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Journal articles on the topic 'SqueeSAR'

Author: Grafiati

Published: 10 March 2023

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1

Bischoff, Christine A., Alessandro Ferretti, Fabrizio Novali, Andrea Uttini, Chiara Giannico, and Francesco Meloni. "Nationwide deformation monitoring with SqueeSAR® using Sentinel-1 data." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 31–37. http://dx.doi.org/10.5194/piahs-382-31-2020.

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Abstract. Subsidence can now be routinely mapped on a national scale thanks to ESA's Sentinel-1 sensors and advanced scalable SqueeSAR® processing. In order to be integrated into existing monitoring programmes, the SqueeSAR® datasets can be calibrated with GNSS measurements. The dense spatial coverage of SqueeSAR® deformation maps captures local deformation phenomena, and with appropriate calibration, can advance the understanding of regional deformation trends. The regular and reliable SAR image acquisitions by Sentinel-1, as well as significant improvements in the scalability of SqueeSAR® processing allow regular updates of deformation maps on a national scale. Filtering the large amount of data for relevant information is achieved by using an algorithm to detect changes in displacement trends.

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2

Mirzaee, S., M. Motagh, B. Akbari, H. U. Wetzel, and S. Roessner. "EVALUATING THREE INSAR TIME-SERIES METHODS TO ASSESS CREEP MOTION, CASE STUDY: MASOULEH LANDSLIDE IN NORTH IRAN." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-1/W1 (May 30, 2017): 223–28. http://dx.doi.org/10.5194/isprs-annals-iv-1-w1-223-2017.

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Masouleh is one of the ancient cities located in a high mountainous area in Gilan province of northern Iran. The region is threatened by a hazardous landslide, which was last activated in 1998, causing 32 dead and 45 injured. Significant temporal decorrelation caused by dense vegetation coverage within the landslide area makes the use of Synthetic Aperture Radar Interferometry (InSAR) for monitoring landslide movement very challenging. In this paper, we investigate the capability of three InSAR time-series techniques for evaluating creep motion on Masouleh landslide. The techniques are Persistent Scatterer Interferometry (PSI), Small BAseline Subset (SBAS) and SqueeSAR. The analysis is done using a dataset of 33 TerraSAR-X images in SpotLight (SL) mode covering a period of 15 months between June 2015 and September 2016. Results show the distinguished capability of SqueeSAR method in comparison to 2 other techniques for assessing landslide movement. The final number of scatterers in the landslide body detected by PSI and SBAS are about 70 and 120 respectively while this increases to about 345 in SqueeSAR. The coherence of interferograms improved by about 37% for SqueeSAR as compared to SBAS. The same rate of displacement was observed in those regions where all the methods were able to detect scatterers. Maximum rates of displacement detected by SqueeSAR technique in the northern edge, older and younger part of the landslide body are about -39, -65 and -22 mm/y, respectively.

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3

Ferretti, Alessandro, Alfio Fumagalli, Fabrizio Novali, Claudio Prati, Fabio Rocca, and Alessio Rucci. "A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR." IEEE Transactions on Geoscience and Remote Sensing 49, no. 9 (September 2011): 3460–70. http://dx.doi.org/10.1109/tgrs.2011.2124465.

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4

Li, Yongning, Weiwei Song, Baoxuan Jin, Xiaoqing Zuo, Yongfa Li, and Kai Chen. "A SqueeSAR Spatially Adaptive Filtering Algorithm Based on Hadoop Distributed Cluster Environment." Applied Sciences 13, no. 3 (January 31, 2023): 1869. http://dx.doi.org/10.3390/app13031869.

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Multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques analyze a study area using a set of SAR image data composed of time series, reaching millimeter surface subsidence accuracy. To effectively acquire the subsidence information in low-coherence areas without obvious features in non-urban areas, an MT-InSAR technique, called SqueeSAR, is proposed to improve the density of the subsidence points in the study area by fusing the distributed scatterers (DS). However, SqueeSAR filters the DS points individually during spatial adaptive filtering, which requires significant computer memory, which leads to low processing efficiency, and faces great challenges in large-area InSAR processing. We propose a spatially adaptive filtering parallelization strategy based on the Spark distributed computing engine in a Hadoop distributed cluster environment, which splits the different DS pixel point data into different computing nodes for parallel processing and effectively improves the filtering algorithm’s performance. To evaluate the effectiveness and accuracy of the proposed method, we conducted a performance evaluation and accuracy verification in and around the main city of Kunming with the original Sentinel-1A SLC data provided by ESA. Additionally, parallel calculation was performed in a YARN cluster comprising three computing nodes, which improved the performance of the filtering algorithm by a factor of 2.15, without affecting the filtering accuracy.

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Bitelli, Gabriele, Flavio Bonsignore, Sara Del Conte, Francesca Franci, Alessandro Lambertini, Fabrizio Novali, Paolo Severi, and Luca Vittuari. "Updating the subsidence map of Emilia-Romagna region (Italy) by integration of SAR interferometry and GNSS time series: the 2011–2016 period." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 39–44. http://dx.doi.org/10.5194/piahs-382-39-2020.

