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Guaragnella, Cataldo, and Tiziana D’Orazio. "A Data-Driven Approach to SAR Data-Focusing." Sensors 19, no. 7 (April 6, 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 parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses.
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TAKAHASHI, KAZUKO, and TAKAO SUMITOMO. "THE QUALITATIVE TREATMENT OF SPATIAL DATA." International Journal on Artificial Intelligence Tools 16, no. 04 (August 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 topological reasoning such as judging the connection patterns of areas. We define the operations of area integration and area division on a PLCA expression. These operations preserve the consistency of the expression, and correspond to real actions on the figures. We can add attributes to each object, such as the properties that hold on an area or that an object represents, and make an attributed PLCA. The operations of area integration/division on an attributed PLCA correspond to the alteration of the classification level of objects, and semantic spatial reasoning can be performed on an attributed PLCA.
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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 (June 23, 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-established practices in the literature. Results: A total of thirty-two articles were identified through the literature search. We observed the included studies used various data-driven approaches to make better use of geospatial big data focusing on a range of health and health-related topics. We found the terms ‘big’ geospatial data and geospatial ‘big data’ have been inconsistently used in the existing geospatial sensing studies focusing on public health. We also learned that the existing research made good use of spatial data infrastructures (SDIs) for geospatial sensing data but did not fully use health SDIs for research. Conclusions: This study reiterates the importance of interdisciplinary collaboration as a prerequisite to fully taking advantage of geospatial big data for future public health studies.
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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 (November 20, 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 spatial scientometrics focusing on the city level by examining relevant scientometric studies. Design/methodology/approach This analysis involves the most significant spatial scientometric studies focusing on the city level and carefully examines how they collect bibliometric and/or scientometric data, what methodologies they employ to process bibliometric data and most importantly, how they approach the spatial unit “city”. Findings After systematically scrutinizing relevant studies in the field, three major problems have been identified: there is no standardized method of how cities should be defined and how metropolitan areas should be delineated; there is no standardized method of how bibliometric and scientometric data on the city level should be collected and processed; and it is not clearly defined how cities can profit from the results of bibliometric and scientometric analysis focusing on them. Originality/value This is the first study that compiles a “database” of scientometric studies focusing on the city level. The paper not only reveals major challenges ahead of city level spatial analysis but recommends some possible solution as well.
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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 (March 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, in a joint inversion. As a result, we do not consider the selection of quadripoles specifically for inde-pendent ERT inversion. Rather, we present an approach to focusthe spatial sensitivity of ERT surveys in specificsubsurface regions with the assumption that those data, when interpreted along with other measurements that are sensitive to those regions, will lead to more complete hydrologic characterization. Because we are interested in monitoring rapid processes, our approach is designed to efficiently identify optimal quadripoles. This is achieved by separating the optimization from the inversion grid, significantly reducing computational effort. We extend our previous work to consider the use of both surface and borehole ERT electrodes and to consider the impacts of horizontally layered electrical conductivity conditions. Results confirm the ability of the method to focus survey sensitivity while showing the importance of incorporation of prior knowledge of the subsurface electric conductivity structure in designing optimal ERT surveys.
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Feuillet, Thierry, Julien Coquin, Denis Mercier, Etienne Cossart, Armelle Decaulne, Helgi Páll Jónsson, and þorsteinn Sæmundsson. "Focusing on the spatial non-stationarity of landslide predisposing factors in northern Iceland." Progress in Physical Geography: Earth and Environment 38, no. 3 (April 16, 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 latitude) and landslide locations is detectable. To explore the non-stationarity of factors that predispose landslide occurrence, we performed two logistic regression models, one global (GLR) and the other enabling the regression parameters to vary locally (geographically weighted logistic regression, GWLR). Each model was computed with two types of outcome, one based on the entire masses of landslides and the other only on the scarps of landslides. GLR results reveal that increasing latitude is associated with increasing probability of landslide occurrence, confirming that post-glacial rebound is of prime importance at the regional scale. Nevertheless, GWLR indicates that this relationship is absent or reversed at some locations, meaning that the influence of paraglacial and other predisposing factors of landsliding (slope, valley depth and curvature) vary at the local scale. This result sheds light on the spatial clustering of three subzones where landsliding drivers are homogeneous. We conclude that a GWR-based approach provides some significant inputs for spatial analysis of mass movement processes, by identifying multi-scale process control zones and by highlighting local drivers, indecipherable in global models.
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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 (September 30, 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 small inner products through dimension reduction, dramatically accelerates the computation speed of model selection. Numerical experiments show that our approach selects a model accurately and computationally efficiently, highlighting the importance of model selection in the spatial regression context. Then, the present approach is applied to open data to investigate local factors affecting crime in Japan. The results suggest that our approach is useful not only for selecting factors influencing crime risk but also for predicting crime events. This scalable model selection will be key to appropriately specifying flexible and large-scale spatial regression models in the era of big data. The developed model selection approach was implemented in the R package spmoran.
