The rise of big spatial data:
This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest researc...
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| Other Authors: | |
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| Format: | Book |
| Language: | English |
| Published: |
Cham, Switzerland
Springer
[2017]
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| Series: | Lecture notes in geoinformation and cartography
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| Subjects: | |
| Summary: | This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. |
| Physical Description: | xxvii, 408 Seiten Illustrationen, Diagramme 25 cm |
| ISBN: | 9783319451220 |
Staff View
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| 520 | |a This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. | ||
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| contents | Application of WEB-GIS for Dissemination and 3D Visualization of Larege-Volume LIDAR Data -- Design and Evaluation of WEBGL-BASED Heat Map Visualization for Big Point Data -- Sparse Big Data Problem: A Case Study of Czech Graffiti Crimes -- Surveying of Open Pit Mine Using Low-Cost Aerial Photogrammetry -- Models for Relocation of Emergency Medical Stations -- The Possibilities of Big GIS Data Processing on the Desktop Computers -- Creating Large Size of Data with Apache Hadoop -- Processing LIDAR Data with Apache Hadoop -- Applicability of Support Vector Machines in Landslide Susceptibility Mapping -- Integration of Heterogeneous Data in the Support of the Forest Protection -- Structural Concept |
| ctrlnum | (OCoLC)985603587 (DE-599)BVBBV047683806 |
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| id | DE-604.BV047683806 |
| illustrated | Illustrated |
| index_date | 2024-07-03T18:56:26Z |
| indexdate | 2024-07-10T09:19:09Z |
| institution | BVB |
| isbn | 9783319451220 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033067838 |
| oclc_num | 985603587 |
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| owner_facet | DE-1050 |
| physical | xxvii, 408 Seiten Illustrationen, Diagramme 25 cm |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Springer |
| record_format | marc |
| series2 | Lecture notes in geoinformation and cartography |
| spelling | The rise of big spatial data Igor Ivan [and three others], editors Cham, Switzerland Springer [2017] xxvii, 408 Seiten Illustrationen, Diagramme 25 cm txt rdacontent n rdamedia nc rdacarrier Lecture notes in geoinformation and cartography Application of WEB-GIS for Dissemination and 3D Visualization of Larege-Volume LIDAR Data -- Design and Evaluation of WEBGL-BASED Heat Map Visualization for Big Point Data -- Sparse Big Data Problem: A Case Study of Czech Graffiti Crimes -- Surveying of Open Pit Mine Using Low-Cost Aerial Photogrammetry -- Models for Relocation of Emergency Medical Stations -- The Possibilities of Big GIS Data Processing on the Desktop Computers -- Creating Large Size of Data with Apache Hadoop -- Processing LIDAR Data with Apache Hadoop -- Applicability of Support Vector Machines in Landslide Susceptibility Mapping -- Integration of Heterogeneous Data in the Support of the Forest Protection -- Structural Concept This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. Geographic information systems Big data Geospatial data Big data fast Geographic information systems fast Geospatial data fast Geoinformationssystem gnd Geoinformation gnd Geoinformatik gnd Big Data gnd Data Mining gnd Ivan, Igor edt Erscheint auch als Online-Ausgabe 978-3-319-45123-7 |
| spellingShingle | The rise of big spatial data Application of WEB-GIS for Dissemination and 3D Visualization of Larege-Volume LIDAR Data -- Design and Evaluation of WEBGL-BASED Heat Map Visualization for Big Point Data -- Sparse Big Data Problem: A Case Study of Czech Graffiti Crimes -- Surveying of Open Pit Mine Using Low-Cost Aerial Photogrammetry -- Models for Relocation of Emergency Medical Stations -- The Possibilities of Big GIS Data Processing on the Desktop Computers -- Creating Large Size of Data with Apache Hadoop -- Processing LIDAR Data with Apache Hadoop -- Applicability of Support Vector Machines in Landslide Susceptibility Mapping -- Integration of Heterogeneous Data in the Support of the Forest Protection -- Structural Concept Geographic information systems Big data Geospatial data Big data fast Geographic information systems fast Geospatial data fast Geoinformationssystem gnd Geoinformation gnd Geoinformatik gnd Big Data gnd Data Mining gnd |
| title | The rise of big spatial data |
| title_auth | The rise of big spatial data |
| title_exact_search | The rise of big spatial data |
| title_exact_search_txtP | The rise of big spatial data |
| title_full | The rise of big spatial data Igor Ivan [and three others], editors |
| title_fullStr | The rise of big spatial data Igor Ivan [and three others], editors |
| title_full_unstemmed | The rise of big spatial data Igor Ivan [and three others], editors |
| title_short | The rise of big spatial data |
| title_sort | the rise of big spatial data |
| topic | Geographic information systems Big data Geospatial data Big data fast Geographic information systems fast Geospatial data fast Geoinformationssystem gnd Geoinformation gnd Geoinformatik gnd Big Data gnd Data Mining gnd |
| topic_facet | Geographic information systems Big data Geospatial data Geoinformationssystem Geoinformation Geoinformatik Big Data Data Mining |
| work_keys_str_mv | AT ivanigor theriseofbigspatialdata |