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Abstract. The analysis of the vertical movements of the soil in the Po River plane of the Emilia-Romagna Region (Italy) was updated through an interferometric analysis referred to the 2011–2016 time-span. This activity is a continuation of previous studies on the state of knowledge of vertical soil movements in the same area, analyzed firstly by levelling and GNSS and more recently by SAR interferometry for the periods 1992–2000, 2002–2006, 2006–2011, on behalf of the Emilia-Romagna Region. The survey area analysed was approximately 13 300 km2, which corresponds to the territory of the regional plain. The interferometric dataset was calibrated through the use of velocity time series of several permanent GNSS stations. Among the 36 stations analysed, 22 were included in the study area: 16 were used for the calibration and 6 as check points). The velocities required for the calibration of the SAR analysis were calculated in the period following the important seismic events that struck the territory of the Emilia Romagna Region in May 2012. The interferometric analysis was carried out by TRE ALTAMIRA using the SqueeSAR™ technology. In particular, in order to update the interferometric dataset to 2016, it was necessary to perform a joint processing of the available RADARSAT-1 data and of the data acquired by the RADARSAT-2 satellite using a specific operating mode of the SqueeSAR™ algorithm known as stitching; this approach allowed the joint processing of images acquired in the same geometry by these two satellites. The study of the time series of the GNSS permanent stations used to provide the velocity datum to the interferometric analysis, is described, and the results of the SqueeSAR™ interferometric processing are reported. Statistical analyses on the spatial distribution and the type of scatterers have been performed during the screening and validation procedures of the dataset, and for the identification and removal of the outliers. Finally, the resulting map is described in order to analyse the measured soil movements with respect to the results obtained in past analyses, and the possible geological and human-induced causes, which could have produced them.

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6

Bischoff, Christine Anna, Richard C. Ghail, Philippa J. Mason, Alessandro Ferretti, and John A. Davis. "Revealing millimetre-scale ground movements in London using SqueeSAR™." Quarterly Journal of Engineering Geology and Hydrogeology 53, no. 1 (March 22, 2019): 3–11. http://dx.doi.org/10.1144/qjegh2018-075.

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7

Kim, Sang-Wan. "Deformation monitoring of Daejeon City using ALOS-1 PALSAR - Comparing the results by PSInSAR and SqueeSAR -." Korean Journal of Remote Sensing 32, no. 6 (December 31, 2016): 567–77. http://dx.doi.org/10.7780/kjrs.2016.32.6.2.

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8

Попов, С. Е., and В. П. Потапов. "БЫСТРЫЙ АЛГОРИТМ ПОИСКА РАСПРЕДЕЛЕННЫХ РАССЕИВАТЕЛЕЙ SQUEESAR В ЗАДАЧЕ ПОСТРОЕНИЯ СКОРОСТЕЙ СМЕЩЕНИЙ ЗЕМНОЙ ПОВЕРХНОСТИ." Программирование, no. 6 (2021): 16–29. http://dx.doi.org/10.31857/s0132347421060066.

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9

Lagios, E., V. Sakkas, F. Novali, F. Bellotti, A. Ferretti, K. Vlachou, and V. Dietrich. "SqueeSAR™ and GPS ground deformation monitoring of Santorini Volcano (1992–2012): Tectonic implications." Tectonophysics 594 (May 2013): 38–59. http://dx.doi.org/10.1016/j.tecto.2013.03.012.

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10

Popov, S. E., and V. P. Potapov. "A Fast Search Algorithm for SqueeSAR Distributed Scatterers in the Problem of Calculating Displacement Velocities." Programming and Computer Software 47, no. 6 (November 2021): 426–38. http://dx.doi.org/10.1134/s0361768821060062.

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11

Ciampalini, Andrea, Federico Raspini, and William Frodella. "Back monitoring of the San Leo (northern Italy) rock cliff by means of SqueeSAR technique." Rendiconti Online della Società Geologica Italiana 41 (November 2016): 227–30. http://dx.doi.org/10.3301/rol.2016.135.

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12

Du, Zheyuan, Linlin Ge, Alex Hay-Man Ng, Qi Zhang, and Mehrisadat Makki Alamdari. "Assessment of the Accuracy Among the Common Persistent Scatterer and Distributed Scatterer Based on SqueeSAR Method." IEEE Geoscience and Remote Sensing Letters 15, no. 12 (December 2018): 1877–81. http://dx.doi.org/10.1109/lgrs.2018.2864274.

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13

Попов, Семен Евгеньевич, Вадим Петрович Потапов, and Роман Юрьевич Замараев. "Parallel algorithm for the identification of distributed scatterers in the problem of calculating the velocities of displacements of the earth’s surface by the Persistent Scaterrers method." Вычислительные технологии, no. 4(26) (October 8, 2021): 82–97. http://dx.doi.org/10.25743/ict.2021.26.4.008.