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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 (December 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 study of three areas with offshore wind projects located in waters managed by marine spatial plans, focusing on how data efforts inform MSP and offshore wind development. Our study finds that MSP can facilitate data efforts during the permitting phase of offshore wind projects, but that other initiatives, particularly renewable energy policies and zoning, appear critical towards establishing offshore wind.
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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 (June 30, 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 topographic map. Through the analysis of the seagrass distribution results and the water depth results, it was confirmed that the boundary between the seagrass distribution in the outer and coastal areas converges to different water depth limits (within 10 m, and within 5 m), which is estimated to be based on the characteristics of the outer sea area. As a result of the analysis of the benthic topography, it was confirmed that the slope of the well-covered distribution was relatively gentle below 0.2~0.8 degrees, and the well-covered distribution was limited to the vicinity of the boundary where the slope changed rapidly. As a result of comparing the area of the seagrass distribution survey in 2015 and 2019, it was confirmed that the area was 238.4 ha and 1,070.9 ha, respectively, which was 4.5 times more widerly when performing Drone survey than diving survey. In order to understand the surrounding environment of the seagrass distribution site, satellite image data and license fishing ground information map at the time of drone shooting (May 2019) were checked. As a result, seaweed (Kelp, Sea mustard seaweed, Seaweed, Seaweed fulvescens, etc.) and shellfish (Abalone) were densely distributed, and most of the facilities except for Seaweed fulvescens farms were separated from their habitat. Drone survey confirmed Zostera marina, Zostera caulescens, and Zostera japonica in Wan Is., but no Phyllospadix iwatensis and Halophila nipponica were identified in 2015. It was confirmed that there was a limit to classifying the types of vegetation due to the characteristics of Phyllospadix iwatensis attached to the rock substrate, and in the case of Halophila nipponica with short leaves of 2 to 3 cm, they were not exposed to the water even at low tide, so there was a limit to detection using drones. These research results are expected to be useful data for grasping the characteristics of a wide range of seagrass habitats in other seas in the future.
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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 six longitudinal levels (0.5°, 1°, 2°, 3°, 4° and 5°) to aggregate the data. We then applied generalised additive models to analyse the 18 scenarios of data for the CPUE standardisation, and quantified differences among the scenarios. This study shows that longitudinal and latitudinal spatial scale and size of the spatial area for data aggregation can greatly influence the standardisation of CPUE. We recommend that similar studies be undertaken whenever possible to evaluate the roles of spatial scales and to identify the optimal spatial scale for data aggregations in the standardisation of CPUE and fisheries stock assessment.
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Zhao, T., X. Zhu, W. Liu, W. Ma, Y. Peng, Y. Zhang, X. Wang, Y. Wan, and X. Di. "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 data normalization and spatial processing, and then spatially matched with the thematic geographic base map to form a thematic map database. This paper studies how to deal with the thematic data in the sequence diagram and how to build the database, including thematic data analysis, thematic data processing, thematic database construction and quality requirements.
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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 (June 23, 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 inversion technique that utilizes Gramian regularization and a moving sensitivity domain approach. We have also developed a new method of magnetization vector decomposition into induced and remanent parts. The case study includes applying the developed inversion method and computer code to interpret a helicopter-borne FTMG survey carried out over the Thompson Nickel Belt. We have analyzed and separately inverted the observed FTMG and total magnetic intensity (TMI) data using the developed 3D inversion methods to obtain the subsurface susceptibility and magnetization vector models. Furthermore, we present a comparison of the inversions utilizing the FTMG data and the TMI data.
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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 (April 11, 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 paper covers 31,692 structured datasets (as of May 31, 2020) among the public data portal datasets. We extracted 1,185,846 field names from over 30,000 datasets. We extracted 1,185,846 field names from over 30,000 datasets. As a result of analyzing the field names, the field names related to spatial information were the most common at 35%. This paper verified the method of deriving the relation between data sets, focusing on the field names classified as spatial information. For this reason, we have defined spatial standard field names. To derive similar field names, we extracted related field names into spaces such as locations, coordinates, addresses, and zip codes used in public datasets. The standard field name of spatial information was designed and derived 43% cooperation rate of 31,692 datasets. In the future, we plan to apply similar field names additionally to improve the data set cooperation rate of the spatial information standard.
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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 (March 24, 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 Unmanned Aerial Vehicles (UAVs) a good alternative to traditional RS platforms. In the management process of forests resources, UAVs are one of the most suitable options to consider, mainly due to: (1) low operational costs and high-intensity data collection; (2) its capacity to host a wide range of sensors that could be adapted to be task-oriented; (3) its ability to plan data acquisition campaigns, avoiding inadequate weather conditions and providing data availability on-demand; and (4) the possibility to be used in real-time operations. This review aims to present the most significant UAV applications in forestry, identifying the appropriate sensors to be used in each situation as well as the data processing techniques commonly implemented.
