From Sentinel-1 data processing to field survey: an operating workflow for the continuous monitoring of the Earth surface deformations

2021 ◽  
Author(s):  
Davide Festa ◽  
Pierluigi Confuorto ◽  
Matteo Del Soldato ◽  
Silvia Bianchini ◽  
Nicola Casagli
Keyword(s):  
Data Processing ◽  
Continuous Monitoring ◽  
Ground Deformation ◽  
Community Research ◽  
Data Mining Algorithm ◽  
Earth Surface ◽  
Radar Images ◽  
Surface Deformations ◽  
Area Of Interest ◽  
Italian Regions

<p>The launch of the Sentinel-1 constellation by the European Copernicus Program, primarily devoted to scientific community research, has allowed acquiring huge volumes of radar images with worldwide coverage and a short temporal sampling (12 days reduced to 6 days thanks to their position at 180° in the same orbit). The systematic collection of imagery and the repeated processing of each new pair of images acquired opened the unprecedent possibility of conducting a continuous monitoring of Earth surface deformations, such as subsidence and slope instabilities over different geomorphological settings. At present, Tuscany, Veneto and Valle d’Aosta regions (Italy) are benefiting from systematical Sentinel-1-based monitoring of geological and geomorphological hazards. The promising outcomes so far obtained constitute a decisive step towards near-real-time monitoring and therefore a valid support for geohazard risk management activities. Retracing the pattern set by the encouraging results from the three Italian Regions, an operating workflow chain is proposed in the framework of an operational monitoring service, from the collection of satellite images to the possibility of conducting field surveys. The procedure is based on 4 different steps: i) continuous collection of Sentinel-1 images, constant data processing through an MT-InSAR (Multi-Temporal Interferometric Synthetic Aperture Radar) technique and exploitation of a data-mining algorithm able to retain only meaningful Measurement Points (MP) in terms of abrupt change of displacement rate; ii) radar-interpretation of the filtered MP for the detection of the possible causes of the anomalies through the use of ancillary informative layers or pre-existing databases; iii) dissemination of the relevant radar-interpreted information to hydrological risk managing actors by a direct alert or periodic bulletins; iv) field investigation, preliminary risk assessment and possible remedial works design. The procedure was successfully applied gathering evidence of its usefulness in practical terms. The cases of the Bosmatto landslide (Valle d’Aosta Region) and the case of the Zeri Landslide (Tuscany Region) which belong to two alpine and apennine environments, respectively, are reported. In the first example, in response to a relevant acceleration interpreted from the MP available on the area of interest, an alert was sent to the regional officers who increased their awareness related to the risk posed by the Bosmatto Landslide. In the second example, a monitoring bulletin which is periodically delivered for the Tuscany Region pointed out the meaningfulness and persistency of anomalies identified in the Zeri municipality. This led the regional authorities to conduct a site investigation oriented to the assessment of preliminary risks. The presented results highlight the effective benefits-cost ratio, the high precision and the short amount of time required to complete the procedure representing a best practice for the early detection of ground deformation events.</p>

Linear discontinuous ground deformation detection based on coherence analysis of pre and post event radar image pairs

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Bartosz Apanowicz
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
Underground Mining ◽  
Ground Deformation ◽  
Satellite Image ◽  
Coherence Analysis ◽  
Radar Images ◽  
Research Areas ◽  
Previous State ◽  
Signal Correlation

Abstract The article presents information on how to use satellite interferometry to detect linear discontinuous ground deformation [LDGD] caused by underground mining. Assumptions were made based on the properties of the SAR signal correlation coefficient (coherence). Places of LDGD have been identified based on these assumptions. Changes taking place on the surface between two acquisitions lead to worse correlation between two radar images. This results in lower values of the SAR signal correlation coefficient in the coherence maps. Therefore, it was assumed that the formation of LDGD could reduce the coherence value compared to the previous state. The second assumption was an increase in the standard deviation of coherence, which is a classic measurement of variability. Therefore any changes in the surface should lead to increasing standard deviation of coherence compared to the previous state. Images from the Sentinel-1 satellite and provided by the ESA were used for analysis. The research is presented on the basis of two research areas located in the Upper Silesian Coal Basin in the south of Poland. The area in which LDGD could occur was limited to 6 % of the total area in case 1 and 36 % in case 2 by applying an appropriate methodology of satellite image coherence analysis. This paper is an introduction to the development of a method of detecting LDGDs caused by underground mining and to study these issues further.

