increased the rate of deposition of the evaporitic sediments; (5) high subsidence rates (up to 14 mm/yr) were detected over landfills and dumpsites, caused by mechanical compaction and biochemical processes; and (6) the deformation rates over areas surrounding known sinkhole locations were low (+/−2 mm/yr). We suggest that this study can pave the way to similar countrywide studies over the remaining Arabian Peninsula countries and to the development of a ground motion monitoring system for the entire Arabian Peninsula.

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

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

scholarly journals Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

2019 ◽  
Vol 93 (12) ◽  
pp. 2651-2660 ◽  
Author(s):  
Sergey Samsonov
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Three Dimensional ◽  
Data Sets ◽  
Ice Flow ◽  
The North ◽  
Glacier Ice ◽  
Deformation Component ◽  
3D Deformation

AbstractThe previously presented Multidimensional Small Baseline Subset (MSBAS-2D) technique computes two-dimensional (2D), east and vertical, ground deformation time series from two or more ascending and descending Differential Interferometric Synthetic Aperture Radar (DInSAR) data sets by assuming that the contribution of the north deformation component is negligible. DInSAR data sets can be acquired with different temporal and spatial resolutions, viewing geometries and wavelengths. The MSBAS-2D technique has previously been used for mapping deformation due to mining, urban development, carbon sequestration, permafrost aggradation and pingo growth, and volcanic activities. In the case of glacier ice flow, the north deformation component is often too large to be negligible. Historically, the surface-parallel flow (SPF) constraint was used to compute the static three-dimensional (3D) velocity field at various glaciers. A novel MSBAS-3D technique has been developed for computing 3D deformation time series where the SPF constraint is utilized. This technique is used for mapping 3D deformation at the Barnes Ice Cap, Baffin Island, Nunavut, Canada, during January–March 2015, and the MSBAS-2D and MSBAS-3D solutions are compared. The MSBAS-3D technique can be used for studying glacier ice flow at other glaciers and other surface deformation processes with large north deformation component, such as landslides. The software implementation of MSBAS-3D technique can be downloaded from http://insar.ca/.

Further Notes on Structural Types and Earth Movements

1931 ◽  
Vol 68 (1) ◽  
pp. 15-24
Author(s):  
J. S. Lee
Keyword(s):  
South Africa ◽  
North America ◽  
Critical Points ◽  
Eastern China ◽  
Point Of View ◽  
Continental Scale ◽  
Structural Types ◽  
Tectonic Features ◽  
Geological Magazine

In a previous paper published in the Geological Magazine, the writer made an attempt to discuss the mechanism of earth movement on a continental scale purely from a tectonic point of view. The problem is so vast and involved that some of the vital points were hardly touched upon, partly because of lack of space and partly of literature. The arrival of the admirable works of Dr. A. du Toit and Dr. E. Krenkel has enabled the writer to deduce the mechanism of the movements of South Africa directly from its tectonic features, which process is thought to be far more reliable than the type of argument used in the previous case although the results arrived at are essentially the same. The earlier movements in North America are now seen to furnish evidence of the same type of mechanism as that which staged the later movements. An epsilon type of structure has been recognized in Eastern China, which was then described as a mere arc. The problem of the distribution of concealed coalfields in England was in the previous paper barely touched upon. It is now proposed to consider some of the critical points bearing on the problem.

Nonlinear Time-Series Prediction with Missing and Noisy Data

1998 ◽  
Vol 10 (3) ◽  
pp. 731-747 ◽  
Author(s):  
Volker Tresp ◽  
Reimar Hofmann
Keyword(s):  
Time Series ◽  
Stochastic Simulation ◽  
Time Series Prediction ◽  
Noisy Data ◽  
Nonlinear Time Series ◽  
Point Of View ◽  
Data Set ◽  
Sunspot Data ◽  
Error Bars ◽  
Probabilistic Point

We derive solutions for the problem of missing and noisy data in nonlinear time-series prediction from a probabilistic point of view. We discuss different approximations to the solutions—in particular, approximations that require either stochastic simulation or the substitution of a single estimate for the missing data. We show experimentally that commonly used heuristics can lead to suboptimal solutions. We show how error bars for the predictions can be derived and how our results can be applied to K-step prediction. We verify our solutions using two chaotic time series and the sunspot data set. In particular, we show that for K-step prediction, stochastic simulation is superior to simply iterating the predictor.

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