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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 (September 8, 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 grouped cluster analysis municipalities with dissimilar deforestation and economic development patterns. The results show that the biome’s economic development and deforestation are spatially concentrated and heterogeneous and are negatively associated for the majority of Cerrado municipalities both in the spatial and cluster analysis, indicating that socioeconomic development may be an inhibitor of deforestation.
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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 (May 31, 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 perspective, a fully connected network is used to temporal nodes. Second, the spatial and temporal characteristics of the data flows of the nodes and their neighbours are retrieved by concentrating on a specific mode and seeing the WSN topology from a global spatial perspective for anomaly identification. The adaptive fusion method's weighted summation step is then used to extract the relevant features from the various models. An LSTM is used in this study to solve the problem of long-term dependence in the temporal dimension. The decoder's reconstructed output and the hidden layer representation of the are used to calculate the anomaly probability of the current system utilising a fully linked network.
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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 (June 1, 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 variability rather than rainfall, the original high-dimensional problem can be effectively replaced by many independent low-dimensional problems that can be solved in parallel with relatively little effort. In reality, conditions are continually varying between these two extremes. This is confirmed by a singular value decomposition of the replicate matrix (covariance square root) produced in an ensemble forecasting simulation experiment. The singular value spectrum drops off quickly after rainfall events, when a few leading modes dominate the spatial structure of soil moisture. The spectrum is much flatter after a prolonged drydown period, when spatial structure is less significant. Deterministic reduced-rank Kalman filters can achieve significant computational efficiency by focusing on the leading modes of a system with large-scale spatial structure. But these methods are not well suited for land surface problems with complex uncertain inputs and rapidly changing spectra. Local ensemble Kalman filters are suitable for such problems during dry periods but give less accurate results after rainfall. The most promising option for achieving computational efficiency and accuracy is to develop generalized localization methods that dynamically aggregate states, reflecting structural changes in the ensemble.
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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 (April 10, 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 algorithm is developed under the CFBP framework to deal with the motion error problem for missile-borne SAR application. In the algorithm, spectrum compression is implemented after a CFBP process, and the SAR images are transformed into the spectrum-compressed domain. Then, the analytical image spectrum is obtained by utilizing wavenumber decomposition based on which the property of motion induced error is carefully investigated. With the analytical image spectrum, it is revealed that the echoes from different scattering points are aligned in the same spectrum range and the phase error becomes a spatial invariant component after spectrum compression. Based on the spectrum-compressed domain, an effective and efficient data-driven MOCO algorithm is accordingly developed for accurate error estimation and compensation. Both simulations of missile-borne SAR and raw data experiment from maneuvering highly-squint airborne SAR are provided and analyzed, which show high focusing performance of the proposed algorithm.
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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 (August 7, 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 specific stationarity conditions of the functional processes under study. The practical implications of our work span across fields like environmental monitoring, geosciences, and biomedical research. This overview encourages advancements in functional geostatistics, paving the way for the development of innovative techniques for analyzing and predicting spatially correlated functional data. It lays the groundwork for future research, enhancing our understanding of spatial statistics and its applications.
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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 (June 17, 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 from the size of the investigated area is properly taken into account.
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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 (May 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 method based on exponential weighted mean for weight allocation to facilitate vitality calculations. Using the Wujiaochang UUC in Shanghai as a case study, we explored the spatial distribution mechanism of vitality and validated the feasibility of this research framework. The proposed assessment method and results obtained in this study offer valuable insights into underground space planning and design, particularly in the context of urban renewal.
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Suman, Abdulla Al, Carlo Russo, Ann Carrigan, Patrick Nalepka, Benoit Liquet-Weiland, Robert Ahadizad Newport, Poonam Kumari, and Antonio Di Ieva. "Spatial and time domain analysis of eye-tracking data during screening of brain magnetic resonance images." PLOS ONE 16, no. 12 (December 2, 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 regions of interest for machine vision applications. Method The study was performed using eye-tracking data 5 seconds in duration from 57 readers (15 Brain-experts, 11 Other-experts, 5 Registrars and 26 Naïves) for 40 neuroradiological images as stimuli (i.e., 20 normal and 20 pathological brain MRIs). The visual scanning patterns were analysed by calculating the fractal dimension (FD) and Hurst exponent (HE) using re-scaled range (R/S) and detrended fluctuation analysis (DFA) methods. The FD was used to measure the spatial geometrical complexity of the gaze patterns, and the HE analysis was used to measure participants’ focusing skill. The focusing skill is referred to persistence/anti-persistence of the participants’ gaze on the stimulus over time. Pathological and normal stimuli were analysed separately both at the “First Second” and full “Five Seconds” viewing duration. Results All experts were more focused and a had higher visual search complexity compared to Registrars and Naïves. This was seen in both the pathological and normal stimuli in the first and five second analyses. The Brain-experts subgroup was shown to achieve better focusing skill than Other-experts due to their domain specific expertise. Indeed, the FDs found when viewing pathological stimuli were higher than those in normal ones. Viewing normal stimuli resulted in an increase of FD found in five second data, unlike pathological stimuli, which did not change. In contrast to the FDs, the scanpath HEs of pathological and normal stimuli were similar. However, participants’ gaze was more focused for “Five Seconds” than “First Second” data. Conclusions The HE analysis of the scanpaths belonging to all experts showed that they have greater focus than Registrars and Naïves. This may be related to their higher visual search complexity than non-experts due to their training and expertise.
