Relevant bibliographies by topics / Vector and Raster Data

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Vector and Raster Data'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Vector and Raster Data"

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Zhou, G., Q. Pan, T. Yue, Q. Wang, H. Sha, S. Huang, and X. Liu. "VECTOR AND RASTER DATA STORAGE BASED ON MORTON CODE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (May 2, 2018): 2523–26. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2523-2018.

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Even though geomatique is so developed nowadays, the integration of spatial data in vector and raster formats is still a very tricky problem in geographic information system environment. And there is still not a proper way to solve the problem. This article proposes a method to interpret vector data and raster data. In this paper, we saved the image data and building vector data of Guilin University of Technology to Oracle database. Then we use ADO interface to connect database to Visual C++ and convert row and column numbers of raster data and X Y of vector data to Morton code in Visual C++ environment. This method stores vector and raster data to Oracle Database and uses Morton code instead of row and column and X Y to mark the position information of vector and raster data. Using Morton code to mark geographic information enables storage of data make full use of storage space, simultaneous analysis of vector and raster data more efficient and visualization of vector and raster more intuitive. This method is very helpful for some situations that need to analyse or display vector data and raster data at the same time.
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Brisaboa, Nieves R., Guillermo de Bernardo, Gilberto Gutiérrez, Miguel R. Luaces, and José R. Paramá. "Efficiently Querying Vector and Raster Data." Computer Journal 60, no. 9 (February 15, 2017): 1395–413. http://dx.doi.org/10.1093/comjnl/bxx011.

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Huang, Y. S., G. Q. Zhou, T. Yue, H. B. Yan, W. X. Zhang, X. Bao, Q. Y. Pan, and J. S. Ni. "VECTOR AND RASTER DATA LAYERED FUSION AND 3D VISUALIZATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 8, 2020): 1127–34. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-1127-2020.

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Abstract. Although contemporary geospatial science has made great progress, spatial data fusion of vector and raster data is still a problem in the geoinformation science environment. In order to solve the problem, this paper proposes a method which merges vector and raster data. Firstly, the row and column numbers of the raster data, and the X, Y values of the vector data are represented by Morton code in the C++ environment, respectively. Secondly, we establish the the raster data table and the vector data table in the Oracle database to store the vector data and the raster data. Third, this paper uses the minimum selection bounding box method to extract the top data of the building model. Finally, we divide the vector and raster data into four steps to obtain the fusion data table, and we call the fusion data in the database for 3D visualization. This method compresses the size of data of the original data, and simultaneously divides the data into three levels, which not only solves the problem of data duplication storage and unorganized storage, but also can realize vector data storage and the raster data storage in the same database at the same time. Thus, the fusion original orthophoto data contains the gray values of building roofs and the elevation data, which can improve the availability of vector data and the raster data in the 3D Visualization application.
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Yu, Hui Ming, Jian Zhong Guo, Yi Cheng, and Qian Lou. "Techniques and Methods of Spatial Data Fusion." Applied Mechanics and Materials 263-266 (December 2012): 3274–78. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.3274.

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Spatial data fusion is an important method of spatial data acquisition. The aim of multisource spatial data integration and fusion is to improve the information precision and information's utilization efficiency. Vector and raster are the two main spatial data structures. This article discusses vector data fusion from of data model fusion, semantic information fusion and coordinates unification, reviews the main methods of raster data fusion and discusses the key technologies of vector and raster data fusion, and proposes the future developments of spatial data fusion technique.
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Aljumaily, Harith, Debra F. Laefer, and Dolores Cuadra. "VECTOR-RASTER DATA FUSION FOR OBJECT EXTRACTION." Advances in Computer Science and Engineering 15, no. 1-2 (April 14, 2016): 13–26. http://dx.doi.org/10.17654/cs015120013.

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Silva-Coira, Fernando, José R. Paramá, Susana Ladra, Juan R. López, and Gilberto Gutiérrez. "Efficient processing of raster and vector data." PLOS ONE 15, no. 1 (January 10, 2020): e0226943. http://dx.doi.org/10.1371/journal.pone.0226943.

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Pan, J. P., Q. L. Xu, and C. H. Yang. "Research and Application of GIS Data Update Technology." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4 (April 23, 2014): 195–200. http://dx.doi.org/10.5194/isprsarchives-xl-4-195-2014.

