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Journal articles on the topic 'SAR matrices'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Grillenzoni, Carlo. "Forecasting Lattice and Point Spatial Data: Comparison of Unilateral and Multilateral SAR Models." Forecasting 6, no. 3 (2024): 700–717. http://dx.doi.org/10.3390/forecast6030036.

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Spatial auto-regressive (SAR) models are widely used in geosciences for data analysis; their main feature is the presence of weight (W) matrices, which define the neighboring relationships between the spatial units. The statistical properties of parameter and forecast estimates strongly depend on the structure of such matrices. The least squares (LS) method is the most flexible and can estimate systems of large dimensions; however, it is biased in the presence of multilateral (sparse) matrices. Instead, the unilateral specification of SAR models provides triangular weight matrices that allow c

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Rzepecki, R., E. Markiewicz, R. Adamiec, and J. Szopa. "Interaction of the Pisum sativum nuclear matrix proteins with SAR DNA." Acta Biochimica Polonica 42, no. 1 (1995): 75–81. http://dx.doi.org/10.18388/abp.1995_4671.

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We have isolated the nuclear matrices from Pisum sativum cell nuclei using three methods: i. standard procedure involving extraction of cell nuclei with 2 M NaCl and 1% Triton X-100; ii. the same with pretreatment of cell nuclei with 0.5 mM CuSO4 (stabilisation step); and iii. method including lithium diiodosalicylate extraction. We compared the polypeptide pattern and residual DNA content of the nuclear matrices isolated. The nuclear matrices displayed a specific endonuclease activity which was due to the presence of a 32 kDa protein. The isolated nuclear matrices bound specifically the scaff

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Jo, Hwi-Jeong, Heewoo Lee, Jihoon Choi, and Wookyung Lee. "Hybrid Deterministic Sensing Matrix for Compressed Drone SAR Imaging and Efficient Reconstruction of Subsurface Targets." Remote Sensing 17, no. 4 (2025): 595. https://doi.org/10.3390/rs17040595.

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Drone-based synthetic aperture radar (SAR) systems have increasingly gained attention due to their potential for rapid surveillance in localized areas. This paper presents a novel approach to SAR processing for subsurface target detection from a lightweight drone platform. The limited processing capacity and memory resources of small SAR platforms demand efficient recovery performance for high-resolution imaging. Compressed sensing (CS) algorithms are widely used to mitigate data storage requirements, yet they often suffer from challenges related to computational burden and detection errors. C

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Peng, Dong, Ting Pan, Wen Yang, and Heng-Chao Li. "K-Matrix: A Novel Change-Pattern Mining Method for SAR Image Time Series." Remote Sensing 11, no. 18 (2019): 2161. http://dx.doi.org/10.3390/rs11182161.

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In this paper, we present a novel method for change-pattern mining in Synthetic Aperture Radar (SAR) image time series based on a distance matrix clustering algorithm, called K-Matrix. As it is different from the state-of-the-art methods, which analyze the SAR image time series based on the change detection matrix (CDM), here, we directly use the distance matrix to determine changed pixels and extract change patterns. The proposed scheme involves two steps: change detection in SAR image time series and change-pattern discovery. First, these distance matrices are constructed for each spatial po

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Rzepecki, R., E. Markiewicz, and J. Szopa. "Identification of the proteins responsible for SAR DNA binding in nuclear matrix of Cucurbita pepo." Acta Biochimica Polonica 42, no. 2 (1995): 171–76. http://dx.doi.org/10.18388/abp.1995_4641.

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The nuclear matrices from White bush (Cucurbita pepo var. patisonina) cell nuclei have been isolated using three methods: I, standard procedure involving extraction of cell nuclei with 2 M NaCl and 1% Triton X-100; II, the same with pre-treatment of cell nuclei with 0.5 mM CuSO4 (stabilisation step); and III, method with extraction by lithium diiodosalicylate (LIS), and compared the polypeptide pattern. The isolated matrices specifically bind SAR DNA derived from human beta-interferon gene in the exogenous SAR binding assay and in the gel mobility shift assay. Using IgG against the 32 kDa endo

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Choi, Jihoon, and Wookyung Lee. "Drone SAR Image Compression Based on Block Adaptive Compressive Sensing." Remote Sensing 13, no. 19 (2021): 3947. http://dx.doi.org/10.3390/rs13193947.