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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 Karnataka, India. The paper also presents the spatial divergence of Surface Energy Fluxes and Actual Evapotranspiration in correlation with various land use and land cover patterns within the study region. Notably, the ET fraction derived from the SEBAL algorithm demonstrates a commendable correlation with the ET fraction derived from EEFlux (R2= 0.9). As a result, this study highlights the significance of accurately capturing surface energy fluxes and actual evapotranspiration within heterogeneous field conditions in regional scale.
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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 (March 1, 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 researchers have shown that SMF beamforming can provide dynamic transmit–receive focusing throughout the field of view. In this paper, we apply SMF beamforming to plane wave transmissions (PWTs) to achieve both dynamic transmit–receive focusing at all imaging depths and high imaging frame rate (>5000 frames per second). We demonstrated the capability of the combined method (PWT + SMF) of achieving two-way focusing mathematically through analysis based on the narrowband Rayleigh–Sommerfeld diffraction theory. Moreover, the broadband performance of PWT + SMF was quantified in terms of lateral resolution and contrast from both computer simulations and experimental data. Results were compared between SMF beamforming and conventional delay-and-sum (DAS) beamforming in both simulations and experiments. At an imaging depth of 40 mm, simulation results showed a 29% lateral resolution improvement and a 160% contrast improvement with PWT + SMF. These improvements were 17% and 48% for experimental data with noise.
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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 (June 19, 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 analyzed; thirdly, a systematic clustering approach was adopted to carry out a typological analysis of 41 cities in the Yangtze River Delta from three perspectives: industrial structure, time stage and spatial level. It was found that (1) regional differences within the Yangtze River Delta are still significant, but are narrowing; (2) different cities or regions show different characteristics of development stages, and late-developing regions can learn from early developing regions; (3) metropolitan areas are still the main areas of employment concentration, and the spatial distribution of employment in some cities is beginning to suburbanize.
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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 (June 30, 2018): 63–85. http://dx.doi.org/10.14329/isr.2018.20.2.063.
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Wang, Juefu, Mark Ng, and Mike Perz. "Seismic data interpolation by greedy local Radon transform." GEOPHYSICS 75, no. 6 (November 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 iteratively applying spatially localized forward and adjoint Radon operators to fit the input data. Optimal local Radon panels can be found via a subspace algorithm which promotes sparsity in the model, and the missing data can be predicted using the resulting local Radon panels. The subspacing strategy greatly reduces the cost of computing local Radon coefficients, thereby reducing the total cost for inversion. The method can handle irregular and regular geometries and significant spatial aliasing. We compare the performance of our method using three simple synthetic data sets with a popular interpolation method known as minimum weighted norm Fourier interpolation, and show the advantage of the new algorithm in interpolating spatially aliased data. We also test the algorithm on the 2D synthetic data and a field data set. Both tests show that the algorithm is a robust antialiasing tool, although it cannot completely recover missing strongly curved events.
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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 (March 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 principal components analysis and cluster analysis; functional regions are defined by a standard rule-based regionalisation algorithm. The territory of the Czech Republic is used as an area for testing the basic hypotheses. The results show that there is some form of interrelationship and complementarity between the spatial distribution of scalar data and vector data, i.e. between spatial structure and spatial interaction patterns, which together form the spatial organisation of a geographical environment.
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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 (May 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 regression model was fitted to determine individual and community-level factors associated with LBW. Finally, most likely clusters with log-likelihood ratio (LLR), relative risk and p value from spatial scan statistics and adjusted OR (AOR) with 95% CI for multilevel logistic regression model were reported.ResultsLBW was spatially clustered in Ethiopia. Primary (LLR=11.57; p=0.002) clusters were detected in the Amhara region. Neonates within this spatial window had a 2.66 times higher risk of being LBW babies as compared with those outside the window. Besides, secondary (LLR=11.4; p=0.003; LLR=10.14, p=0.0075) clusters were identified at southwest Oromia, north Oromia, south Afar and southeast Amhara regions. Neonates who were born from severely anaemic (AOR=1.40, 95% CI (1.03 to 2.15)), and uneducated (AOR=1.90, 95% CI (1.23 to 2.93)) mothers, those who were born before 37 weeks of gestation (AOR=5.97, 95% CI (3.26 to 10.95)) and women (AOR=1.41, 95% CI (1.05 to 1.89)), had significantly higher odds of being LBW babies.ConclusionThe high-risk areas of LBW were detected in Afar, Amhara and Oromia regions. Therefore, targeting the policy interventions in those hotspot areas and focusing on the improvement of maternal education, strengthening anaemia control programmes and elimination of modifiable causes of prematurity could be vital for reducing the LBW disparity in Ethiopia.