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This paper summed up 3 kinds of GIS data update ways started from the actual production, as these data are raster to raster data, raster to vector data and vector to vector data. We described the most advanced and most effective ways to update each kind of data, solved lots of insufficient exist in current GIS data update ways effectively, such as long update time, low update efficiency, data redundancy and can’t query and analysis based on time. From the actual production project, those ways we described were proven to be effective and feasible.
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Moehl, J. J., E. M. Weber, and J. J. McKee. "A VECTOR ANALYTICAL FRAMEWORK FOR POPULATION MODELING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W2-2021 (August 19, 2021): 103–8. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w2-2021-103-2021.

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Abstract. We propose a vector alternative to the typical raster based population modeling framework. When compared with rasters, vectors are more precise, have the ability to hold more information, and are more conducive to areal constructs such as building and parcel outlines. While rasters have traditionally provided computational efficiency, much of this efficiency is reduced at finer resolutions and computational resources are more plentiful today. Herein we describe the approach and implementation methodology. We also describe the output data stack for the United States and provide examples and applications.
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Ayliffe, A. C. "Raster Digitized Mapping For The Royal Air Force." Journal of Navigation 49, no. 2 (May 1996): 143–53. http://dx.doi.org/10.1017/s0373463300013230.

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In a paper delivered to Geo '89, a NATO symposium, Wing Commander G. T. Scard was tempted to summarize RAF requirements for digital geographic information as ‘raster now, vector later’.1 He avoided that temptation. However, it is still easy to assume that supplying raster data is today's quick solution to the problem of providing geographic information, and that soon raster products will be replaced by a new generation of vector products. Six years on, raster digitized mapping is becoming firmly established as a major geographic information product supplied by the Military Survey Defence Agency. Although vector data is becoming widely available, there are no defined RAF requirements to procure map displays based on vector products. It is apparent that raster data will remain an important source of displayed geographic information on which the RAF will rely for a long time. However, supplying raster mapping is not easy. There are technical problems which need further work to find solutions. This work is urgent. Systems using raster data are already in service and we cannot wait for vector data to replace raster data at some unspecified future date.
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Karim, H., A. Abdul Rahman, and M. R. Mohd Salleh. "MULTI-SCALE AND SCALE DIMENSION PROPERTIES IN SPATIAL RASTER MODELLING – CONCEPT AND CURRENT IMPLEMENTATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 339–45. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-339-2019.

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Abstract. Various users and applications required different abstraction details of spatial model either in vector or/and raster data types/models. Generating different model abstraction details (e.g. Level of Detail/LOD) produces various drawbacks especially for data model sharing among stakeholders or publics. Different abstraction detail or LOD means different details in geometry, semantic information, attributes as well as different accuracy provided within the vector model (e.g. a certain LOD). On the other hand, raster dataset with different resolutions on certain information or layer (e.g. elevation, land cover, spatial imagery, soil type, thematic raster map and others) could also be considered as multi-scale raster modelling which produces similar drawbacks with additional storage redundancy/consumption and updating works. There are some solutions for vector scale modelling such as CityGML (3D) and multi-scale or vario-scale (2D) modelling induce good solutions for vector; however, there are no solution for raster data type (or model) yet. Thus, a concept description in categorizing and defining multi-scale for multi-resolution raster dataset should be introduced. This paper basically highlights the similarity of spatial 2D vector and raster type GIS dataset, some introduction and properties of raster dataset which able to be defined it as the same level of vector LoD in scale modelling. This paper basically tries to kick off a new multi-scale domain in supporting spatial raster dataset (new idea), which will be then be extend/expand by related researchers near the future. Discussion on successful implementation of vector multi-scale model will be in the paper as well as existing multi-scale approach in storing raster dataset as the main content of the paper. Some potential analysis on related multi-scale raster and validation are also discussed to give brief idea on what is spatial raster capable of; especially to those who are new/not yet engage with this multi-scale spatial raster dataset.
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Dissertations / Theses on the topic "Vector and Raster Data"

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Wu, Ying. "COTS GIS integration and its SOAP-based web services." ScholarWorks@UNO, 2004. http://louisdl.louislibraries.org/u?/NOD,99.

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Thesis (M.S.)--University of New Orleans, 2004.
Title from electronic submission form. "A thesis ... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Computer Science."--Thesis t.p. Vita. Includes bibliographical references.
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Wang, Huan. "A Large-scale Dynamic Vector and Raster Data Visualization Geographic Information System Based on Parallel Map Tiling." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/550.

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With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.
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Magalhães, Karina Mochetti de 1982. "Uma alternativa publica para o metodo de marcas d'agua Raster em mapas vetoriais (RAWVec)." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276159.