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In this paper, an adaptive block compressive sensing (BCS) method is proposed for compression of synthetic aperture radar (SAR) images. The proposed method enhances the compression efficiency by dividing the magnitude of the entire SAR image into multiple blocks and subsampling individual blocks with different compression ratios depending on the sparsity of coefficients in the discrete wavelet transform domain. Especially, a new algorithm is devised that selects the best block measurement matrix from a predetermined codebook to reduce the side information about measurement matrices transferred

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Abonazel, Mohamed R. "Determinants of Per Capita Personal Income in the US: Spatial Fixed Effects Panel Data Modeling." Journal of Advanced Research in Applied Mathematics and Statistics 05, no. 1&2 (2020): 1–13. http://dx.doi.org/10.24321/2455.7021.202001.

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Over the last decades, the Per Capita Personal Income (PCPI) variable was a common measure of the effectiveness of economic development policy. Therefore, this paper is an attempt to investigate the determinants of personal income by using spatial panel data models for 48 U.S. states during the period from 2009 to 2017. We utilize the three following models: spatial autoregressive (SAR) model, Spatial Error (SEM) Model, and Spatial Autoregressive Combined (SAC) model, with individual (or spatial) fixe deffects according to three different known methods for constructing spatial weights matrices

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Porzycka-Strzelczyk, Stanisława, Jacek Strzelczyk, Kamil Szostek, et al. "Information Extraction from Satellite-Based Polarimetric SAR Data Using Simulated Annealing and SIRT Methods and GPU Processing." Energies 15, no. 1 (2021): 72. http://dx.doi.org/10.3390/en15010072.

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The main goal of this research was to propose a new method of polarimetric SAR data decomposition that will extract additional polarimetric information from the Synthetic Aperture Radar (SAR) images compared to other existing decomposition methods. Most of the current decomposition methods are based on scattering, covariance or coherence matrices describing the radar wave-scattering phenomenon represented in a single pixel of an SAR image. A lot of different decomposition methods have been proposed up to now, but the problem is still open since it has no unique solution. In this research, a ne

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Ao, Dongyang, Corneliu Octavian Dumitru, Gottfried Schwarz, and Mihai Datcu. "Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X." Remote Sensing 10, no. 10 (2018): 1597. http://dx.doi.org/10.3390/rs10101597.

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With more and more SAR applications, the demand for enhanced high-quality SAR images has increased considerably. However, high-quality SAR images entail high costs, due to the limitations of current SAR devices and their image processing resources. To improve the quality of SAR images and to reduce the costs of their generation, we propose a Dialectical Generative Adversarial Network (Dialectical GAN) to generate high-quality SAR images. This method is based on the analysis of hierarchical SAR information and the “dialectical” structure of GAN frameworks. As a demonstration, a typical example

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Klymchuk, Tetiana. "Regularizing algorithm for mixed matrix pencils." Applied Mathematics and Nonlinear Sciences 2, no. 1 (2017): 123–30. http://dx.doi.org/10.21042/amns.2017.1.00010.

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AbstractP. Van Dooren (1979) constructed an algorithm for computing all singular summands of Kronecker’s canonical form of a matrix pencil. His algorithm uses only unitary transformations, which improves its numerical stability. We extend Van Dooren’s algorithm to square complex matrices with respect to consimilarity transformations $\begin{array}{} \displaystyle A \mapsto SA{\bar S^{ - 1}} \end{array}$ and to pairs of m × n complex matrices with respect to transformations $\begin{array}{} \displaystyle (A,B) \mapsto (SAR,SB\bar R) \end{array}$, in which S and R are nonsingular matrices.

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Wassermann, Anne Mai, Peter Haebel, Nils Weskamp, and Jürgen Bajorath. "SAR Matrices: Automated Extraction of Information-Rich SAR Tables from Large Compound Data Sets." Journal of Chemical Information and Modeling 52, no. 7 (2012): 1769–76. http://dx.doi.org/10.1021/ci300206e.

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Shen, Peng, Changcheng Wang, Haiqiang Fu, Jianjun Zhu, and Jun Hu. "Estimation of Equivalent Number of Looks in Time-Series Pol(In)SAR Data." Remote Sensing 12, no. 17 (2020): 2715. http://dx.doi.org/10.3390/rs12172715.