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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 (March 19, 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 years (376 studies) focusing on the considered scales in the studies. We show that the majority of medical studies are restricted to certain geographical regions. It is desirable that the number of studies be adapted to the number of the respective population. On the basis of these studies, we develop a framework to investigate the relationship between space and health. Finally, we apply our methodology to investigate the relationship between the prevalence of slums and different health metrics using data of the global burden of diseases for different prefectures in Brazil on a subnational level.
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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 (October 17, 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 were collected to demonstrate existing spatial patterns and infrastructure connectivity. Exploratory spatial data analysis and focal statistics analysis were central in the data processing. The findings reveal that cycling activities are separated from urban public transport infrastructure, and the city of Johannesburg’s transport system is characterized by spatially fragmented commuting and cycling operations, with limited to no sharing of infrastructure. Most public transport stations are not easily accessible for non-motorized transport and are characterized by inadequate cycling facilities. In conclusion, the identification of an urban public transportation catchment area becomes essential for developing cities such as Johannesburg. This can be used as tool for planning infrastructural upgrades and forecasting potential public transport ridership while also assessing the impacts of investments in transit planning. There is thus a need to integrate motorized urban public transport and cycling infrastructural developments toward promoting multi-mobility and infrastructure sharing.
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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 (January 18, 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 patterns by focusing on the restaurants of the eight most famous cuisines in Mainland China. Initially, the density based geospatial hotspot detector method is proposed to analyze and mapping the spatial quantitative characteristics of the eight major cuisines. A heuristic method for geographical regionalization based on machine learning was used to analyze spatial distribution patterns in accordance with the proportion of these cuisines in each prefecture-level city. Results show that some types of single-category cuisines have a stronger spatial concentration effect in the present, whereas others have a strong diffusion trend. In the comprehensive analysis of multicategory cuisines, the eight major cuisines formed a new structure of geographical regionalization of Chinese cuisine culture. This study is helpful to understand regional structure characteristics of food preference, and the density-based hotspot detector proposed in this paper can also be used in the analysis of other type of point of interest (POI) data.
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Rendra, Meldi, and Estananto Estananto. "SPATIAL PLANNING IN SUPPORTING VILLAGE DEVELOPMENT." Charity 6, no. 1a (March 27, 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 19 at Langensari-Lembang, Indonesia, found a method of static to dynamic, aggregated to disaggregated, and macro to micro. The results can visualize planning support in general solutions to specific adjustments of some public goods. Covid 19- suitable indicator schemes can design in isolated areas. Targets are how population aggregation and household mobilities in rural areas are affected by these planning policies. We believe action research improvements will employ a practical future on big data and artificial intelligence.
Keyword: Spatial Planning, GIS, Decision Making
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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 (January 1, 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 a single statistic (μ); μ is significantly correlated with the fractal dimension of fish distribution. It is argued that the Lévy statistic is a good candidate for an ecosystem indicator that might contribute to real-time monitoring of ecosystems.
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Fu, Yongqi, Chunlei Du, Wei Zhou, and Lennie Enk Ng Lim. "Nanopinholes-Based Optical Superlens." Research Letters in Physics 2008 (February 13, 2008): 1–5. http://dx.doi.org/10.1155/2008/148505.
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A type of nanopinhole-based plasmonic structure is presented. It can realize superfocusing within micron-scale propagation distance with spatial resolution beyond diffraction limit. Cut-off wavelength effect is highlighted for understanding how periodicity distribution of the nanopinholes influences transmission and focusing through the structure. Redshift peak transmission occurs while the periodicity increases. In addition, focusing property of the plasmonic structures is analyzed for the monochromatic illumination with different incident wavelengths ranging from 400 nm to 750 nm. The easy fabrication and high focusing performance of the proposed structures may be used in data storage devices, bioimaging, and nanolithography.
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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 (December 31, 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 the selected cases, comparing spaces before and after remodeling, and investigating five elements of spatial resilience in the remodeled spacesThis case analysis is expected to yield significant data, providing a theoretical foundation for remodeling methods to enhance spatial resilience in aging spaces in the future.
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Li, Meng-Lin, and Pai-Chi Li. "Improved Fourier-Transform-Based Parallel Receive Beam Formation." Ultrasonic Imaging 25, no. 2 (April 2003): 73–84. http://dx.doi.org/10.1177/016173460302500201.