Continuous monitoring of ground deformational scenario of Veneto region (Italy) through Sentinel-1 data

2020 ◽  
Author(s):  
Pierluigi Confuorto ◽  
Silvia Bianchini ◽  
Davide Festa ◽  
Federico Raspini ◽  
Nicola Casagli
Keyword(s):  
Urban Areas ◽  
Continuous Monitoring ◽  
Surface Deformation ◽  
Risk Mitigation ◽  
Ground Deformation ◽  
European Space Agency ◽  
Economic Losses ◽  
Deformation Pattern ◽  
Veneto Region ◽  
Natural Risk

<p>Continuous monitoring of the Earth surface is fundamental for the development and the evolution of the society, to reduce the risks posed by major geo-hazards like landslides, subsidence and sinkholes, which have a large impact on urban areas and can cause direct and indirect socio-economic losses. The start of spaceborne Synthetic Aperture Radar systems represented a milestone for the control of the territory, since SAR-based monitoring enables accurate measurement of the surface deformation over large areas, with a frequency dependent on the revisit time of the satellites. In this sense, the launch of the European Space Agency Sentinel-1 mission, characterized by a 6-days repeat pass, portrayed a great innovation and a step towards near-real-time monitoring. In this work, we present the first results of the continuous monitoring of the Veneto region (Northeastern Italy) performed by means of Sentinel-1 data, in the framework of an operational monitoring service. The procedure applied is based on a systematic processing chain made of four steps: i) Continuous generation of Sentinel-1 ground deformation maps, providing Measurement Points (MP) characterized by annual average velocity (mm/yr) and displacement Time Series (TS); ii) TS screening and classification, applied after each new satellite acquisition, to identify any change in the deformation pattern, according to a selected threshold; iii) constant update of the “anomalies” and their classification, according to the type of deformation; iv) warning to local authorities, in case of persistent and significant anomalous trends which require further investigations and field surveys. Its first application on the Veneto region shows promising outcomes, evidencing those areas characterized by movements that can be detected by SAR satellites. A few examples of this operational procedure are here shown, such as the cases of Lamosano, where a translational slide involves the local village, or of Recoaro Terme, where the Mt. Rotolon landslide is constantly studied. Moreover, subsidence is also a major threat in Veneto region, testified by the long-term phenomena of the NE plain (Verona and Vicenza provinces) and by the city of Venice, where the interaction of tides and subsidence causes the periodical flooding (“acqua alta”) of the renowned UNESCO site. The presented results want to demonstrate that the constant and continuous monitoring of the territory through Sentinel-1 data represents a best practice for the detection of ground deformation events, aiming at the natural risk mitigation for the development of the human environment.</p>

scholarly journals Analysis of sales levels of pharmaceutical products by using data mining algorithm C45

2021 ◽  
Vol 22 (1) ◽  
pp. 476
Author(s):  
Rini Sovia ◽  
Abulwafa Muhammad ◽  
Syafri Arlis ◽  
Guslendra Guslendra ◽  
Sarjon Defit
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Data Processing ◽  
Medicinal Product ◽  
Pharmaceutical Products ◽  
Data Mining Algorithm ◽  
Sales Data ◽  
Great Demand ◽  
Mining Algorithm ◽  
Using Data