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As an essential parameter in synthetic aperture radar (SAR) images, the equivalent number of looks (ENL) not only indicates the speckle noise level in multi-look SAR data but also can be used for evaluating the region homogeneity level. Currently, time-series polarimetric (interferometric) SAR (TSPol(In)SAR) data are increasingly abundant, but traditional equivalent number of looks (ENL) estimators only use polarimetric information from a mono-temporal observation and do not consider the temporal characteristics or interferometric coherence of ground targets. Therefore, this paper puts forward

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Wang, Wenguang, Xin Ren, Yan Zhang, and Meng Li. "Deep Learning Based Lithology Classification Using Dual-Frequency Pol-SAR Data." Applied Sciences 8, no. 9 (2018): 1513. http://dx.doi.org/10.3390/app8091513.

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Lithology classification is a crucial step in the prospecting process, and polarimetric synthetic aperture radar (Pol-SAR) imagery has been extensively used for it. However, despite significant improvements in both information content of Pol-SAR imagery and advanced classification approaches, lithology classification using Pol-SAR data may not provide satisfactory classification accuracy due to high similarity of certain classes. In this paper, a novel Pol-SAR lithology classification method based on a stacked sparse autoencoder (SSAE) is proposed. By using superpixel segmentation, new feature

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Arii, Motofumi, Jakob J. van Zyl, and Yunjin Kim. "Adaptive Model-Based Decomposition of Polarimetric SAR Covariance Matrices." IEEE Transactions on Geoscience and Remote Sensing 49, no. 3 (2011): 1104–13. http://dx.doi.org/10.1109/tgrs.2010.2076285.

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Ben Abdallah, Nadia, Halim Dabbou, Mohamed Imen Gallali, and Salem Hathroubi. "Stock Returns’ Co-Movement: A Spatial Model with Convex Combination of Connectivity Matrices." Risks 13, no. 6 (2025): 110. https://doi.org/10.3390/risks13060110.

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This paper examines the extent of stock-returns’ co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that merges four weight matrices—geographical distance, bilateral trade, sector similarity, and company size—into one global matrix. Our results reveal strong spatial stock-market dependence, show that spatial proximity is better captured by financial-distance measures than by pure geographical distance, and indicate that the weight matrix based on sector si

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Salsabil, Tsuroyya, Dianne Amor Kusuma, and Budi Nurani Ruchjana. "Penerapan Perangkat Lunak RStudio untuk Penaksiran Parameter Model Spatial Autoregressive." KUBIK: Jurnal Publikasi Ilmiah Matematika 8, no. 1 (2023): 50–64. http://dx.doi.org/10.15575/kubik.v8i1.30037.

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Research and analysis that are not only based on time (temporal) but also on space (spatial) require tools in the form of software to ensure that the data analysis and processing yield good, fast, and accurate results. One of the software tools that can be used for this purpose is RStudio software. The advantages of RStudio include being open-source software (OSS), which can be used freely without cost, and it has many packages and functions that can facilitate data processing. One of the spatial-based analyses is spatial data analysis. The structure within RStudio allows users to call functio

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Deng, Junwu, Peng Zhou, Mingdian Li, Haoliang Li, and Siwei Chen. "Quad-Pol SAR Data Reconstruction from Dual-Pol SAR Mode Based on a Multiscale Feature Aggregation Network." Remote Sensing 15, no. 17 (2023): 4182. http://dx.doi.org/10.3390/rs15174182.

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Polarimetric synthetic aperture radar (PolSAR) is widely used in remote sensing applications due to its ability to obtain full-polarization information. Compared to the quad-pol SAR, the dual-pol SAR mode has a wider observation swath and is more common in most SAR systems. The goal of reconstructing quad-pol SAR data from the dual-pol SAR mode is to learn the contextual information of dual-pol SAR images and the relationships among polarimetric channels. This work is dedicated to addressing this issue, and a multiscale feature aggregation network has been established to achieve the reconstruc

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Gupta-Ostermann, Disha, Veerabahu Shanmugasundaram, and Jürgen Bajorath. "Neighborhood-Based Prediction of Novel Active Compounds from SAR Matrices." Journal of Chemical Information and Modeling 54, no. 3 (2014): 801–9. http://dx.doi.org/10.1021/ci5000483.