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A Fourier transform (FT)-based technique for forming parallel receive beams has been previously employed to increase the imaging frame rate in ultrasonic imaging. However, the image quality in FT-based parallel reconstruction is degraded because differences in range focusing delays are ignored and a wide transmit beam needs to be used. In this paper, an adaptive weighting technique based on a focusing-quality index is used to reduce the sidelobes of the FT-derived parallel receive beams. The focusing-quality index is derived from the spatial spectrum of the received aperture data after the receive delays have been applied. Since the spatial spectrum of the baseband aperture data is also used to approximate receive beams in FT-based parallel reconstruction, the adaptive weighting technique can be directly combined with the FT-based technique for forming parallel receive beams with only a slight increase in system complexity. Real ultrasound data are used to demonstrate the efficacy of the proposed technique on both wire targets and speckle-generating objects. The results clearly demonstrate the effectiveness in reducing the sidelobes. In addition, the image background noise is suppressed. The principles, experimental results, and the extension of the proposed technique to 3D ultrasound imaging are described in this paper.
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Lin, ChungYi, Shen-Lung Tung, Hung-Ting Su, and Winston H. Hsu. "TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (March 24, 2024): 22927–33. http://dx.doi.org/10.1609/aaai.v38i21.30331.
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To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns. Our extensive analysis validates its potential for transportation. Focusing on vehicle-related GCT flow prediction, we propose a graph neural network that integrates multivariate, temporal, and spatial facets for improved accuracy. Experiments reveal our model's superiority over baselines, especially in long-term predictions. We also highlight the potential for GCT flow integration into transportation systems.
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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 (February 15, 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 based on geometric transformation and rendering optimization, focusing more on the data compression and visual quality of the model, which essentially does not change the data structure of the BIM model, and it is difficult to establish the mapping relationship between spatial location and spatial data, information, and resources. In addition, current coding methods proposed for BIM models are mostly based on the line classification method, which realizes the identification of components based on the classification of their attributes, and the location information is stored according to the attributes or natural language descriptions, which need to be parsed and translated when they are used, and this procedure ignores the importance of spatial location in daily management and emergency management. The importance of spatial location in daily management and emergency management is also ignored. Based on this kind of identification code, it is impossible to directly analyze and apply spatial location data. Therefore, this paper takes the combination of GIS technology and BIM technology as the starting point and proposes a BIM data modeling method based on the BeiDou grid code, based on the efficiency of its underlying data organization and the accuracy of its real geographic location expression on the one hand and the completeness of the information expression by BIM and fine three-dimensional visualization on the other hand. Finally, a series of experiments are carried out based on the method. Through visualization modeling and efficiency experiments, different feature models are meshed to verify the feasibility and efficiency of the model. Through coding and information query experiments, the model′s data organization capability, data dynamic carrying capability, and efficient spatial computation capability and practical application capability are verified.
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Lucek, Stephen. "Metaphor variation of spatial conceptualizations in Irish English." Metaphor Variation in Englishes around the World 4, no. 1 (September 22, 2017): 36–62. http://dx.doi.org/10.1075/cogls.4.1.03luc.
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Abstract The current paper offers a novel methodological approach to gathering rich spatial data from Irish English speakers, showing variation in the cognition of physical and conceptual space. A mixed method study was conducted to gather conceptual and sociolinguistic data. This includes the first part of the data gathering: a structured interview, focusing on geographic aspects of the town and two wayfinding exercises. I then describe the second part of the study: twenty cloze procedure questions relating to a written example, followed by questions relating to seventeen hand-drawn images. I take as a baseline the instruments used by, inter alia, Levinson and Wilkins (2006a) and apply them to a within-culture study. I conclude this paper by discussing replicability and future studies. While Conceptual Metaphor Theory (CMT) offers researchers a model to connect physical and conceptual elements of space, we have not seen a large-scale study of how CMT affects the language of space in varieties of English.
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Choi, HaeOk. "Geospatial Data Approach for Demand-Oriented Policies of Land Administration." Land 9, no. 1 (January 20, 2020): 31. http://dx.doi.org/10.3390/land9010031.
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To develop the land administration sector, it is important to examine the difficulties faced and requests made by citizens. Accordingly, this study analyzes the Voice of Citizens data relating to land administration in an attempt to identify characteristics of civil complaints in the spatial sector that are unique to land administration. This research builds geospatial Database by combining civil complaint data and spatial information to the analysis of interest of the civil complaint area in order to identify the major keywords on the map. The analysis reveals that civil complaints relating to land administration pertain mostly to the operational methods and services of institutions in charge of the civil complaints, rather than to the ownership and results of land administration. These results indicate that response and operational methods must be determined prior to the administrative process relating to land ownership. This study further confirms that the civil complaints relating to ownership generally arose out of the mountainous and coastal regions, rather than cities. Going forward, this study could be used as reference material for determining policy priorities focusing, in particular, on the policy consumers’ utilizing data on civil complaints in terms of government policy.
