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Journal articles on the topic 'Spatial Data Focusing'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Lee, Gi-bbeum, and Ji-Hyun Lee. "A Data-Driven Study on Spatial Network of Learning Facilities in Urban Areas : Focusing on Centrality and Educational Disparity." Korea Institute of Design Research Society 10, no. 1 (2025): 9–18. https://doi.org/10.46248/kidrs.2025.1.9.

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The spatial connectivity of learning facilities (LFs) affects educational accessibility and learner behavior, serving as a key factor in designing urban educational environments. This study proposes a method for analyzing the distribution of local LFs using spatial big data and network analysis. The network of 788 LFs, including elementary, middle, and high schools, academies, tutoring centers, and libraries, across 5 boroughs in Daejeon was analyzed. Centrality measures were applied to assess the proximity of LFs and identify hubs within the network. Results showed the centrality distribution

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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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TAKAHASHI, KAZUKO, and TAKAO SUMITOMO. "THE QUALITATIVE TREATMENT OF SPATIAL DATA." International Journal on Artificial Intelligence Tools 16, no. 04 (2007): 661–82. http://dx.doi.org/10.1142/s0218213007003497.

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This paper aims at an efficient treatment of spatial data using qualitative representation. We propose a new framework called PLCA, which provides a symbolic representation for the figure in a two-dimensional plane, focusing on the connections between regions. It is based on four simple objects: points(P), lines(L), circuits(C) and areas(A). The entire figure is represented as a combination of these objects. Pairs of areas, circuits or lines never cross. The simple, clear data structure based on objects makes the system feasible and easy to implement. A PLCA expression can be subject to topolo

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Koh, Keumseok, Ayaz Hyder, Yogita Karale, and Maged N. Kamel Boulos. "Big Geospatial Data or Geospatial Big Data? A Systematic Narrative Review on the Use of Spatial Data Infrastructures for Big Geospatial Sensing Data in Public Health." Remote Sensing 14, no. 13 (2022): 2996. http://dx.doi.org/10.3390/rs14132996.

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Background: Often combined with other traditional and non-traditional types of data, geospatial sensing data have a crucial role in public health studies. We conducted a systematic narrative review to broaden our understanding of the usage of big geospatial sensing, ancillary data, and related spatial data infrastructures in public health studies. Methods: English-written, original research articles published during the last ten years were examined using three leading bibliographic databases (i.e., PubMed, Scopus, and Web of Science) in April 2022. Study quality was assessed by following well-

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Csomós, György. "On the challenges ahead of spatial scientometrics focusing on the city level." Aslib Journal of Information Management 72, no. 1 (2019): 67–87. http://dx.doi.org/10.1108/ajim-06-2019-0152.

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Purpose Spatial bibliometrics and scientometrics have traditionally focused on examining both country and regional levels; however, in recent years, numerous spatial analyses on the city level have been carried out. While city-level scientometric analyses have gained popularity among policymakers and statistical/economic research organizations, researchers in the field of bibliometrics are divided regarding whether it is possible to observe the spatial unit “city” through bibliometric and scientometric tools. The purpose of this paper is to reveal the most significant challenges ahead of spati

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Li, Yutang, Chen Xu, Dengfeng Liu, et al. "Lidar Doppler Tomography Focusing Error Analysis and Focusing Method for Targets with Unknown Rotational Speed." Remote Sensing 17, no. 3 (2025): 506. https://doi.org/10.3390/rs17030506.

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Lidar Doppler tomography (LDT) is a significant method for imaging rotating targets in long-distance air and space applications. Typically, these targets are non-cooperative and exhibit unknown rotational speeds. Inferring the rotational speed from observational data is essential for effective imaging. However, existing research predominantly emphasizes the development of imaging algorithms and interference suppression, often neglecting the analysis of rotational speed estimation. This paper examines the impact of errors in rotational speed estimation on imaging quality and proposes a robust m

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Keßler, Carsten, Albert Remke, Henryk Hodam, Fabian Przybylak, and Andreas Rienow. "OER4SDI: Open Educational Resources for Spatial Data Infrastructures." AGILE: GIScience Series 5 (May 30, 2024): 1–10. http://dx.doi.org/10.5194/agile-giss-5-9-2024.