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Wang, Gongtang, Fuyu Bo, Xue Chen, Wenfeng Lu, Shaohai Hu, and Jing Fang. "A Collaborative Despeckling Method for SAR Images Based on Texture Classification." Remote Sensing 14, no. 6 (2022): 1465. http://dx.doi.org/10.3390/rs14061465.

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Speckle is an unavoidable noise-like phenomenon in Synthetic Aperture Radar (SAR) imaging. In order to remove speckle, many despeckling methods have been proposed during the past three decades, including spatial-based methods, transform domain-based methods, and non-local filtering methods. However, SAR images usually contain many different types of regions, including homogeneous and heterogeneous regions. Some filters could despeckle effectively in homogeneous regions but could not preserve structures in heterogeneous regions. Some filters preserve structures well but do not suppress speckle

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Gupta-Ostermann, Disha, Yoichiro Hirose, Takenao Odagami, Hiroyuki Kouji, and Jürgen Bajorath. "Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity." F1000Research 4 (March 23, 2015): 75. http://dx.doi.org/10.12688/f1000research.6271.1.

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In a previous Method Article, we have presented the ‘Structure-Activity Relationship (SAR) Matrix’ (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SAR information in matrices reminiscent of R-group tables. SARM calculations also yield many virtual candidate compounds that form a “chemical space envelope” around related series. To further extend the SARM approach, different methods are developed to predict the activity of virtual compounds. In th

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Gupta-Ostermann, Disha, Yoichiro Hirose, Takenao Odagami, Hiroyuki Kouji, and Jürgen Bajorath. "Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity." F1000Research 4 (April 15, 2015): 75. http://dx.doi.org/10.12688/f1000research.6271.2.

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In a previous Method Article, we have presented the ‘Structure-Activity Relationship (SAR) Matrix’ (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SAR information in matrices reminiscent of R-group tables. SARM calculations also yield many virtual candidate compounds that form a “chemical space envelope” around related series. To further extend the SARM approach, different methods are developed to predict the activity of virtual compounds. In th

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Atto, Abdourrahmane Mahamane, Emmanuel Trouve, Yannick Berthoumieu, and Grégoire Mercier. "Multidate Divergence Matrices for the Analysis of SAR Image Time Series." IEEE Transactions on Geoscience and Remote Sensing 51, no. 4 (2013): 1922–38. http://dx.doi.org/10.1109/tgrs.2012.2210228.

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DERUN, Ivan, and Hanna Mysaka. "DRIVERS OF EXPANSION OF SOCIAL ACCOUNTINGAND REPORTING: INDICATION OF BIBLIOMETRIC TRENDS." Bulletin of Taras Shevchenko National University of Kyiv. Economics, no. 224 (2024): 75–86. http://dx.doi.org/10.17721/1728-2667.2024/224-1/9.

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Background. Due to the demand of stakeholders for information about social and environmental aspects of business, the system of social accounting and reporting (SAR) has become important in promoting the ideology of sustainable development at the micro-level. Conducting SAR research provides socio-ecological reporting practices with a theoretical basis for further development and improvement. The bibliometric evaluation of SAR publications enables the identification of promising trends in the research domain evolution, which will accelerate its effective development. The article aims to substa

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Rezaeian, A., S. Homayouni, and A. Safari. "SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 613–17. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-613-2015.

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Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper

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Tang, Tao, and Gangyao Kuang. "SAR Image Reconstruction of Vehicle Targets Based on Tensor Decomposition." Electronics 11, no. 18 (2022): 2859. http://dx.doi.org/10.3390/electronics11182859.

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Due to the imaging mechanism of Synthetic Aperture Radars (SARs), the target shape on an SAR image is sensitive to the radar incidence angle and target azimuth, but there is strong correlation and redundancy between adjacent azimuth images of SAR targets. This paper studies multi-angle SAR image reconstruction based on non-negative Tucker decomposition using adjacent azimuth images reconstructed to form a sparse tensor. Sparse tensors are used to perform non-negative Tucker decomposition, resulting in non-negative core tensors and factor matrices. The reconstruction tensor is obtained by calcu

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Tan, Xintong, Qi Yu, Zelong Wang, and Jubo Zhu. "Towards Better Understanding of SAR Image: Feature Enhancement via Non-Local and Low-Rank Approach." Journal of Physics: Conference Series 2025, no. 1 (2021): 012071. http://dx.doi.org/10.1088/1742-6596/2025/1/012071.