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Описывается программная реализация быстрого алгоритма поиска распределенных рассеивателей для задачи построения скоростей смещений земной поверхности на базе платформы Apache Spark. Рассматривается полная схема расчета скоростей смещений методом постоянных рассеивателей. Предложенный алгоритм интегрируется в схему после этапа совмещения с субпиксельной точностью стека изображений временн´ой серии радарных снимков космического аппарата Sentinel-1. Алгоритм не является итерационным и может быть реализован в парадигме параллельных вычислений. Применяемая платформа Apache Spark позволила распределенно обрабатывать массивы стека радарных данных (от 60 изображений) в памяти на большом количестве физических узлов в сетевой среде. Время поиска распределенных рассеивателей удалось снизить в среднем до десяти раз по сравнению с однопроцессорной реализацией алгоритма. Приведены сравнительные результаты тестирования вычислительной системы на демонстрационном кластере. Алгоритм реализован на языке программирования Python c подробным описанием методов и объектов The article describes implementation of the software for a fast algorithm which finds distributed scatterers for the problem of plotting displacement velocities of the earth’s surface based on the Apache Spark platform. The Persistent Scatterer (PS) method is widely used for estimating the displacement rates of the earth’s surface. It consists of the identification of coherent radar targets (interferogram pixels) that demonstrate high phase stability during the entire observation period. The most advanced algorithm for solving the identification problem is the SqueeSAR algorithm. It allows searching and processing Distributed Scatterers (DS) - specific reflectors, integrating them into the general scheme for calculating displacement velocities using the PS method. A careful analysis of the SqueeSAR algorithm has identified areas that are critical to its performance. The whole algorithm is based on an enumeration of the initial data, where nontrivial transformations are performed at each step. The stages of searching for adjacent points in the design window with multiple passes over the entire area of the image and solving the maximization problem when assessing the real values of the interferometric phases turned out to be noticeably costly. To speed up the processing of images, it is proposed to use the Apache Spark massively parallel computing platform. Specialized primitives (Resilient Distributed Data) for recurrent inmemory processing are available here. This provides multiple accesses to the radar data loaded into memory from each cluster node and allows logical dividing of the snapshot stack into subareas. Thus calculations are performed independently in massively parallel mode. Based on the SqueeSAR mathematical model, it is assumed that the radar image data and the calculated geophysical parameters calculated are common for each statistically homogeneous sample of nearby pixels. In accordance with this assumption, the uniformity (homogeneity) of the pixels is estimated within a given window. The search for distributed scatterers occurs independently by the sequence of shifts of the windows over the entire area of the image. The window is shifted along the width and height of the image with a step equal to the width and height of the window. Pairs of samples in the window are composed of vectors of complex pixel values in each of the N images. The validity of the Kolmogorov-Smirnov criterion is checked for each of the pairs. To estimate the values of the phases of homogeneous pixels, the maximization problem is solved. The method of maximum likelihood estimation (MLE) is considered. The construction of the correct MLE form is carried out by analyzing the statistical properties of the coherence matrix of all images using the complex Wishart distribution. The Apache Spark platform applied here permits processing of distributed radar data stack arrays in memory on a large number of physical nodes in a network environment. The average search time for distributed scatterers turned out to be 10 times less compared to the uniprocessor implementation of the algorithm. The algorithm is implemented in the Python programming language with a detailed description of the objects and methods of the algorithm. The proposed algorithm and its parallel implementation allows applying the developed approaches to other problems and types of satellite data for remote sensing of the earth from space

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14

Reinisch, Elena C., Michael Cardiff, John Akerley, Ian Warren, and Kurt L. Feigl. "Spatio–Temporal Analysis of Deformation at San Emidio Geothermal Field, Nevada, USA Between 1992 and 2010." Remote Sensing 11, no. 16 (August 19, 2019): 1935. http://dx.doi.org/10.3390/rs11161935.

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Although subsidence has been observed at the San Emidio geothermal field in Nevada using interferometric synthetic aperture radar since the early 1990s, the spatial extent and temporal evolution of the subsidence have not heretofore been quantified. Furthermore, the weather conditions and geographic location of San Emidio negatively affect interferometric image quality, causing low correlation amongst pairs. To address this, we introduce a new method for selecting pairs in areas of low correlation and small deformation signal using a minimum spanning tree method with a measure of image quality as the weighting criterion. We validate our pair selection approach by comparing our data products to SqueeSAR TM data products from a previous study at San Emidio. We also develop a deformation model which characterizes the spatial extent of subsidence at San Emidio in terms of volume change of the reservoir. After applying this deformation model to our data set of interferometric pairs, we examine the temporal relationship of the observed deformation with production and injection operations associated with geothermal power production.

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15

Alberti, Simona, Alessandro Ferretti, Gabriele Leoni, Claudio Margottini, and Daniele Spizzichino. "Surface deformation data in the archaeological site of Petra from medium-resolution satellite radar images and SqueeSAR™ algorithm." Journal of Cultural Heritage 25 (May 2017): 10–20. http://dx.doi.org/10.1016/j.culher.2017.01.005.

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16

Crippa, Chiara, Elena Valbuzzi, Paolo Frattini, Giovanni B. Crosta, Margherita C. Spreafico, and Federico Agliardi. "Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data." Landslides 18, no. 7 (April 6, 2021): 2445–63. http://dx.doi.org/10.1007/s10346-021-01654-0.