<p>This research was conducted to analyze the level of sales of pharmaceutical products at a Pharmacy. This is done to find out the types of products that have high and low sales levels. This study uses the C45 Data Mining Algorithm concept that will produce a conclusion on the prediction of sales of pharmaceutical products through data processing obtained from sales transactions at pharmacies. This C45 algorithm will form a decision tree that provides users with knowledge about products that are in great demand by consumers based on sales data and predetermined variables. The final result of the C45 algorithm produces a number of rules that can identify the inheritance of a type of medicinal product. C45 algorithm is able to produce 20 types of categories that will be labeled goals based on the number of pharmaceutical products, since it can be concluded that C45 successfully defines 55% of the existing objective categories.</p>

scholarly journals Integrated Data Processing Methodology for Airborne Repeat-pass Differential SAR Interferometry

2014 ◽  
Vol XL-1 ◽  
pp. 109-112
Author(s):  
C. Dou ◽  
H. Guo ◽  
C. Han ◽  
X. Yue ◽  
Y. Zhao
Keyword(s):  
Data Processing ◽  
Ground Deformation ◽  
Sar Interferometry ◽  
Accurate Estimation ◽  
Processing Theory ◽  
Residual Motion ◽  
Sar Imagery ◽  
Airborne Sar ◽  
Integration Data ◽  
Differential Sar Interferometry

Short temporal baseline and multiple ground deformation information can be derived from the airborne differential synthetic aperture radar Interforemetry (D-InSAR). However, affected by the turbulence of the air, the aircraft would deviate from the designed flight path with high frequent vibrations and changes both in the flight trajectory and attitude. Restricted by the accuracy of the position and orientation system (POS), these high frequent deviations can not be accurately reported, which would pose great challenges in motion compensation and interferometric process. Thus, these challenges constrain its wider applications. The objective of this paper is to investigate the accurate estimation and compensation of the residual motion errors in the airborne SAR imagery and time-varying baseline errors between the diffirent data acquirations, furthermore, to explore the integration data processing theory for the airborne D-InSAR system, and thus help to accomplish the correct derivation of the ground deformation by using the airborne D-InSAR measurements.

scholarly journals STRATEGIES FOR PS PROCESSING OF LARGE SENTINEL-1 DATASETS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 99-106
Author(s):  
M. Evers ◽  
H. Hammer ◽  
A. Thiele ◽  
K. Schulz
Keyword(s):  
Data Acquisition ◽  
Monitoring System ◽  
High Frequency ◽  
Critical Infrastructure ◽  
Active Tectonics ◽  
Sar Images ◽  
Surface Deformations ◽  
Area Of Interest ◽  
Processing Strategies

Abstract. Several advanced DInSAR techniques have been used to map surface deformations due to volcanism, active tectonics, landslides, subsidence, and uplift as well as to monitor the deformation of critical infrastructure such as bridges and dams. Recently, studies have explored the potential of these techniques to be integrated into a permanently operating monitoring system. ESA’s Sentinel-1 satellites have been providing SAR images for such a purpose since 2014. Nowadays, it is easy to access more than 230 SAR images of any area of interest, and update this dataset every six days with a new image.Due to the high frequency of the data acquisition, the question arises on how to best handle such a dataset. Is it suitable to always consider the whole available dataset or would a partial processing of the dataset and combining the results at a later point be more appropriate? To answer these questions, three different processing strategies are investigated in this paper. The first is a continuously growing dataset and for the second and third strategy, the dataset was divided into sub-stacks with and without overlap. In this study, the key parameters of each strategy are analyzed. In addition, the size of the sub-stacks is varied and the results are compared.

CHIPSCANNER: Reverse Engineering Solution for Microchips at the Nanometer-Scale

2011 ◽  
Author(s):  
Joseph Klingfus ◽  
Kevin Burcham ◽  
Martin Rasche ◽  
Thomas Borchert ◽  
Niklas Damnik
Keyword(s):  
Data Collection ◽  
Data Processing ◽  
Reverse Engineering ◽  
Nanometer Scale ◽  
Large Area ◽  
Image Capture ◽  
Sem Image ◽  
Reverse Engineer ◽  
Area Of Interest ◽  
Insight Into

Abstract Chipscanning is the high-resolution, large-area, SEM image capture of complete (or partial) IC devices. Images are acquired sequentially in matrix-array fashion over an area of interest and large image mosaics are created from the collection of smaller images. Chipscanning is of keen interest to those involved with component obsolescence, design verification, anti-counterfeiting, etc. Chipscanning, and subsequent processing of the images, can also be used to reverse engineer an IC device. The reverse engineering process can be broken down into three main tasks; sample preparation, data collection, and data processing. We present practical insight into the data collection and data processing tasks and discuss an instrument platform uniquely suited for imaging such devices.