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Yoccoz, N. G., and R. A. Ims. "Spatial population dynamics of small mammals: some methodological and practical issues." Animal Biodiversity and Conservation 27, no. 1 (June 1, 2004): 427–35. http://dx.doi.org/10.32800/abc.2004.27.0427.
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Small mammals have been widely used to further our understanding of spatial and temporal population dynamical patterns, because their dynamics exhibit large variations, both in time (multi-annual cycles vs. seasonal variation only) and space (regional synchrony, travelling waves). Small mammals have therefore been the focus of a large number of empirical and statistical (analysis of time-series) studies, mostly based on trapping indices. These studies did not take into account sampling variability associated with the use of counts or estimates of population size. In this paper, we use our field study focusing on population dynamics and demography of small mammals in North Norway at three spatial scales (0.1, 10 and 100 km) to illustrate some methodological and practical issues. We first investigate the empirical patterns of spatial population dynamics, focusing on correlation among time-series of population abundance at increasing spatial scales. We then assess using simulated data the bias of estimates of spatial correlation induced by using either population indices such as the number of individuals captured (i.e., raw counts) or estimates of population size derived from statistical modeling of capture-recapture data. The problems encountered are similar to those described when assessing density-dependence in time-series -a special case of the consequence of measurement error for estimates of regression coefficients- but are to our knowledge ignored in the ecological literature. We suggest some empirical solutions as well as more rigorous approaches.
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Le Clainche, Soledad, and José M. Vega. "Analyzing Nonlinear Dynamics via Data-Driven Dynamic Mode Decomposition-Like Methods." Complexity 2018 (December 12, 2018): 1–21. http://dx.doi.org/10.1155/2018/6920783.
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This article presents a review on two methods based on dynamic mode decomposition and its multiple applications, focusing on higher order dynamic mode decomposition (which provides a purely temporal Fourier-like decomposition) and spatiotemporal Koopman decomposition (which gives a spatiotemporal Fourier-like decomposition). These methods are purely data-driven, using either numerical or experimental data, and permit reconstructing the given data and identifying the temporal growth rates and frequencies involved in the dynamics and the spatial growth rates and wavenumbers in the case of the spatiotemporal Koopman decomposition. Thus, they may be used to either identify and extrapolate the dynamics from transient behavior to permanent dynamics or construct efficient, purely data-driven reduced order models.
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Amaghouss, Jabrane, and Aoamar Ibourk. "Toward a spatial approach for convergence." International Journal of Development Issues 19, no. 2 (May 6, 2020): 187–204. http://dx.doi.org/10.1108/ijdi-07-2019-0131.
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Purpose In recent years, there is growing recognition of the importance of geography and space in the analysis of economic convergence by focusing on the dynamics of monetary indicators. The analysis of spatial convergence based on socio-economic indicators are rare. These variables present a complement to understand the spatial dynamics of territorial units. The purpose of this paper is, first, to analyzes and describes trends in multidimensional poverty in Morocco and second it explores the convergence hypothesis. Design/methodology/approach Data are driven from HCP (2017). It concerns 75 provinces over the period 2004 and 2014. In addition to the availability of data, this period corresponds to significant changes in public policy. The nature of the observations necessitates the use of the spatial analysis techniques. Findings The results show that poverty is a geographical phenomenon with low speed of convergence. The paper propose some solutions to help policymakers implement an effective targeting policy aimed at reducing spatial inequalities in terms of multidimensional poverty in Morocco. Originality/value The analysis of spatial convergence based on socio-economic indicators are rare. This paper will focus on the convergence of the poverty index for a developing country.
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Lanzer, Jan D., Florian Leuschner, Rafael Kramann, Rebecca T. Levinson, and Julio Saez-Rodriguez. "Big Data Approaches in Heart Failure Research." Current Heart Failure Reports 17, no. 5 (August 12, 2020): 213–24. http://dx.doi.org/10.1007/s11897-020-00469-9.
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Abstract Purpose of Review The goal of this review is to summarize the state of big data analyses in the study of heart failure (HF). We discuss the use of big data in the HF space, focusing on “omics” and clinical data. We address some limitations of this data, as well as their future potential. Recent Findings Omics are providing insight into plasmal and myocardial molecular profiles in HF patients. The introduction of single cell and spatial technologies is a major advance that will reshape our understanding of cell heterogeneity and function as well as tissue architecture. Clinical data analysis focuses on HF phenotyping and prognostic modeling. Summary Big data approaches are increasingly common in HF research. The use of methods designed for big data, such as machine learning, may help elucidate the biology underlying HF. However, important challenges remain in the translation of this knowledge into improvements in clinical care.
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Masse, Nicolas Y., Todd M. Herrington, and Erik P. Cook. "Spatial attention enhances the selective integration of activity from area MT." Journal of Neurophysiology 108, no. 6 (September 15, 2012): 1594–606. http://dx.doi.org/10.1152/jn.00949.2011.