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Orientador: Ricardo Dahab
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação
Made available in DSpace on 2018-08-13T10:53:28Z (GMT). No. of bitstreams: 1 Magalhaes_KarinaMochettide_M.pdf: 3703797 bytes, checksum: 931cd070eb909803435fa87f05e0f83c (MD5) Previous issue date: 2009
Resumo: Marcas d'água vem sendo utilizadas em vários tipos de arquivos de multimídia, como áudio, vídeo e imagens de bitmap, para combater sua copia e distribuição ilegais. Somente com a popularização dos Sistemas de Informação Geográfica (GIS) e da utilização de dados espaciais na Web, marcas d'água para mapas vetoriais ganharam maior atenção, principalmente porque este tipo de imagem possui produção cara, mas pode ser reproduzido facilmente. Esse trabalho revisa o método RAWVec, que insere uma marca d'água representada por uma imagem raster ou bitmap num mapa vetorial, e apresenta uma alternativa publica para tal método.
Abstract: Watermarks have been used for a long time in several digital media to avoid the illegal copy and distribution of these items. Only with the popularization of Geographic Information Systems (GIS) and the use of spatial data on the Web, watermarks for vector maps gained more attention, mostly because vector maps are expensive to produce, but easy to copy. This work reviews the RAWVec Method that embeds a watermark, in the form of a bitmap image, into digital vector maps; and presents a semi-blind alternative method.
Mestrado
Mestre em Ciência da Computação
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Klusoňová, Pavla. "GIS obce Dolní Újezd." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2014. http://www.nusl.cz/ntk/nusl-227078.

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The thesis deals with geographical information systems ( GIS) which are nowadays common tools for use in civil service and local administration. The theoretical part is focused on more detailed characterization of these systems including issues concerning geographical data and data base systems. The description of the particular GIS software solution for the selected village of Dolní Újezd in the application of ArcInfo is the main contain of the practical sections. The creation of spatial analysis is a component of the project with the aim of finding a suitable location for benches for public use. The resulting project called “GIS Dolní Újezd”wil be used by the local council in Dolní Újezd.
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Kelblová, Kristýna. "GIS využití krajiny obce Jinačovice." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2013. http://www.nusl.cz/ntk/nusl-226223.

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This master thesis focuses on the development of the GIS in the Jinačovice municipality, particularly on the land use. The core data used for the research has been gathered by aerial photography since 1950. Other data sources include other types of maps, especially Cadastral map, ZABAGED data and statistical data. An analysis of the Land use has been carried out as well as additional analyses of the area. The research has been conducted specifically for the Jinačovice municipality.
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Armstrong, Curtis A. "Vectorization of Raster Images Using B-Spline Surfaces." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1513.pdf.

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Ilg, Markus. "Digital processing of map data in raster format /." Zürich : Geographisches Institut Eidgenössische Technische Hochschule, 1986. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=7973.

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Siwela, Blessing. "Web-based management of time-series raster data." Master's thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/6441.

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Data discovery and data handling often presents serious challenges to organizations that manage huge archives of raster datasets such as those generated by satellite remote sensing. Satellite remote sensing produces a regular stream of raster datasets used in many applications including environmental and agricultural monitoring. This thesis presents a system architecture for the management of time-series GIS raster datasets. The architecture is then applied in a prototype implementation for a department that uses remote sensing data for agricultural monitoring. The architecture centres on three key components. The first is a metadatabase to hold metadata for the raster datasets, and an interface to manage the metadatabase and facilitate the search and discovery of raster metadata. The design of the metadatabase involved the examination of existing standards for geographic raster metadata and the determination of the metadata elements required for time-series raster data. The second component is an interactive tool for viewing the time-series raster data discovered via the metadatabase. The third component provides basic image analysis functionality typically required by users of time-series raster datasets. A prototype was implemented using open source software and following the Open Geospatial Consortium specifications for web map services (WMS) version 1.3.0. After implementation, an evaluation of the prototype was carried out by the target users from the RRSU (Regional Remote Sensing Unit) to assess the usability, the added value of the prototype and its impact on the work of the users. The evaluation showed that the prototype system was generally well received, since it allowed both the data managers and users of time-series datasets to save significant amounts of time in their work routines and it also offered some raster data analyses that are useful to a wider community of time-series raster data managers.
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Momsen, Eric. "Vector-Vector Patterns for Agricultural Data." Thesis, North Dakota State University, 2013. https://hdl.handle.net/10365/27040.