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Abstract. Education on spatial data infrastructures is an important building block of study programs focusing on spatial data. The focus is on equipping students with essential skills for future contributions to spatial data infrastructure development and application. Despite a wide range of available teaching materials, their reuse is hindered by a lack of harmonization and integration into learning modules. This paper reports on the activities in the "Open Educational Resources for Spatial Data Infrastructures" (OER4SDI) project, which addresses this gap by developing easily reusable teachin

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Furman, Alex, Ty P. Ferré, and Gail L. Heath. "Spatial focusing of electrical resistivity surveys considering geologic and hydrologic layering." GEOPHYSICS 72, no. 2 (2007): F65—F73. http://dx.doi.org/10.1190/1.2433737.

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Electrical resistivity tomography (ERT) has shown great promise for monitoring transient hydrologic processes. One advantage of ERT under those conditions is the ability of a user to tailor the spatial sensitivity of an ERT survey through selection of electrode locations and electrode combinations. Recent research has shown that quadripoles can be selected in a manner that improves the independent inversion of ERT data. Our ultimate interest lies in using ERT data along with measurements from other sensors, which typically can provide high-quality data from shallow regions of the subsurface, i

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Feuillet, Thierry, Julien Coquin, Denis Mercier, et al. "Focusing on the spatial non-stationarity of landslide predisposing factors in northern Iceland." Progress in Physical Geography: Earth and Environment 38, no. 3 (2014): 354–77. http://dx.doi.org/10.1177/0309133314528944.

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Most studies focusing on landslide spatial analysis have considered the relationships between predictors and landslide occurrence as fixed effects. Yet spatially varying relationships, i.e. non-stationarity, often occur in any spatial data set and should be theoretically considered in statistical models for a better fit. In Skagafjörður, a landslide-rich north–south oriented area located in northern Iceland, we investigated whether spatial non-stationarity in the relationships between paraglacial variables (glacio-isostatic rebound and post-glacial debuttressing, both captured in this area by

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Serge, Decroly FEMBA. "Exploratory Analysis of Regional Disparities in Human Development in Cameroon." JOURNAL OF ECONOMICS, FINANCE AND MANAGEMENT STUDIES 5, no. 10 (2022): 3002–10. https://doi.org/10.5281/zenodo.7238318.

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The objective of this paper is to analyze the link between geographic location and the level of human development in Cameroon. To achieve that objective, we use Exploratory Spatial Data Analysis (ESDA) techniques on regional human development indices (HDI) in Cameroon from 2001 to 2014. The Moran test confirms the presence of a positive and significant global spatial autocorrelation of the regional human development indices. Thus, the values of the regional human development index in Cameroon are not randomly distributed. There is thus spatial clustering of regions with similar HDI levels. The

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Murakami, Daisuke, Mami Kajita, and Seiji Kajita. "Scalable Model Selection for Spatial Additive Mixed Modeling: Application to Crime Analysis." ISPRS International Journal of Geo-Information 9, no. 10 (2020): 577. http://dx.doi.org/10.3390/ijgi9100577.

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A rapid growth in spatial open datasets has led to a huge demand for regression approaches accommodating spatial and non-spatial effects in big data. Regression model selection is particularly important to stably estimate flexible regression models. However, conventional methods can be slow for large samples. Hence, we develop a fast and practical model-selection approach for spatial regression models, focusing on the selection of coefficient types that include constant, spatially varying, and non-spatially varying coefficients. A pre-processing approach, which replaces data matrices with smal

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Yeo, JungYoon, JooBong Jeong, and JongKyu Kim. "Spatial Distribution Characteristics of Seagrass Habitat Based on Remote Sensing Data: Focusing on Wan Island." GEO DATA 4, no. 2 (2022): 23–36. http://dx.doi.org/10.22761/dj2022.4.2.003.

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In May 2019, UAV photogrammetry using drones (unmanned aircraft) was conducted to investigate the spatial distribution characteristics of the seagrass habitat in Wan Island. Wan Is. sea was divided into 3 geographical areas (Site A, B, C) by referring to the seagrass distribution identified by the National Coastal seagrass forest precision survey (Ministry of Oceans and Fisheries, 2015), and contour lines were extracted from grid depth data. In addition, a 3-D benthic topographic map using DTM (Digital Terrain Model) was created to understand the characteristics and slope of the benthic topogr

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Ryan, Kendra, Andy Danylchuk, and Adrian Jordaan. "Is Marine Spatial Planning Enough to Overcome Biological Data Deficiencies?" Journal of Environmental Assessment Policy and Management 20, no. 04 (2018): 1850012. http://dx.doi.org/10.1142/s1464333218500126.