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AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

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17

Ansar, A. M. H., A. H. M. Din, A. S. A. Latip, and M. N. M. Reba. "A SHORT REVIEW ON PERSISTENT SCATTERER INTERFEROMETRY TECHNIQUES FOR SURFACE DEFORMATION MONITORING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W3-2021 (January 10, 2022): 23–31. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w3-2021-23-2022.

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Abstract. Technology advancement has urged the development of Interferometric Synthetic Aperture Radar (InSAR) to be upgraded and transformed. The main contribution of the InSAR technique is that the surface deformation changes measurements can achieve up to millimetre level precision. Environmental problems such as landslides, volcanoes, earthquakes, excessive underground water production, and other phenomena can cause the earth's surface deformation. Deformation monitoring of a surface is vital as unexpected movement, and future behaviour can be detected and predicted. InSAR time series analysis, known as Persistent Scatterer Interferometry (PSI), has become an essential tool for measuring surface deformation. Therefore, this study provides a review of the PSI techniques used to measure surface deformation changes. An overview of surface deformation and the basic principles of the four techniques that have been developed from the improvement of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), which is Small Baseline Subset (SBAS), Stanford Method for Persistent Scatterers (StaMPS), SqueeSAR and Quasi Persistent Scatterer (QPS) were summarised to perceive the ability of these techniques in monitoring surface deformation. This study also emphasises the effectiveness and restrictions of each developed technique and how they suit Malaysia conditions and environment. The future outlook for Malaysia in realising the PSI techniques for structural monitoring also discussed in this review. Finally, this review will lead to the implementation of appropriate techniques and better preparation for the country's structural development.

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18

Li, Gen, Zegang Ding, Mofan Li, Zihan Hu, Xiaotian Jia, Han Li, and Tao Zeng. "Bayesian Estimation of Land Deformation Combining Persistent and Distributed Scatterers." Remote Sensing 14, no. 14 (July 19, 2022): 3471. http://dx.doi.org/10.3390/rs14143471.

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Persistent Scatterer Interferometry (PSI) has been widely used for monitoring land deformation in urban areas with millimeter accuracy. In natural terrain, combining persistent scatterers (PSs) and distributed scatterers (DSs) to jointly estimate deformation, such as SqueeSAR, can enhance PSI results for denser and better coverage. However, the phase quality of a large number of DSs is far inferior to that of PSs, which deteriorates the deformation measurement accuracy. To solve the contradiction between measurement accuracy and coverage, a Bayesian estimation method of land deformation combining PSs and DSs is proposed in this paper. First, a two-level network is introduced into the traditional PSI to deal with PSs and DSs. In the first-level network, the Maximum Likelihood Estimation (MLE) of deformation parameters at PSs and high-quality DSs is obtained accurately. In the secondary-level network, the remaining DSs are connected to the nearest PSs or high-quality DSs, and the deformation parameters are estimated by Maximum A Posteriori (MAP) based on Bayesian theory. Due to the poor phase quality of the remaining DSs, MAP can achieve better estimation results than the MLE based on the spatial correlation of the deformation field. Simulation and Sentinel-1A satellite data results verified the feasibility and reliability of the proposed method. Regularized by the spatial deformation field derived from the high-quality PSs and DSs, the proposed method is expected to achieve robust results even in low-coherence areas, such as rural areas, vegetation coverage areas, or deserts.

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Shen, Peng, Changcheng Wang, and Jun Hu. "A Polarization Stacking Method for Optimizing Time-Series Interferometric Phases of Distributed Scatterers." Remote Sensing 14, no. 17 (August 25, 2022): 4168. http://dx.doi.org/10.3390/rs14174168.

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For time-series interferometric phases optimization of distributed scatterers (DSs), the SqueeSAR technology used the phase linking (PL) to extract the equivalent single-master (ESM) interferometric phases from the multilooking time-series coherence matrix. The Cramer–Rao lower bound (CRLB) for the PL describes the highest achievable estimation accuracy of the ESM phases, which depends on the number of looks and the time-series coherence magnitude matrix. With the abundance of time-series polarimetric SAR data, many scholars have studied the coherence magnitude-based polarimetric optimization methods for optimizing the DS’s time-series interferometric phases, for example, the widely-used exhaustive search polarimetric optimization (ESPO) algorithm. However, the traditional polarimetric optimization methods select the boundary extremums of the coherence region (CR) as the optimized complex coherence, which is usually biased from the free-noise one. Currently, in the polarimetric InSAR (PolInSAR) technology, Shen et al. innovatively considered polarimetric information as statistical samples and proposed the total power (TP) coherency matrix construction method for increasing the number of looks and reducing the interferometric phase noise. Therefore, to optimize the time-series interferometric phases for DS, this paper proposes performing a polarization stacking and extending the PolInSAR TP construction to the time-series PolInSAR (TSPolInSAR) data configuration, called the time-series TP (TSTP) method. Simulated and real experiments prove that the new TSTP construction method has better performance and higher efficiency than the single polarimetric and the traditional ESPO algorithms.