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Abstract Feature enhancement for synthetic aperture radar (SAR) images is of great significance for their understanding and interpretation. In this work, we aim to address the issues by introducing the low-rank constraint into non-local means framework, dubbed NL_LR. The non-local means framework takes advantages of the non-local self-similarity of SAR images, which makes this approach efficient in noise suppression and preservation of structures and resolution. When estimating the value of the target pixel, a low-rank matrix can be constructed with vectorization of similar image patches. By e

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Shkvarko, Yuriy, Hector Perez-Meana, and Alejandro Castillo-Atoche. "Enhanced Radar Imaging in Uncertain Environment: A Descriptive Experiment Design Regularization Approach." International Journal of Navigation and Observation 2008 (August 13, 2008): 1–11. http://dx.doi.org/10.1155/2008/810816.

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A new robust technique for high-resolution reconstructive imaging is developed as required for enhanced remote sensing (RS) with imaging array radar or/and synthetic aperture radar (SAR) operating in an uncertain RS environment. The operational scenario uncertainties are associated with the unknown statistics of perturbations of the signal formation operator (SFO) in turbulent medium, imperfect array calibration, finite dimensionality of measurements, uncontrolled antenna vibrations, and random carrier trajectory deviations in the case of SAR. We propose new descriptive experiment design regul

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Lv, Hushan, Yongrui Li, Yizhuang Xie, and Tingting Qiao. "An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System." Remote Sensing 15, no. 11 (2023): 2885. http://dx.doi.org/10.3390/rs15112885.

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Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping

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D’Hondt, Olivier, Ronny Hänsch, Nicolas Wagener, and Olaf Hellwich. "Exploiting SAR Tomography for Supervised Land-Cover Classification." Remote Sensing 10, no. 11 (2018): 1742. http://dx.doi.org/10.3390/rs10111742.

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In this paper, we provide the first in-depth evaluation of exploiting Tomographic Synthetic Aperture Radar (TomoSAR) for the task of supervised land-cover classification. Our main contribution is the design of specific TomoSAR features to reach this objective. In particular, we show that classification based on TomoSAR significantly outperforms PolSAR data provided relevant features are extracted from the tomograms. We also provide a comparison of classification results obtained from covariance matrices versus tomogram features as well as obtained by different reference methods, i.e., the trad

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van Zyl, Jakob J., Motofumi Arii, and Yunjin Kim. "Model-Based Decomposition of Polarimetric SAR Covariance Matrices Constrained for Nonnegative Eigenvalues." IEEE Transactions on Geoscience and Remote Sensing 49, no. 9 (2011): 3452–59. http://dx.doi.org/10.1109/tgrs.2011.2128325.

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Ben Abdallah, R., A. Mian, A. Breloy, A. Taylor, M. N. El Korso, and D. Lautru. "Detection Methods Based on Structured Covariance Matrices for Multivariate SAR Images Processing." IEEE Geoscience and Remote Sensing Letters 16, no. 7 (2019): 1160–64. http://dx.doi.org/10.1109/lgrs.2018.2890155.

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Yang, Huizhang, Chengzhi Chen, Shengyao Chen, and Feng Xi. "Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements." Remote Sensing 11, no. 4 (2019): 472. http://dx.doi.org/10.3390/rs11040472.

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This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system

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Esmaeilzade, M., F. Jahani, and J. Amini. "USING COVARIANCE MATRIX FOR CHANGE DETECTION OF POLARIMETRIC SAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W4 (September 26, 2017): 69–76. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w4-69-2017.