Using corner reflectors for enhancing landslide and infrastructure monitoring in the UK

2021 ◽  
Author(s):  
Krisztina Kelevitz ◽  
Jonathan E Chambers ◽  
Jimmy Boyd ◽  
Alessandro Novellino ◽  
Colm Jordan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Continuous Monitoring ◽  
New Technologies ◽  
Ground Deformation ◽  
Tall Buildings ◽  
Limiting Factor ◽  
Destructive Interference ◽  
Digital Environment ◽  
Infrastructure Monitoring ◽  
The Uk

&lt;p&gt;With the advances of ESA&amp;#8217;s Sentinel-1 InSAR (Interferometric Synthetic Aperture Radar) mission there are freely available remote sensing ground deformation observations all over the globe that allows continuous monitoring of natural hazards and structural instabilities. The Digital Environment initiative in the UK aims to include these remote sensing data in the effort of forecasting and mitigating hazards across the UK.&lt;/p&gt;&lt;p&gt;However, analyses of low coherence areas (e.g. forested and vegetated areas) with conventional InSAR methodologies are difficult to perform due to the limiting factor of temporal and geometric decorrelation. Even the application of the permanent scatterer (PS) technique may not be successful when there is a low density of stable radar targets. Using artificial reflectors with high radar cross section (RCS) can be a way of overcome this limitation and achieve measurements with a good signal-to-clutter ratio (SCR).&lt;/p&gt;&lt;p&gt;In order to be able to include Sentinel-1 data in the UK&amp;#8217;s Digital Environment it is important to understand the advantages and limitations of these observations and interpret them appropriately. The Hollin Hill landslide observatory in North Yorkshire is used by the British Geological Survey in their efforts to understand landslide processes, and to trial new technologies and methodologies for slope stability characterisation and monitoring.&lt;/p&gt;&lt;p&gt;We present InSAR results of the Hollin Hill landslide where a variety of ground-based geophysical measurements (e.g. GPS, Electric resistivity tomography, meteorological observations) are available for comparison with InSAR data. We use Sentinel-1 InSAR data acquired between Oct 2015 and Jan 2021 to study the behaviour of this landslide. We find that the Line of Sight component of the down-slope movement is 2.7 mm/yr in the descending track, and 7.5-7.7 mm/yr in the ascending track. The InSAR measurements also highlight the seasonal behaviour of this landslide.&lt;/p&gt;&lt;p&gt;In July 2019 six corner reflectors were installed to improve the coherence of the InSAR measurements, especially in the ascending acquisition mode. We present comparison with ground-based measurements such as the movement recorded by the GPS measurements of the pegs of the ERT survey or the moisture recorded by the various instruments at the site, and show the improvement introduced by the corner reflectors.&lt;/p&gt;&lt;p&gt;In addition we present results of an experiment that explores the use of smaller corner reflectors for potential urban applications of infrastructure monitoring. A single corner reflector needs to be at least ~67cm wide and tall to be seen by the Sentinel-1 satellites. We show that by placing 4 reflectors with 33cm dimensions in the same pixel coherent signal can be acquired. It is feasible to install small reflectors on bridges, tall buildings, or incorporate &amp;#8220;corner-like&amp;#8221; features in newly built structures,but care needs to be taken on the precise spacing of the reflectors to avoid destructive interference. Continuous monitoring of infrastructure with remote sensing and machine learning can alert to potential failures where further investigation is needed.&lt;/p&gt;

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