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Manzoni, Marco, Andrea Virgilio Monti-Guarnieri, Eugenio Realini, and Giovanna Venuti. "Joint Exploitation of SAR and GNSS for Atmospheric Phase Screens Retrieval Aimed at Numerical Weather Prediction Model Ingestion." Remote Sensing 12, no. 4 (February 17, 2020): 654. http://dx.doi.org/10.3390/rs12040654.

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This paper proposes a simple and fast method to estimate Atmospheric Phase Screens (APSs) by jointly exploit a stack of Synthetic Aperture Radar (SAR) images and a dataset of GNSS-derived atmospheric product. The output of this processing is conceived to be ingested by Numerical Weather Prediction Models (NWPMs) to improve weather forecasts. In order to provide wide and dense area coverage and to respect requirements in terms of spatial resolution of ingestion products in NWPMs, both Permanent Scatterers (PSs) and Distributed Scatterers (DSs) are jointly exploited. While the formers are by definition stable targets, but unevenly distributed, the latter are ubiquitous but stable only within a certain temporal baseline that can vary depending on the operational frequency of the radar. The proposed method is thus particularly suited for C, L, and P band missions with low temporal baseline between two consecutive acquisitions of the same scene: these conditions, that are both necessary to provide the dense space-time coverage required by meteorologists, allow for a reliable and robust estimation of APSs thanks to the intrinsic limitation of temporal decorrelation. The proposed technique integrates Zenith Total Delay (ZTD) products computed on a very sparse grid from a network of GNSS stations to correct for SAR orbital errors and to provide the missing phase constant from the derived APS map. In this paper, the complete workflow is explained, and a comparison of the derived APSs is performed with phase screens derived from state-of-the-art SAR processing workflow (SqueeSAR®).

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Mulas, M., M. Petitta, A. Corsini, S. Schneiderbauer, F. V. Mair, and C. Iasio. "Long-term monitoring of a deep-seated, slow-moving landslide by mean of C-band and X-band advanced interferometric products: the Corvara in Badia case study (Dolomites, Italy)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 827–29. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-827-2015.

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The availability of data from various Synthetic Aperture Radar (SAR) operating in X-Band and C-Band acquired in the last decades enables to monitor slopes affected by landslides. The ASI-founded project ‘LAWINA’ (2010 – 2012) aimed at the improvement of SAR – based monitoring techniques as well as at the integration of SAR data with data stemming from other sensors. Test case area of LAWINA has been a slow-moving landslide located up-stream of Corvara in Badia village in the Dolomites, Italy. Within the scope of the project different time-series obtained through 35 Envisat2, 40 Radarsat-1 and 46 Cosmo-SkyMed covering this test area have been processed in order to explore the potentials to analyse historical and near real time landslide dynamics. The SAR data are characterized by various geometric and temporal resolutions having been acquired by 3 sensors operating at different bands in different periods between 2003 and 2011. TeleRilevamento Europa (TRE) exploited these data in order to retrive displacement timeseries applying its proprietary SqueeSAR algorithm. After re-projecting Envisat-2 and Radarsat datasets according to the CSK Line Of Sight a comparison of displacements recorded by each sensor has been possible. For this purpose, we have selected areas characterized by the presence of Persistent Scatterers or Diffused Scatterers from at least two datasets. This multi-sensor approach allowed determining the slope displacement tracking during 8 years. Even though the different time series are not formally integrated each other, the result is accurate enough to allow the evaluation of the landslide’s behaviour and trend over several years.

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22

Comola, Francesco, Carlo Janna, Alberto Lovison, Marco Minini, Andrea Tamburini, and Pietro Teatini. "Efficient global optimization of reservoir geomechanical parameters based on synthetic aperture radar-derived ground displacements." GEOPHYSICS 81, no. 3 (May 2016): M23—M33. http://dx.doi.org/10.1190/geo2015-0402.1.

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When large volumes of fluids are removed from or injected into underground formations for, e.g., hydrocarbon and water production, [Formula: see text] storage, gas storage, and geothermal energy exploitation, monitoring of surface deformations coupled to numerical modeling improves our understanding of reservoir behavior. The ability to accurately simulate surface displacements, however, is often impaired by limited information on reservoir geometry, waterdrive strength, and fluid-geomechanical parameters characterizing the geologic formations of interest. We have investigated the ability of efficient global optimization (EGO) to reduce the parameter uncertainties usually affecting geomechanical modeling. EGO is used to identify the parameter set that minimizes the difference in land displacements obtained from synthetic aperture radar (SAR)-derived measurements and 3D geomechanical modeling. We have tested the approach on the Tengiz giant oil field, Kazakhstan, where large uncertainties affect our knowledge of geomechanical parameters and pore pressure evolution. SqueeSAR on ENVISAT and RADARSAT-1 images acquired between 2004 and 2007 provided a set of high-precision, high-areal-density subsidence measurements of the test site. Based on the available information, a 3D geomechanical model of the reservoir has been developed using the elastoplastic finite-element code GEPS3D. Our results indicated that EGO efficiently identifies the global optimum in the parameter space, yielding a significant reduction in the difference between modeled and measured land subsidence. The match between simulated and SAR-measured horizontal displacements was developed as validation of the EGO calibration, which thus proved an effective and rather inexpensive method for the simultaneous management of several uncertainties and the reliable quantification of the rock properties.