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The United States only accounts for 0.2% of the global offshore wind installed capacity despite a potential technical resource four orders of magnitude greater. A cumbersome permitting process is one of the challenges in implementing new projects. Part of this process requires biological data in order to inform assessments of environmental impacts; yet these data may be lacking for particular taxa at the required scale. Marine spatial planning (MSP) is a process that often includes data identification, collection, collation and analyses components. In this paper, we conduct a collective case s

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Tian, Siquan, Yong Chen, Xinjun Chen, Liuxiong Xu, and Xiaojie Dai. "Impacts of spatial scales of fisheries and environmental data on catch per unit effort standardisation." Marine and Freshwater Research 60, no. 12 (2009): 1273. http://dx.doi.org/10.1071/mf09087.

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Spatial scale is an important factor that needs to be considered in data collection and analysis in ecological studies. Studies focusing on the quantitative evaluation of impacts of spatial scales are, however, limited in fisheries. Using the Chinese squid-jigging fishery in the north-western Pacific Ocean as an example, we evaluated impacts of spatial scale used in grouping fisheries and environmental data on the standardisation of fisheries catch per unit effort (CPUE). We developed 18 scenarios of different spatial scales with a combination of three latitudinal levels (0.5°, 1° and 2°) and

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Li, Heng, Wei Huang, Yong Zhai, Wenhao Zhao, Xinyan Zheng, and Jin Liu. "Research on New Spatial Data Infrastructure Supports the Circulation of Geographic Information Data Elements." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4-2024 (October 21, 2024): 303–9. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-2024-303-2024.

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Abstract. Data is an important factor of production in the digital economy era and an important support for building a new development pattern. As an important part of data resources, geographic information data is also an important new factor of production, which plays a unique role in the construction of digital China and economic and social development. From the perspective of releasing the value of data elements, data infrastructure is a new type of infrastructure that provides integrated data aggregation, processing,circulation, application, operation, and security services for society un

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Guimarães, Nathalie, Luís Pádua, Pedro Marques, Nuno Silva, Emanuel Peres, and Joaquim J. Sousa. "Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities." Remote Sensing 12, no. 6 (2020): 1046. http://dx.doi.org/10.3390/rs12061046.

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Currently, climate change poses a global threat, which may compromise the sustainability of agriculture, forestry and other land surface systems. In a changing world scenario, the economic importance of Remote Sensing (RS) to monitor forests and agricultural resources is imperative to the development of agroforestry systems. Traditional RS technologies encompass satellite and manned aircraft platforms. These platforms are continuously improving in terms of spatial, spectral, and temporal resolutions. The high spatial and temporal resolutions, flexibility and lower operational costs make Unmann

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Jorgensen, Michael, Michael S. Zhdanov, and Brian Parsons. "3D Focusing Inversion of Full Tensor Magnetic Gradiometry Data with Gramian Regularization." Minerals 13, no. 7 (2023): 851. http://dx.doi.org/10.3390/min13070851.

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Full tensor magnetic gradiometry (FTMG) is becoming a practical method for exploration due to recent advancements in superconducting quantum interference device (SQUID) technology. This paper introduces an efficient method of 3D modeling and inversion of FTMG data. The forward modeling uses single-point Gaussian integration with pulse basis functions to compute the volume integrals representing the second spatial derivatives of the magnetic potential. The inversion is aimed at recovering both the magnetic susceptibility and magnetization vectors. We have introduced a 3D regularized focusing in

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Zhao, T., X. Zhu, W. Liu, et al. "RESEARCH ON THEMATIC DATA PROCESSING AND DATABASE CONSTRUCTION OF SEQUENCE DIAGRAM." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022 (June 2, 2022): 395–401. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2022-395-2022.

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Abstract. The sequence diagram in the atlas shall represent the latest macro overview achievements of the country, closely focusing on the major national development strategies, and select topics directly related to economic construction and people's life, including thematic information such as sea area, railway, highway, population, tourism, forest, nature reserve, surface coverage, urban agglomeration and strategic layout. According to the selected thematic content, the relevant thematic information is collected and analyzed, and the available thematic information data is extracted through d

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Barros, Pedro Henrique Batista de, and Alysson Luiz Stege. "Socioeconomic Development and Deforestation in the Cerrado Biome, Brazil: Spatial Interactions and Heterogeneity." Revista Brasileira de Estudos Regionais e Urbanos 15, no. 3 (2022): 393–415. http://dx.doi.org/10.54766/rberu.v15i3.792.