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Agriculture is increasingly driven by massive data, and some challenges are not covered by existing statistics, machine learning, or data mining techniques. Many crops are characterized not only by yield but also by quality measures, such as sugar content and sugar lost to molasses for sugarbeets. The set of features furthermore contains time series data, such as rainfall and periodic satellite imagery. This study examines the problem of identifying relationships in a complex data set, in which there are vectors (multiple attributes) for both the explanatory and response conditions. This problem can be characterized as a vector-vector pattern mining problem. The proposed algorithm uses one of the vector representations to determine the neighbors of a randomly picked instance, and then tests the randomness of that subset within the other vector representation. Compared to conventional approaches, the vector-vector algorithm shows better performance for distinguishing existing relationships.
National Science Foundation Partnerships for Innovation program Grant No. 1114363
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Pavić, Darko [Verfasser]. "Combining raster- and vector-representations for image and geometry processing applications / Darko Pavić." Aachen : Shaker, 2010. http://d-nb.info/100796734X/34.

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Books on the topic "Vector and Raster Data"

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Paskevich, Valerie F. Conversion of raster image data to vector cartographic data. Reston, VA: U.S. Geological Survey, 1991.

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Kessener, Laurens R. A., Frans J. Peters, and Marloes L. P. van Lierop, eds. Data Structures for Raster Graphics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71071-1.

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Ilg, Markus. Digital processing of map data in raster format. Zürich: Geographisches Institut, Eidgenössische Technische Hochschule, 1986.

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Blelloch, Guy E. Vector models for data-parallel computing. Cambridge, Mass: MIT Press, 1990.

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Monette, Bryan. CanSIS regional soils data in vector format. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Knapp, David. Agriculture Canada central Saskatchewan vector soils data. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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1943-, Gray Robert M., ed. Vector quantization and signal compression. Boston: Kluwer Academic Publishers, 1992.

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J, Gurdak Jason. Estimating prediction uncertainty from geographical information system raster processing: A user's manual for the Raster error propagation tool (REPTool). Reston, Va: U.S. Geological Survey, 2009.

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J, Gurdak Jason. Estimating prediction uncertainty from geographical information system raster processing: A user's manual for the Raster error propagation tool (REPTool). Reston, Va: U.S. Geological Survey, 2009.

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Knapp, David. BOREAS forest cover data layers of the NSA in raster format. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Book chapters on the topic "Vector and Raster Data"

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McInerney, Daniel, and Pieter Kempeneers. "Raster Meets Vector Data." In Open Source Geospatial Tools, 129–39. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01824-9_9.

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Samet, Hanan, Clifford A. Shaffer, and Robert E. Webber. "Using linear quadtrees to store vector data." In Data Structures for Raster Graphics, 91–123. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71071-1_6.

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Chiang, Yao-Yi, and Craig A. Knoblock. "Extracting Road Vector Data from Raster Maps." In Graphics Recognition. Achievements, Challenges, and Evolution, 93–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13728-0_9.

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Chiang, Yao-Yi, and Craig A. Knoblock. "Generating Named Road Vector Data from Raster Maps." In Geographic Information Science, 57–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33024-7_5.

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Sun, Min, Yong Xue, Ai-Nai Ma, and Shan-Jun Mao. "Dynamic Vector and Raster Integrated Data Model Based on Code-Points." In Lecture Notes in Computer Science, 984–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47789-6_104.

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Bowen, B. Archie, and Jianli Liu. "Pattern Classification from Raster Data Using Vector Lenses, Neural Networks and Expert Systems." In Mapping and Spatial Modelling for Navigation, 117–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84215-3_7.

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Homburg, Timo, Steffen Staab, and Daniel Janke. "GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data." In Lecture Notes in Computer Science, 258–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62419-4_15.

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Li, Zhilin, and Haowen Yan. "Transformation in Scale for Continuous Zooming." In Manual of Digital Earth, 279–324. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9915-3_8.

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Abstract This chapter summarizes the theories and methods in continuous zooming for Digital Earth. It introduces the basic concepts of and issues in continuous zooming and transformation in scale (or multiscale transformation). It presents the theories of transformation in scale, including the concepts of multiscale versus variable scale, transformation in the Euclidean space versus the geographical space, and the theoretical foundation for transformation in scale, the Natural Principle. It addresses models for transformations in scale, including space-primary hierarchical models, feature-primary hierarchical models, models of transformation in scale for irregular triangulation networks, and the models for geometric transformation of map data. It also discusses the mathematical solutions to transformations in scale (including upscaling and downscaling) for both raster (numerical and categorical data) and vector (point set data, line data set and area data) data. In addition, some concluding remarks are provided.
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Lim, Hyeeun. "Raster Data." In Encyclopedia of GIS, 949–55. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1080.