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Zhang, J. "INSAR COLLABORATIVE MONITORING MODE AND MULTI-MODE COMPUTING SERVICES FOR GEOHAZARDS IDENTIFICATION IN OPEN-PIT MINING AREA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2021 (June 28, 2021): 241–47. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2021-241-2021.

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Abstract. InSAR has developed a variety of methods, such as D-InSAR, PS-InSAR, MBAS, CT, SqueeSAR, POT, etc., which have been widely used in land subsidence monitoring. For open pit mining areas, there are usually mining activity, complex terrain features, low coherence, and local large deformation gradients, which makes it difficult for time series InSAR technology to obtain high-density surface deformation information in open pit mining areas. Traditional methods usually only monitor the linear deformation of the surface caused by the mining of a few working zone above the underground mining area, and the temporal and spatial resolution is lower. How to obtain high-precision, high-density, and time-sensitive deformation information is the main difficulty of InSAR monitoring in open pit mining areas. Make full use of the geosensor network monitoring system, optimize monitoring mode of collaborated satellite-to-ground based InSAR, further realize whole calculation and geographic information services, to achieve early identification and discovery of abnormal in large-area macro-monitoring, and accurate monitoring of local areas in real-time early warning, which is the development direction of ground deformation monitoring of mining areas. The study area is Pingshuo open pit mining area. we fully study the application mode and services of InSAR monitoring for geohazards in open-pit mining area, through the establishment of satellite InSAR technology system for large-scale macro-monitoring and forecasting, and GBSAR and GSN for local precision monitoring. The effective mode of InSAR monitoring of geohazard in open-pit mines is summarized. A combination of D-InSAR, POT (Pixel offset tracking), Time Series-InSAR and GB-SAR is used in a wide range, and high-resolution optical images are used to identify localized changes in subsidence areas and open-pit mining areas.

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24

Jones, David. "Electric squeezer." Nature 367, no. 6460 (January 1994): 222. http://dx.doi.org/10.1038/367222a0.

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25

Korsunsky, Boris. "A vacuum squeezer." Physics Teacher 40, no. 3 (March 2002): 186. http://dx.doi.org/10.1119/1.1466557.

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Helseth, L. E., T. M. Fischer, R. W. Hansen, and T. H. Johansen. "Microscopic magnetic squeezer." Applied Physics Letters 85, no. 13 (September 27, 2004): 2556–58. http://dx.doi.org/10.1063/1.1795977.

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He, Zengyou, Xiaofei Xu, and Shenchun Deng. "Improving categorical data clustering algorithm by weighting uncommon attribute value matches." Computer Science and Information Systems 3, no. 1 (2006): 23–32. http://dx.doi.org/10.2298/csis0601023h.

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This paper presents an improved Squeezer algorithm for categorical data clustering by giving greater weight to uncommon attribute value matches in similarity computations. Experimental results on real life datasets show that, the modified algorithm is superior to the original Squeezer algorithm and other clustering algorithm with respect to clustering accuracy.

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Sterling, Leon, and Yossi Nygate. "PYTHON: An expert squeezer." Journal of Logic Programming 8, no. 1-2 (January 1990): 21–39. http://dx.doi.org/10.1016/0743-1066(90)90049-b.

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29

Iivonen, A., J. Kuhalainen, R. Saintola, K. Valli, T. Inamura, M. Koizumi, K. Morita, and A. Yoshida. "The squeezer ion guide." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 70, no. 1-4 (August 1992): 213–19. http://dx.doi.org/10.1016/0168-583x(92)95934-j.

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Heurs, M., I. R. Petersen, M. R. James, and E. H. Huntington. "Homodyne locking of a squeezer." Optics Letters 34, no. 16 (August 11, 2009): 2465. http://dx.doi.org/10.1364/ol.34.002465.

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Shimizu, H., S. Yamazaki, T. Ono, and K. Emura. "Highly practical fiber squeezer polarization controller." Journal of Lightwave Technology 9, no. 10 (1991): 1217–24. http://dx.doi.org/10.1109/50.90918.

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Dewi, D. C., Novrianti, C. Handayani, O. Wulandari, and I. Nurhayati. "Design of ergonomic grated coconut squeezer." IOP Conference Series: Materials Science and Engineering 602 (September 6, 2019): 012043. http://dx.doi.org/10.1088/1757-899x/602/1/012043.

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Zhang, Jiang, and Kaiwei Liu. "Neural Information Squeezer for Causal Emergence." Entropy 25, no. 1 (December 23, 2022): 26. http://dx.doi.org/10.3390/e25010026.