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This paper investigates the relationship between socioeconomic development and deforestation in the Cerrado biome, mainly focusing on the current Brazilian agricultural frontier of Matopiba. More specifically, we search for spatial interactions, heterogeneity, and spatial clusters among the municipalities using the exploratory analysis of spatial data (ESDA). Due to the many possible socioeconomic variables related to deforestation decisions, we create a Socioeconomic Development Index (SDI) that synthesizes all possible influences using factorial analysis from multivariate statistics. We also

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Fadjarajani, Siti, Ruli As’ari, and Anita Eka Putri. "Model of Problem-Based Learning in Geography: Focusing on Societal Dynamics to Enhance Spatial Thinking Skills." E3S Web of Conferences 600 (2024): 02011. http://dx.doi.org/10.1051/e3sconf/202460002011.

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This article explores how problem-based learning (PBL) can enhance geography education by improving spatial thinking through social dynamics. Spatial thinking is crucial for understanding geography’s social complexity and advancing STEM education quality. Geographic Information Systems (GIS) and the Spatial-Based Learning (SBL) model are utilized to develop these skills, vital for disaster management and emergencies. The study employs participatory action research, involving students, teachers, and communities in solving real-world problems, assessing PBL’s impact on spatial thinking in geogra

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Et.al, Yun-Young Hwang. "Linked Method of Open Government Data by Datasets Oriented." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 780–85. http://dx.doi.org/10.17762/turcomat.v12i6.2095.

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In order to make public data more useful, it is necessary to provide relevant data sets that meet the needs of users. We introduce the method of linkage between datasets. We provide a method for deriving linkages between fields of structured datasets provided by public data portals. We defined a dataset and connectivity between datasets. The connectivity between them is based on the metadata of the dataset and the linkage between the actual data field names and values. We constructed the standard field names. Based on this standard, we established the relationship between the datasets. This pa

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McLaughlin, Dennis, Yuhua Zhou, Dara Entekhabi, and Virat Chatdarong. "Computational Issues for Large-Scale Land Surface Data Assimilation Problems." Journal of Hydrometeorology 7, no. 3 (2006): 494–510. http://dx.doi.org/10.1175/jhm493.1.

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Abstract Land surface data assimilation problems are often limited by the high dimensionality of states created by spatial discretization over large high-resolution computational grids. Yet field observations and simulation both confirm that soil moisture can have pronounced spatial structure, especially after extensive rainfall. This suggests that the high dimensionality of the problem could be reduced during wet periods if spatial patterns could be more efficiently represented. After prolonged drydown, when spatial structure is determined primarily by small-scale soil and vegetation variabil

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., Subha, Anurag Patel, and Saranraj . "A Multi Model Approach: A Data Engineering Driven Pipeline Model for Detecting Anomaly in Sensor Data using Stacked LSTM." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2800–2805. http://dx.doi.org/10.22214/ijraset.2023.52084.

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Abstract: This study uses a self-supervised learning technique based on auto encoders to find anomalous nodes. Only temporal variables have been taken into account and researched so far for use in identifying anomalies in wireless sensor networks (WSNs). This method fully utilises the geographic and temporal information of the WSN for anomaly identification by incorporating the extraction of geographic location features, intermodal WSN correlation features, and temporal WSN data flow characteristics into the design of the autoencoder. First, by focusing on a single mode from a local spatial pe

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Knura, Martin, and Jochen Schiewe. "Preserving Spatial Patterns in Point Data: A Generalization Approach Using Agent-Based Modeling." ISPRS International Journal of Geo-Information 13, no. 12 (2024): 431. https://doi.org/10.3390/ijgi13120431.

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Visualization and interpretation of user-generated spatial content such as Volunteered Geographic Information (VGI) is challenging because it combines enormous data volume and heterogeneity with a spatial bias. When dealing with point data on a map, these characteristics can lead to point clutter, reducing the readability of the map product and misleading users to false interpretations of patterns in the data, e.g., regarding specific clusters or extreme values. With this work, we provide a framework that is able to generalize point data, preserving spatial clusters and extreme values simultan

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Mokhonko, Oleksandr, and Anatoliy Ivanisik. "Calculation position of the focal point in self-focusing media." InterConf, no. 43(193) (March 20, 2024): 429–35. http://dx.doi.org/10.51582/interconf.19-20.03.2024.042.

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Using a laser beam in a self-focusing environment with different power more and less than the critical one, more accurate coordinates of the point with the maximum radiation intensity were obtained. The results of the calculations corresponded to the experimental data obtained by spatial filtering of the angular spectra of forced Raman scattering. The agreement of the results was satisfactory for all beam power levels.

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Giraldo, Ramón, Víctor Leiva, and Cecilia Castro. "An Overview of Kriging and Cokriging Predictors for Functional Random Fields." Mathematics 11, no. 15 (2023): 3425. http://dx.doi.org/10.3390/math11153425.