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Nowadays change detection is an important role in civil and military fields. The Synthetic Aperture Radar (SAR) images due to its independent of atmospheric conditions and cloud cover, have attracted much attention in the change detection applications. When the SAR data are used, one of the appropriate ways to display the backscattered signal is using covariance matrix that follows the Wishart distribution. Based on this distribution a statistical test for equality of two complex variance-covariance matrices can be used. In this study, two full polarization data in band L from UAVSAR are used

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Mustak, S., G. Uday, B. Ramesh, and B. Praveen. "EVALUATION OF THE PERFORMANCE OF SAR AND SAR-OPTICAL FUSED DATASET FOR CROP DISCRIMINATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W6 (July 26, 2019): 563–71. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w6-563-2019.

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<p><strong>Abstract.</strong> Crop discrimination and acreage play a vital role in interpreting the cropping pattern, statistics of the produce and market value of each product. Sultan Battery is an area where a large amount of irrigated and rainfed paddy crops are grown along with Rubber, Arecanut and Coconut. In addition, the northern region of Sultan Battery is covered with evergreen and deciduous forest. In this study, the main objective is to evaluate the performance of optical and Synthetic Aperture Radar (SAR)-optical hybrid fusion imageries for crop discrimination in

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AKOLO, INGKA RIZKYANI. "PERBANDINGAN MATRIKS PEMBOBOT ROOK DAN QUEEN CONTIGUITY DALAM ANALISIS SPATIAL AUTOREGRESSIVE MODEL (SAR) DAN SPATIAL ERROR MODEL (SEM)." Jambura Journal of Probability and Statistics 3, no. 1 (2022): 11–18. http://dx.doi.org/10.34312/jjps.v3i1.13582.

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The spatial weighting matrix is very important to overview of the relationship between one location to another in the spatial regression. In this study, the authors compare the weighting matrix of queen contiguity and rook contiguity in the SAR and SEM models in stunting cases in Bone Bolango Regency, Gorontalo Province. The variables used are the number of IDL, the percentage of LBW, the amount of proper sanitation, the percentage of exclusively breastfed babies, and the number of poor people. The purpose of this study was to determine the factors that influence stunting in Bone Bolango Regen

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Li, Liang, Yongtao Zhu, Jun Hong, Feng Ming, and Yu Wang. "Design and Implementation of a Novel Polarimetric Active Radar Calibrator for Gaofen-3 SAR." Sensors 18, no. 8 (2018): 2620. http://dx.doi.org/10.3390/s18082620.

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The Chinese first fully polarimetric space-borne synthetic aperture radar (SAR)-Gaofen-3 (GF-3) was launched in August 2016, which operates at the C-band and the resolution can reach 1 m. Polarimetric SAR calibration is a procedure that corrects the polarization distortion of a measured scattering matrix by referring to the scattering matrix of a known target. The present paper describes the principle, design, manufacture, and measurement results of a novel polarimetric active radar calibrator (PARC) designed for GF-3. A new design method for PARC was presented and two dual-polarized antennas

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Soh, L. K., and C. Tsatsoulis. "Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices." IEEE Transactions on Geoscience and Remote Sensing 37, no. 2 (1999): 780–95. http://dx.doi.org/10.1109/36.752194.

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Guaragnella, Cataldo, and Tiziana D’Orazio. "A Data-Driven Approach to SAR Data-Focusing." Sensors 19, no. 7 (2019): 1649. http://dx.doi.org/10.3390/s19071649.

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Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission par

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Houssein, Essam H., Gaber M. Mohamed, Nagwan Abdel Samee, Reem Alkanhel, Ibrahim A. Ibrahim, and Yaser M. Wazery. "An Improved Search and Rescue Algorithm for Global Optimization and Blood Cell Image Segmentation." Diagnostics 13, no. 8 (2023): 1422. http://dx.doi.org/10.3390/diagnostics13081422.

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Image segmentation has been one of the most active research areas in the last decade. The traditional multi-level thresholding techniques are effective for bi-level thresholding because of their resilience, simplicity, accuracy, and low convergence time, but these traditional techniques are not effective in determining the optimal multi-level thresholding for image segmentation. Therefore, an efficient version of the search and rescue optimization algorithm (SAR) based on opposition-based learning (OBL) is proposed in this paper to segment blood-cell images and solve problems of multi-level th

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Varia, N., N. Davawala, S. Chirakkal, D. Haldar, R. Ghosh, and D. Putrevu. "CHANGE DETECTION OF POLARIMETRIC SAR DATA FOR MONITORING OF AGRICULTURAL AREAS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (November 15, 2018): 229–32. http://dx.doi.org/10.5194/isprs-annals-iv-5-229-2018.