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Lim, Hyeeun. "Raster Data." In Encyclopedia of GIS, 1–7. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_1080-2.

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Conference papers on the topic "Vector and Raster Data"

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Gamba, Paolo, Fabio Dell'Acqua, and Gianni Lisini. "Raster to Vector in 2D Urban Data." In 2007 Urban Remote Sensing Joint Event. IEEE, 2007. http://dx.doi.org/10.1109/urs.2007.371821.

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Singla, Samriddhi. "Raptor: Large Scale Processing of Big Raster + Vector Data." In SIGMOD/PODS '21: International Conference on Management of Data. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448016.3450585.

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Singla, Samriddhi, Ahmed Eldawy, Tina Diao, Ayan Mukhopadhyay, and Elia Scudiero. "Experimental Study of Big Raster and Vector Database Systems." In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. http://dx.doi.org/10.1109/icde51399.2021.00231.

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Raffa, Mario, Paola Mercogliano, and Carmela Galdi. "Georeferencing raster maps using vector data: A meteorological application." In 2016 IEEE Metrology for Aerospace (MetroAeroSpace). IEEE, 2016. http://dx.doi.org/10.1109/metroaerospace.2016.7573194.

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Eldawy, Ahmed, Lyuye Niu, David Haynes, and Zhiba Su. "Large Scale Analytics of Vector+Raster Big Spatial Data." In SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3139958.3140042.

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Teng, Junhua, and Fahui Wang. "Improved algorithm for data conversion from raster to vector." In Geoinformatics 2007, edited by Peng Gong and Yongxue Liu. SPIE, 2007. http://dx.doi.org/10.1117/12.764602.

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Singla, Samriddhi, and Ahmed Eldawy. "Distributed zonal statistics of big raster and vector data." In SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3274895.3274985.

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Singla, Samriddhi, and Ahmed Eldawy. "Raptor Zonal Statistics: Fully Distributed Zonal Statistics of Big Raster + Vector Data." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9377907.

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Gutierrez, Gilberto, Susana Ladra, Juan R. Lopez, Jose R. Parama, and Fernando Silva-Coira. "Efficient Processing of top-K Vector-Raster Queries Over Compressed Data." In 2018 Data Compression Conference (DCC). IEEE, 2018. http://dx.doi.org/10.1109/dcc.2018.00063.

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Arocena, J., J. Lozano, M. Quartulli, I. Olaizola, and J. Bermudez. "Linked open data for raster and vector geospatial information processing." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7326961.

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Reports on the topic "Vector and Raster Data"

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Steneker, M., and G. F. Bonham-Carter. Computer Program For Converting Arc - Node Vector Data To Raster Format. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1988. http://dx.doi.org/10.4095/130461.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Harris Corporation Data, MIL-R-28002A (Raster). Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada312283.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Rockwell International Data MIL-R-28O02A (Raster). Fort Belvoir, VA: Defense Technical Information Center, August 1993. http://dx.doi.org/10.21236/ada312284.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Cubic Defense Systems' Data, MIL-R-28002A (Raster). Fort Belvoir, VA: Defense Technical Information Center, August 1993. http://dx.doi.org/10.21236/ada312287.

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Lammers, Gary, and Mel Lammers. Raster Transfer Test Using: Industrial Data Link's Data. MIL-R-28002A (Raster) Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, August 1992. http://dx.doi.org/10.21236/ada312285.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Raster Data Transfer Using: AAI Corporation/O'Neil & Associates' Data, MIL-R-28002A (Raster) Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, November 1992. http://dx.doi.org/10.21236/ada312307.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Raster Transfer Test Using: Raytheon Company's Data MIL-R-28002A (Raster) Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, September 1992. http://dx.doi.org/10.21236/ada312286.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Frontier Engineering's Data. MIL-R-28002A (Raster). Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, April 1993. http://dx.doi.org/10.21236/ada312411.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Rockwell International Data MIL-R-28O02A (Raster) Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, August 1993. http://dx.doi.org/10.21236/ada312525.

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CALS TEST NETWORK WRIGHT-PATTERSON AFB OH. Technical Raster Transfer Using: Harris Corporation's Data MIL-R-28002A (Raster) Quick Short Test Report. Fort Belvoir, VA: Defense Technical Information Center, April 1993. http://dx.doi.org/10.21236/ada312800.

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You might also be interested in the extended bibliographies on the topic 'Vector and Raster Data' for particular source types:
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