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This article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions. A significant aspect of the functional random fields analysis is evaluating stationarity to characterize the stability of statistical properties across the spatial domain. The article explores methodologies from the literature, providing insights into the challenges and advancements in functional geostatistics. This work is relevant from theoretical and practical perspectives, offering an integrated view of methodologies tailored to the specif

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Piao, Minrui. "Deciphering Biological Function Difference Between MO::L1 and MO::L2/3 in Mouse Brain from Spatial Transcriptomics Data." Theoretical and Natural Science 67, no. 1 (2024): 160–65. https://doi.org/10.54254/2753-8818/2024.18874.

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Parsing brain structure is crucial in neuroscience research, and the advent of spatial transcriptomics offers unprecedented molecular opportunities. In this study, we utilized 10X Visium spatial transcriptomics to analyze the mouse hindbrain, focusing on the MO::L1 and MO::L2/3 regions. By integrating artificial priors with the SpaceFlow method, we identified spatial organization and conducted differential gene expression analysis. Key findings include the identification of TGF-beta and Hippo signaling pathways, crucial for neurodevelopment and injury repair. Our results highlight the roles of

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Bao, Min, Song Zhou, and Mengdao Xing. "Processing Missile-Borne SAR Data by Using Cartesian Factorized Back Projection Algorithm Integrated with Data-Driven Motion Compensation." Remote Sensing 13, no. 8 (2021): 1462. http://dx.doi.org/10.3390/rs13081462.

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Due to the independence of azimuth-invariant assumption of an echo signal, time-domain algorithms have significant performance advantages for missile-borne synthetic aperture radar (SAR) focusing with curve moving trajectory. The Cartesian factorized back projection (CFBP) algorithm is a newly proposed fast time-domain implementation which can avoid massive interpolations to improve the computational efficiency. However, it is difficult to combine effective and efficient data-driven motion compensation (MOCO) for achieving high focusing performance. In this paper, a new data-driven MOCO algori

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Bo, Chen, Shan Miao, Yun Zhao, and Jinyu Li. "Assessing Forest Quality Using Multi-Source Satellite Remote Sensing Data." International Journal of Distributed Systems and Technologies 16, no. 1 (2025): 1–19. https://doi.org/10.4018/ijdst.383047.

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This study uses Sentinel satellite data to estimate forest quality over a large area, focusing on Beijing. By combining ground survey data with remote sensing, a random forest model predicts forest parameters. The results show a correlation coefficient of 0.60-0.76 and a relative root mean square error of 0.09-0.39. Average tree height and diameter at breast height (DBH) had the highest accuracy (75%-80%), followed by canopy density and plant number density (68%-75%). The spatial agreement between predicted and actual forest quality indicates the model's effectiveness.

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Rajvanshi, Tushar, Maria Antonia Maisto, Angela Dell’Aversano, and Raffaele Solimene. "Image-Based RCS Estimation from Near-Field Data." Journal of Imaging 5, no. 6 (2019): 61. http://dx.doi.org/10.3390/jimaging5060061.

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This paper deals with the problem of estimating the RCS from near-field data by image-based approaches. In particular, a rigorous focusing procedure based on a weighted adjoint scheme, which is also applicable to an arbitrary measurement curve, is developed. The developed formalism allows us to address the important question concerning the need to employ a multi-frequency configuration to estimate the RCS. Accordingly, it is shown that if RCS is required at a given frequency, then the target image obtained solely at such a frequency can be exploited provided that the spatial truncation arising

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Pan, Q., Y. H. Dong, and F. L. Peng. "A data-informed assessment method for the urban underground complex vitality." IOP Conference Series: Earth and Environmental Science 1333, no. 1 (2024): 012011. http://dx.doi.org/10.1088/1755-1315/1333/1/012011.

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Abstract The urgent need for urban renewal and the rapid expansion of underground spaces has spurred the construction of urban underground complexes (UUCs). Vibrant UUCs are crucial for the efficient utilization of underground spaces and urban sustainability. Previous research on urban underground complex vitality (UUCV) has been primarily theoretical with limited reusability. In this study, we aimed to address this gap by focusing on underground functional facilities and spatial distribution characteristics to establish a UUCV indicator system based on walkability theory. We introduced a meth

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Li, Zhe, Tianlian Wang, and Su Sun. "Research on Quantitative Analysis Methods for the Spatial Characteristics of Traditional Villages Based on Three-Dimensional Point Cloud Data: A Case Study of Liukeng Village, Jiangxi, China." Land 13, no. 8 (2024): 1261. http://dx.doi.org/10.3390/land13081261.