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<p><strong>Abstract.</strong> Change detection is important to understand the patterns of transition in multi-temporal SAR acquisitions over same geographical areas. In this work, we implemented a test statistic on covariance matrices for change detection. The RADARSAT-2 data spanning the agricultural land of Central Hisar Farm in Haryana, India was used. Hypothesis testing on test-statistic was done by a pre-decided significance level. A change map was plotted and the areas with ‘change’ and ‘no change’ were determined. Analysis of changing trends of different crop lifecycle

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Aghababaei, H., G. Ferraioli, and V. Pascazio. "RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (November 6, 2020): 483–86. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-483-2020.

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Abstract. Dealing with multi-look polarimetric synthetic aperture radar (PolSAR) images requires averaging several independent looks to generate a sample covariance matrix of similar target scattering vectors. Along this, estimation of optimal similarity between target scattering vectors is still an open issue. In the literature, this intrinsic task has been mainly addressed in the information-based, geometric-based and detection-based frameworks. However, the derived measures mainly rely on the model assumption such as fully developed speckle and circular complex Gaussian distribution of the

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Islam, Md Touhidul, Nilima Das, Nusrat Jahan, Md Sifat Siddik, Khalid Mahmud, and A. K. M. Adham. "Utilizing geographic information system and indexing to evaluate irrigation suitability of groundwater in Kalihati Upazila, Bangladesh." Archives of Agriculture and Environmental Science 8, no. 3 (2023): 385–96. http://dx.doi.org/10.26832/24566632.2023.0803017.

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The aim of this research was to evaluate groundwater quality for irrigation in Kalihati Upazila, Bangladesh, a region that is significantly reliant on groundwater for crop development, especially during dry periods. By combining hydrochemical analysis and Geographic Information System (GIS), the research examined the physicochemical attributes and their spatial distribution. Fifteen groundwater samples from various locations were analyzed to measure parameters such as sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium adsorption ratio (MA

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Xin, Jihao, Xingdong Liang, Zhiyu Jiang, et al. "Robust Synchronization Error Estimation Under Multipath Fading in Distributed SAR." Electronics 14, no. 5 (2025): 983. https://doi.org/10.3390/electronics14050983.

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Unmanned Aerial Vehicle (UAV)-based distributed Synthetic Aperture Radar (SAR) is a current research focus. Phase synchronization is crucial for eliminating the non-coherence of distributed systems. However, as the number of UAVs increases, fast time-varying multipath effects caused by rotors can lead to multipath fading. This degrades the signal-to-noise ratio (SNR) of the synchronization link and distorts the synchronization waveform. It further breaks the reciprocity of the dual one-way synchronization link, ultimately degrading phase synchronization accuracy. We propose a robust method for

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Yoshimori, Atsushi, Huabin Hu, and Jürgen Bajorath. "Adapting the DeepSARM approach for dual-target ligand design." Journal of Computer-Aided Molecular Design 35, no. 5 (2021): 587–600. http://dx.doi.org/10.1007/s10822-021-00379-5.

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AbstractThe structure–activity relationship (SAR) matrix (SARM) methodology and data structure was originally developed to extract structurally related compound series from data sets of any composition, organize these series in matrices reminiscent of R-group tables, and visualize SAR patterns. The SARM approach combines the identification of structural relationships between series of active compounds with analog design, which is facilitated by systematically exploring combinations of core structures and substituents that have not been synthesized. The SARM methodology was extended through the

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Xie, Zhaozhe, Yongqiang Cheng, and Hao Wu. "Ship Detection in SAR Images via Kullback-Leibler Divergence-Based Matrix Information Geometry Detector." Journal of Physics: Conference Series 2525, no. 1 (2023): 012012. http://dx.doi.org/10.1088/1742-6596/2525/1/012012.