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Distinguishing which of the many proposed neural mechanisms of spatial attention actually underlies behavioral improvements in visually guided tasks has been difficult. One attractive hypothesis is that attention allows downstream neural circuits to selectively integrate responses from the most informative sensory neurons. This would allow behavioral performance to be based on the highest-quality signals available in visual cortex. We examined this hypothesis by asking how spatial attention affects both the stimulus sensitivity of middle temporal (MT) neurons and their corresponding correlation with behavior. Analyzing a data set pooled from two experiments involving four monkeys, we found that spatial attention did not appreciably affect either the stimulus sensitivity of the neurons or the correlation between their activity and behavior. However, for those sessions in which there was a robust behavioral effect of attention, focusing attention inside the neuron's receptive field significantly increased the correlation between these two metrics, an indication of selective integration. These results suggest that, similar to mechanisms proposed for the neural basis of perceptual learning, the behavioral benefits of focusing spatial attention are attributable to selective integration of neural activity from visual cortical areas by their downstream targets.
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Liu, Jun Ping, Fei Long Dong, and Jia Wei Shao. "Information Management of Maritime Work Based on GIS." Applied Mechanics and Materials 580-583 (July 2014): 2774–77. http://dx.doi.org/10.4028/www.scientific.net/amm.580-583.2774.
Full textAbstract:
Seawall is an important barrier of Zhejiang coastal strip. To effectively manage the information of maritime work in Zhejiang and convert the traditional management into the modern management, the information management system of maritime work based on GIS is developed. Take Kaomen seawall for example, the overall structure of information management system based on GIS is designed, focusing on the data entry, spatial attribute show, spatial attribute query, spatial information statistics and analysis. This design plays a significant role in the flood control and disaster reduction in the future, making the information management of maritime work convenient and practical.
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Peng, Haorui, Ivan Vasconcelos, Yanadet Sripanich, and Lele Zhang. "An analysis of acquisition-related subsampling effects on Marchenko focusing, redatuming, and primary estimation." GEOPHYSICS 86, no. 5 (September 1, 2021): WC75—WC88. http://dx.doi.org/10.1190/geo2020-0914.1.
Full textAbstract:
Marchenko methods can retrieve Green’s functions and focusing functions from single-sided reflection data and a smooth velocity model, as essential components of a redatuming process. Recent studies also indicate that a modified Marchenko scheme can reconstruct primary-only reflection responses directly from reflection data without requiring a priori model information. To provide insight into the artifacts that arise when input data are not ideally sampled, we study the effects of subsampling in both types of Marchenko methods in 2D earth and data — by analyzing the behavior of Marchenko-based results on synthetic data subsampled in sources or receivers. With a layered model, we find that for Marchenko redatuming, subsampling effects jointly depend on the choice of integration variable and the subsampling dimension, originated from the integrand gather in the multidimensional convolution process. When reflection data are subsampled in a single dimension, integrating on the other yields spatial gaps together with artifacts, whereas integrating on the subsampled dimension produces aliasing artifacts but without spatial gaps. Our complex subsalt model indicates that the subsampling may lead to very strong artifacts, which can be further complicated by having limited apertures. For Marchenko-based primary estimation (MPE), subsampling below a certain fraction of the fully sampled data can cause MPE iterations to diverge, which can be mitigated to some extent by using more robust iterative solvers, such as least-squares QR. Our results, covering redatuming and primary estimation in a range of subsampling scenarios, provide insights that can inform acquisition sampling choices as well as processing parameterization and quality control, e.g., to set up appropriate data filters and scaling to accommodate the effects of dipole fields, or to help ensuring that the data interpolation achieves the desired levels of reconstruction quality that minimize subsampling artifacts in Marchenko-derived fields and images.
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Czepkiewicz, Michał, Piotr Jankowski, and Zbigniew Zwoliński. "Geo-Questionnaire: A Spatially Explicit Method for Eliciting Public Preferences, Behavioural Patterns, and Local Knowledge – An Overview." Quaestiones Geographicae 37, no. 3 (September 6, 2018): 177–90. http://dx.doi.org/10.2478/quageo-2018-0033.
Full textAbstract:
Abstract Geo-questionnaires have been used in a variety of domains to collect public preferences, behavioural patterns, and spatially-explicit local knowledge, for academic research and environmental and urban planning. This paper provides an overview of the method focusing on the methodical characteristics of geo-questionnaires including software functions, types of collected data, and techniques of data analysis. The paper also discusses broader methodical issues related to the practice of deploying geo-questionnaires such as respondent selection and recruitment, representativeness, and data quality. The discussion of methodical issues is followed by an overview of the recent examples of geo-questionnaire applications in Poland, and the discussion of socio-technical aspects of geo-questionnaire use in spatial planning.