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Conventional studies of causal emergence have revealed that stronger causality can be obtained on the macro-level than the micro-level of the same Markovian dynamical systems if an appropriate coarse-graining strategy has been conducted on the micro-states. However, identifying this emergent causality from data is still a difficult problem that has not been solved because the appropriate coarse-graining strategy can not be found easily. This paper proposes a general machine learning framework called Neural Information Squeezer to automatically extract the effective coarse-graining strategy and the macro-level dynamics, as well as identify causal emergence directly from time series data. By using invertible neural network, we can decompose any coarse-graining strategy into two separate procedures: information conversion and information discarding. In this way, we can not only exactly control the width of the information channel, but also can derive some important properties analytically. We also show how our framework can extract the coarse-graining functions and the dynamics on different levels, as well as identify causal emergence from the data on several exampled systems.

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Arya, Govind Prasad, Arvind Singh, Rahul Painuly, Shashank Bhadri, and Sunakshi Maurya. "LZ SQUEEZER A Compression Technique based on LZ77 and LZ78." SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 01, no. 02 (June 27, 2013): 01–04. http://dx.doi.org/10.9756/sijcsea/v1i2/01010258.

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Wirawan, Vincentius, Seng Hansun, and Hargyo Tri Nugroho I. "Implementasi Algoritma Squeezer dan Term Frequency Ranking dalam Pembangunan Sistem Rekomendasi Tempat Makan." Jurnal ULTIMA Computing 6, no. 1 (June 1, 2014): 25–32. http://dx.doi.org/10.31937/sk.v6i1.292.

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Food is something that can not be separated from the life of every human being. Its variation makes a lot of people interested in tasting many types of food, even they have not known yet. The detail information of restaurants, especially their location could be a problem. So, the restaurants recommendation website is made to help them. The recommendations are given by the Squeezer algorithm using the user’s input as references. The accuracy of the given recommendations are determined from the amount and consistency of the user at the time of selecting the item. The Term Frequency Ranking is used as a searching feature to display the search results in ordered manner by their relevancy rank. Experiment result shows that the Term Frequency Ranking gives high value of Recall, 1, and 0.46 for the Precision value. Index Terms—Recommended System, Squeezer, Term Frequency Ranking, Website.

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Doğru, Harun, Kemal Uygur, and Mustafa Tüz. "Concha Bullosa Squeezer for Turbinoplasty (Doğgru Forceps)." Journal of Otolaryngology 33, no. 02 (2004): 111. http://dx.doi.org/10.2310/7070.2004.02112.

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Eckardt, Claus. "SQUEEZER—A NEW DEVICE FOR VITREORETINAL SURGERY." Retina 37, no. 11 (November 2017): 2199–200. http://dx.doi.org/10.1097/iae.0000000000001825.

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Surata, I. Wayan, Tjokorda Gde Tirta Nindhia, D. Budyanto, and A. E. Yulianto. "Design and manufacture a coconut milk squeezer." IOP Conference Series: Materials Science and Engineering 201 (May 2017): 012015. http://dx.doi.org/10.1088/1757-899x/201/1/012015.

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Zahidi, Abdallah, Amrane Said, Nawfel Azami, and Naoual Nasser. "Effect of fiber and solenoid variation parameters on the elements of a corrector PID for electromagnetic fiber squeezer based polarization controller." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (June 1, 2020): 2441. http://dx.doi.org/10.11591/ijece.v10i3.pp2441-2451.

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Controlling the polarization of the light output from single-mode fiber systems is very important for connecting it to polarization-dependent integrated optical circuits, while applications using a heterodyne detection system. Polarization controller using fiber squeezer is attractive for a low-loss, low-penalty coherent optical fiber trunk system. However, for polarization controllers using electromagnetic fiber squeezer, the stability problem due to the saturation of their magnetic circuit must be studied. In fact, in their conventional configuration, open-loop stability affects performance and limits applications. First at all, this effect has been analyzed and a feedback circuit with correctors has been proposed to improve stability performance. Then a simulation study is proposed to examine the influence of the system parameters on the corrector constants. The results of the simulation show that if the system parameters change the constants Kp, Ki and Kd of the PID corrector must be adjusted to keep an optimized dynamic response.

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Syakhroni, Akhmad, and Sukarno Budi Utomo. "RANCANG BANGUN ALAT PEMARUT DAN PEMERAS SANTAN KELAPA DENGAN MENGGUNAKAN 1 MOTOR PENGGERAK UNTUK MENINGKATKAN EFEKTIFITAS." Infotekmesin 9, no. 02 (July 22, 2019): 76–82. http://dx.doi.org/10.35970/infotekmesin.v9i02.15.

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There are many of food processing of raw materials are still using a separate tools of coconut grater and squeezer, which causes a long production process. Basically the grater machines on the market only can be used to scrape away the coconut meat. While the tool for extracting the coconut milk is still using coconut sieve and squeezed by hand. The Research initiated with a survey into traditional markets and entrepreneurs of coconut grater services around Semarang. The survey aimed to identify the tools used in the market and the needs of potential users. The survey obtained data of customer’s need that will be used as a reference for developing the concept of making tools. Anthropometric data needed to design the dimensions of the tool, with the purpose of the tool made will be ergonomics and comfortable to be used by the operator. Grater and Squeezer of Coconut Milk Tool which designed has dimensions of 105 cm height and 74 cm width. It has parts: the framework, grater, bleeder screw, motor, gear box, water container, and a pulley / wheel.