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Traditional villages are important carriers of cultural heritage, and the quantitative study of their spatial characteristics is an important approach to their preservation. However, the rapid extraction, statistics, and estimation of the rich spatial characteristic indicators in these villages have become bottlenecks in traditional village research. This paper employs UAV (unmanned aerial vehicle) and handheld laser scanners to acquire three-dimensional point cloud data and construct a spatial feature three-dimensional calculation workflow of “field data collection—data processing—data analys

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Bangi, Shashank C., and Veena S. Soraganvi. "Estimation of spatial surface energy fluxes and actual evapotranspiration over Ghataprabha river basin using remote sensing data." E3S Web of Conferences 455 (2023): 03008. http://dx.doi.org/10.1051/e3sconf/202345503008.

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Accurately measuring Actual Evapotranspiration (AET) in spatial scale is a crucial yet challenging task within the hydrological cycle, playing a pivotal role in determining the water requirements of diverse crops. Consequently, precise estimation of Evapotranspiration (ET) at a spatial scale is imperative for regions characterized by arid and semiarid conditions, such as the Ghataprabha river basin. In current study, actual evapotranspiration was estimated using SEBAL algorithm utilizing Landsat-8 satellite data and meteorological data, focusing on the Ghataprabha river basin situated in Karna

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Noa-Yarasca, Efrain, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, and Douglas R. Smith. "Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices?" AI 6, no. 3 (2025): 58. https://doi.org/10.3390/ai6030058.

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Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. This study introduces an innovative approach to crop yield prediction by incorporating spatially lagged spectral data (SLSD) through the spatial-lagged machine learning (SLML) model, an enhanced version of the spatial lag X (SLX) model. The research aims to show that SLSD improves prediction compared to traditional vegetation index (VI)-based methods.

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Oh, Yun Sook, Mina Kim, and Jae Eun Yoon. "A study on resilience characteristics in the architecture of Lacaton & Vassal: Focusing on the French apartment Transfomation Projects." Korea Institute of Design Research Society 8, no. 4 (2023): 324–34. http://dx.doi.org/10.46248/kidrs.2023.4.324.

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This study aims to investigate the characteristics of space through the architecture of Lacaton & Vassal and to analyze elements that enhance spatial resilience. By examining the architectural philosophy of Lacaton & Vassal, the study focuses on three remodeling projects in France to explore strategies and elements that strengthen spatial resilience. To achieve the research objectives, a reclassification of space resilience characteristics was conducted based on a review of previous studies on resilience, and criteria for analysis were established. This involved an in-depth analysis of

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Suman, Abdulla Al, Carlo Russo, Ann Carrigan, et al. "Spatial and time domain analysis of eye-tracking data during screening of brain magnetic resonance images." PLOS ONE 16, no. 12 (2021): e0260717. http://dx.doi.org/10.1371/journal.pone.0260717.

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Introduction Eye-tracking research has been widely used in radiology applications. Prior studies exclusively analysed either temporal or spatial eye-tracking features, both of which alone do not completely characterise the spatiotemporal dynamics of radiologists’ gaze features. Purpose Our research aims to quantify human visual search dynamics in both domains during brain stimuli screening to explore the relationship between reader characteristics and stimuli complexity. The methodology can be used to discover strategies to aid trainee radiologists in identifying pathology, and to select regio

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Chen, Chen. "Changes in the Spatial Distribution of the Employed Population in the Yangtze River Delta Region since the 21st Century: An Analysis and Discussion Based on Census Data." Land 12, no. 6 (2023): 1249. http://dx.doi.org/10.3390/land12061249.

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Focusing on the Yangtze River Delta region, the spatial distribution and change characteristics of the employed population were assessed by selecting three time points: 2000, 2010 and 2020. Firstly, a correlation was established between population employment statistics and spatial units of administrative divisions to analyze the spatial distribution characteristics of the employed population in general and by industry; secondly, the changing characteristics of the spatial distribution of the employed population over time, including the migration of the centroid and density changes, were analyz

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Erlebach, Martin, Marián Halás, Jan Daniel, and Pavel Klapka. "Is there congruence in the spatial patterns of regions derived from scalar and vector geographical information?" Moravian Geographical Reports 27, no. 1 (2019): 2–14. http://dx.doi.org/10.2478/mgr-2019-0001.