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Abstract Ship detection in synthetic aperture radar (SAR) imagery is an important application in the field of marine remote sensing. As the most common method in ship detection, classical constant false alarm rate (CFAR) methods rely on the target-to-clutter contrast and accurate estimates of distribution models, making it difficult to adapt to complex and variable sea surface backgrounds. Considering the limitations of the CFAR methods, this paper proposes a new detector for ship detection based on matrix information geometry (MIG) theory. The proposed detector models each SAR sample data as

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Sobari, Muhamad, Armalia Desiyanti, Devi Yanti, Putri Monika, Atje Setiawan Abdullah, and Budi Nurani Ruchjana. "Comparison of Spatial Weight Matrices in Spatial Autoregressive Model: Case Study of Intangible Cultural Heritage in Indonesia." JTAM (Jurnal Teori dan Aplikasi Matematika) 7, no. 1 (2023): 244. http://dx.doi.org/10.31764/jtam.v7i1.10757.

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Intangible Cultural Heritage (ICH) can effectively contribute to Sustainable Development Goals (SDGs) in all economic, social, and environmental dimensions, along with peace and security. Studying ICH in Indonesia cannot be separated from the spatial aspect of how an area's attributes are related to other areas located close to each other. Spatial regression modeling needs to be done by considering the selection of spatial weight matrix. Using the wrong spatial weight matrix will increase the standard error in parameter estimation. Therefore, this study aims to determine: the best spatial weig

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Martín-del-Campo-Becerra, Gustavo Daniel, Andreas Reigber, Matteo Nannini, and Scott Hensley. "Single-Look SAR Tomography of Urban Areas." Remote Sensing 12, no. 16 (2020): 2555. http://dx.doi.org/10.3390/rs12162555.

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Synthetic aperture radar (SAR) tomography (TomoSAR) is a multibaseline interferometric technique that estimates the power spectrum pattern (PSP) along the perpendicular to the line-of-sight (PLOS) direction. TomoSAR achieves the separation of individual scatterers in layover areas, allowing for the 3D representation of urban zones. These scenes are typically characterized by buildings of different heights, with layover between the facades of the higher structures, the rooftop of the smaller edifices and the ground surface. Multilooking, as required by most spectral estimation techniques, reduc

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Koukiou, Georgia. "SAR Features and Techniques for Urban Planning—A Review." Remote Sensing 16, no. 11 (2024): 1923. http://dx.doi.org/10.3390/rs16111923.

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Urban planning has, in recent years, been significantly assisted by remote sensing data. The data and techniques that are used are very diverse and are available to government agencies as well as to private companies that are involved in planning urban and peri-urban areas. Synthetic aperture radar data are particularly important since they provide information on the geometric and electrical characteristics of ground objects and, at the same time, are unaffected by sunlight (day–night) and cloud cover. SAR data are usually combined with optical data (fusion) in order to increase the reliabilit

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Lu, Yi, Changbao Yang, and Zhiguo Meng. "Lithology Discrimination Using Sentinel-1 Dual-Pol Data and SRTM Data." Remote Sensing 13, no. 7 (2021): 1280. http://dx.doi.org/10.3390/rs13071280.

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Compared to various optical remote sensing data, studies on the performance of dual-pol Synthetic aperture radar (SAR) on lithology discrimination are scarce. This study aimed at using Sentinel-1 data to distinguish dolomite, andesite, limestone, sandstone, and granite rock types. The backscatter coefficients VV and VH, the ratio VV–VH; the decomposition parameters Entropy, Anisotropy, and Alpha were firstly derived and the Kruskal–Wallis rank sum test was then applied to these polarimetric derived matrices to assess the significance of statistical differences among different rocks. Further, t

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Patrakeeva, O. Yu. "EVALUATING THE IMPACT OF INFRASTRUCTURE ON SPATIAL SOCIO-ECONOMIC DEVELOPMENT IN THE REGION." Ecology. Economy. Informatics.System analysis and mathematical modeling of ecological and economic systems 1, no. 6 (2021): 285–90. http://dx.doi.org/10.23885/2500-395x-2021-1-6-291-285-290.

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The paper raises the question: is there a connection between infrastructure security, population density, the level of economic activity expressed in terms of the volume of output, production and services in the context of municipalities of the Rostov region. The models of the spatial lag SAR and the spatial error SEM were tested. For both regressants – population density and volume of output – SAR turned out to be the best model for all types of distance matrices under consideration. The results showed that currently there is an imbalance in the development of Rostov’s municipalities. The Ros

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