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He, Zengyou, Xiaofei Xu, and Shengchun Deng. "Squeezer: An efficient algorithm for clustering categorical data." Journal of Computer Science and Technology 17, no. 5 (September 2002): 611–24. http://dx.doi.org/10.1007/bf02948829.

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42

Sayed Hassen, S. Z. "Modelling, analysis and simulation of an optical squeezer." Applied Mathematical Modelling 39, no. 13 (July 2015): 3846–61. http://dx.doi.org/10.1016/j.apm.2014.11.066.

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43

Kowalska, Małgorzata, Justyna Konopska, Melánia Feszterová, Anna Zbikowska, and Barbara Kowalska. "Quality Assessment of Natural Juices and Consumer Preferences in the Range of Citrus Fruit Juices." Applied Sciences 13, no. 2 (January 5, 2023): 765. http://dx.doi.org/10.3390/app13020765.

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The purpose of the study was to analyse and update consumers’ changing preferences in the choice of citrus fruit juices and to evaluate the sensory and physicochemical characteristics of two kinds of juices: juice squeezed from raw fruit and a commercial juice indicated by respondents as best matching their preferences. The survey was conducted in the form of an online survey posted on app.ankieteo.pl. The survey was also sent via a link through social networks. A total of 862 people took part in the survey. Consumers are most likely to consume juices one to three times a week (28.3%). Orange juice was the most popular among respondents (52.4%). The main factors influencing decisions to purchase citrus fruit juices are the type of fruit from which the juice was made, the vitamin content and the product’s price. In choosing juices, respondents were also guided by favourable health qualities and the presence of minerals. From the physicochemical determinations of orange juices obtained from a juicer and squeezer and commercial juice “O”, it was found that the quality of commercial orange juice indicated by consumers in the survey is comparable to juices made with a squeezer or a juice.

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44

Bender, Michael, William Martin, Jennifer Hess, Fred Sayles, Lary Ball, and Claude Lambert. "A whole-core squeezer for interfacial pore-water sampling1." Limnology and Oceanography 32, no. 6 (November 1987): 1214–25. http://dx.doi.org/10.4319/lo.1987.32.6.1214.

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INAKUMA, Takahiro, Hirohisa TATSUZAWA, and Yukio ISHIGURO. "Manufacturing Process of Carrot Juice using a Fresh Squeezer." NIPPON SHOKUHIN KAGAKU KOGAKU KAISHI 43, no. 1 (1996): 85–90. http://dx.doi.org/10.3136/nskkk.43.85.

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46

Iqbal, Zaqlul, and Drupadi Ciptaningtyas. "Designing and Experimenting Semi-automatic Green Grass Jelly Squeezer." International Journal on Advanced Science, Engineering and Information Technology 8, no. 4 (July 29, 2018): 1105. http://dx.doi.org/10.18517/ijaseit.8.4.4744.

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47

Alexander, Tal, and Mark Morris. "Squeezars: Tidally Powered Stars Orbiting a Massive Black Hole." Astrophysical Journal 590, no. 1 (May 15, 2003): L25—L28. http://dx.doi.org/10.1086/376671.

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48

Hadi, R. M. E., E. Chumaidiah, and S. Wulandari. "Study of squeezer machine performance of cooked soy porridge." IOP Conference Series: Materials Science and Engineering 469 (January 16, 2019): 012029. http://dx.doi.org/10.1088/1757-899x/469/1/012029.

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49

Ramdani, Rifki, and Kadarismansyah. "PERANCANGAN MESIN PEMERAS SANTAN DENGAN SISTEM SPINNER." Jurnal Permadi: Perancangan, Manufaktur, Material dan Energi 3, no. 2 (May 31, 2021): 101–13. http://dx.doi.org/10.52005/permadi.v3i2.52.

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Coconut plants are very abundant natural resources and useful for humans. One of the benefits of coconut plants is: coconut flesh which is the raw material for coconut milk which is generally used as food preparations. In general, the process of squeezing coconut milk is still using a manual extortion process, so it requires energy and time which is quite long. To overcome this, it is necessary to design a machine efficient coconut milk squeezer, this machine is designed using materials that economical so that it can be reached by all people, especially those who have a culinary business. This coconut milk squeezer works on the principle of the system rotate, the grated coconut meat is placed in a tube in the machine, at that time the coconut meat will be rotated at high speed so that The liquid coconut milk contained in the coconut meat is separated from the coconut meat. Motorcycle the driving force used is an electric motor, the power on the electric motor will transmitted from the rotation of the pully motor through the v-belt to the pully and the shaft which moved. The extortion process is carried out by pressing the on button so that the tube will rotate automatically. Coconut meat in the tube will not be damaged because there is no pressing process when the engine is rotating.

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MÃ¸llgaard, H. Peter. "A Squeezer Round the Corner? Self-Regulation and Forward Markets." Economic Journal 107, no. 440 (January 1, 1997): 104–12. http://dx.doi.org/10.1111/1468-0297.00144.

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