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Abstract Selected traits of the spatial organisation of a geographical environment which stem from two types of human behaviour (locational and interactive) are examined in this paper. An attempt is made to find and account for similarities in the spatial patterns of scalar and vector geographical data. In doing so, the paper analyses a core-periphery dichotomy, based on socio-economic information, and travel-to-work patterns. The paper uses the concept of a region as an integrating and focusing framework for the study. Formal regions (peripheral areas) are defined through the application of p

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Risimati, Brightnes, Trynos Gumbo, and James Chakwizira. "Spatial Integration of Non-Motorized Transport and Urban Public Transport Infrastructure: A Case of Johannesburg." Sustainability 13, no. 20 (2021): 11461. http://dx.doi.org/10.3390/su132011461.

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Sustainability of transport infrastructure integration begins with involving an all-inclusive transportation chain instead of only focusing on one part of the journey. This is achieved by facilitating spatial integration between diverse transport modalities to allow for a multiplicity of travel opportunities. This paper unpacks the extent of the spatial integration of non-motorized transport and urban public transport infrastructure within the city of Johannesburg in South Africa. Cycling activity datasets derived from Strava Metro and the spatial data of urban public transport infrastructures

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Lee, Il Sup, Kyung Kyu Kim, and Ae Ri Lee. "A Big Data Analysis Methodology for Examining Emerging Trend Zones Identified by SNS Users : Focusing on the Spatial Analysis Using Instagram Data." Information Systems Review 20, no. 2 (2018): 63–85. http://dx.doi.org/10.14329/isr.2018.20.2.063.

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Liyew, Alemneh Mekuriaw, Malede Mequanent Sisay, and Achenef Asmamaw Muche. "Spatial distribution and factors associated with low birth weight in Ethiopia using data from Ethiopian Demographic and Health Survey 2016: spatial and multilevel analysis." BMJ Paediatrics Open 5, no. 1 (2021): e000968. http://dx.doi.org/10.1136/bmjpo-2020-000968.

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ObjectiveThis study aimed to assess the spatial distribution, individual and community-level factors associated with low birth weight in Ethiopia.MethodSecondary data analysis was conducted using the 2016 Ethiopian Demographic and Health Survey data. A total of 2110 neonates were included in this study. Spatial autocorrelation analysis was conducted to assess the spatial clustering of LBW. Besides, the spatial scan statistics and ordinary kriging interpolation were done to detect the local level clusters and to assess predicted risk areas, respectively. Furthermore, a multilevel logistic regre

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Olusoji, J. Daniel, A. Adejumo Olusola, S. Oritogun Kolawole, O. Jaiyesimi Ebunoluwa, and W. Ladi-Akinyemi Temitope. "The Spatial Distribution of HIV Prevalence Rates in Nigeria." British Journal of Medicine & Medical Research 21, no. 7 (2017): 1–10. https://doi.org/10.9734/BJMMR/2017/33184.

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Nigeria has witnessed a gradual decline in the national trend of HIV prevalence from the peak of 5.8% in 2001 to 3.4% in 2012. In spite of the decline nationally, there is a wide variation in the distribution of HIV at the sub-national level. This study therefore aims to explore the spatial distribution of HIV in Nigeria. The study was an ecological study of secondary data of the National HIV prevalence studies conducted between 2008 and 2012. The global Moran’s <em>I</em> and Local Moran’s <em>I</em> (LISA) test were used to measure spatial autocorrelation. A final choropleth map of local Mor

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Bertrand, Sophie, Julian M. Burgos, François Gerlotto, and Jaime Atiquipa. "Lévy trajectories of Peruvian purse-seiners as an indicator of the spatial distribution of anchovy (Engraulis ringens)." ICES Journal of Marine Science 62, no. 3 (2005): 477–82. http://dx.doi.org/10.1016/j.icesjms.2004.12.002.

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Abstract Analogous to other top predators foraging on patchy resources, the spatial behaviour of fishers provides information on the spatial organization of fish. Focusing on the Peruvian anchovy purse-seine fishery, vessel monitoring system data are used to describe fishing vessels' trajectories, and acoustic survey data to characterize anchovy spatial distribution. Vessel trajectories were analysed in terms of move-length distribution, whereas fish distribution was characterized by spatial extent, concentration, and fractal dimension. Fishers perform Lévy flights that can be characterized by

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Jiang, Shangjing, Haiping Zhang, Haoran Wang, Lei Zhou, and Guoan Tang. "Using Restaurant POI Data to Explore Regional Structure of Food Culture Based on Cuisine Preference." ISPRS International Journal of Geo-Information 10, no. 1 (2021): 38. http://dx.doi.org/10.3390/ijgi10010038.

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As a result of the influence of geographical environment and historical heritage, food preference has significant regional differentiation characteristics. However, the spatial structure of food culture represented by the cuisine culture at the regional level has not yet been explored from the perspective of geography. Cultural regionalization is an important way to analyze and understand the spatial structure of food culture. It is of great significance to deeply mine intra-regional homogeneity and scientifically cognize inter-regional cultural characteristics. This study aims to explore such

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Chen, Yuling, Yang Lou, and Jesse Yen. "Dynamic Transmit–Receive Beamforming by Spatial Matched Filtering for Ultrasound Imaging with Plane Wave Transmission." Ultrasonic Imaging 39, no. 4 (2017): 207–23. http://dx.doi.org/10.1177/0161734617692017.

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During conventional ultrasound imaging, the need for multiple transmissions for one image and the time of flight for a desired imaging depth limit the frame rate of the system. Using a single plane wave pulse during each transmission followed by parallel receive processing allows for high frame rate imaging. However, image quality is degraded because of the lack of transmit focusing. Beamforming by spatial matched filtering (SMF) is a promising method which focuses ultrasonic energy using spatial filters constructed from the transmit–receive impulse response of the system. Studies by other res

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Friesen, John, Victoria Friesen, Ingo Dietrich, and Peter F. Pelz. "Slums, Space, and State of Health—A Link between Settlement Morphology and Health Data." International Journal of Environmental Research and Public Health 17, no. 6 (2020): 2022. http://dx.doi.org/10.3390/ijerph17062022.

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Approximately 1 billion slum dwellers worldwide are exposed to increased health risks due to their spatial environment. Recent studies have therefore called for the spatial environment to be introduced as a separate dimension in medical studies. Hence, this study investigates how and on which spatial scale relationships between the settlement morphology and the health status of the inhabitants can be identified. To this end, we summarize the current literature on the identification of slums from a geographical perspective and review the current literature on slums and health of the last five y

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Wang, Juefu, Mark Ng, and Mike Perz. "Seismic data interpolation by greedy local Radon transform." GEOPHYSICS 75, no. 6 (2010): WB225—WB234. http://dx.doi.org/10.1190/1.3484195.

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We propose a greedy inversion method for a spatially localized, high-resolution Radon transform. The kernel of the method is based on a conventional iterative algorithm, conjugate gradient (CG), but is utilized adaptively in amplitude-prioritized local model spaces. The adaptive inversion introduces a coherence-oriented mechanism to enhance focusing of significant model parameters, and hence increases the model resolution and convergence rate. We adopt the idea in a time-space domain local linear Radon transform for data interpolation. We find that the local Radon transform involves iterativel

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Zhang, Huangchuang, Ge Li, and Meilin Pu. "BIM Data Model Based on Multi-Scale Grids in Civil Engineering Buildings." Remote Sensing 16, no. 4 (2024): 690. http://dx.doi.org/10.3390/rs16040690.

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The construction of digital twin cities is a current research hotspot; GIS technology and BIM technology are widely used in the field of digital twin cities. However, BIM is still subject to major limitations in its applications, mainly due to huge amounts of model data, low query efficiency and accuracy, non-uniform marking systems, etc. The reason is that the BIM model itself focuses more on the expression of visual effects and lacks spatial calculation ability and the utilization of spatial location information. Secondly, the current lightweight processing methods for BIM models are mostly

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Rendra, Meldi, and Estananto Estananto. "SPATIAL PLANNING IN SUPPORTING VILLAGE DEVELOPMENT." Charity 6, no. 1a (2023): 1. http://dx.doi.org/10.25124/charity.v6i1a.5899.

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    Planning degrees have been focusing on rural studies, which make the best planning system for prevailing social welfare in villages. While village governments know development studies by demographic data in tabulation to evaluate/design the planning policies better or not. Different rural study models have been enriched and implemented in the past time. We use GIS to prove planning measures to be effective in rural governance to expand the decision-making process in planning policies. The participation/action research experienced a targeted planning policy in Covid

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Giri, Aviskar, Vasit Sagan, and Michael Podgursky. "The Ballpark Effect: Spatial-Data-Driven Insights into Baseball’s Local Economic Impact." Applied Sciences 14, no. 18 (2024): 8134. http://dx.doi.org/10.3390/app14188134.

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The impact of sporting events on local economies and their spatial distribution is a topic of active policy debate. This study adds to the discussion by examining granular cellphone location data to assess the spillover effects of Major League Baseball (MLB) games in a major US city. Focusing on the 2019 season, we explore granular geospatial patterns in mobility and consumer spending on game days versus non-game days in the Saint Louis region. Through density-based clustering and hotspot analysis, we uncover distinct spatiotemporal signatures and variations in visitor affluence across differe

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