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Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications
The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and...
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Lenguaje: | eng |
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Springer
2012
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Acceso en línea: | https://dx.doi.org/10.1007/978-94-007-4075-4 http://cds.cern.ch/record/1501913 |
_version_ | 1780927088605265920 |
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author | Lakshmanan, Valliappa |
author_facet | Lakshmanan, Valliappa |
author_sort | Lakshmanan, Valliappa |
collection | CERN |
description | The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery. |
id | cern-1501913 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2012 |
publisher | Springer |
record_format | invenio |
spelling | cern-15019132021-04-21T23:55:14Zdoi:10.1007/978-94-007-4075-4http://cds.cern.ch/record/1501913engLakshmanan, ValliappaAutomating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental ApplicationsEngineeringThe ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.Springeroai:cds.cern.ch:15019132012 |
spellingShingle | Engineering Lakshmanan, Valliappa Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title | Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title_full | Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title_fullStr | Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title_full_unstemmed | Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title_short | Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications |
title_sort | automating the analysis of spatial grids: a practical guide to data mining geospatial images for human & environmental applications |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-94-007-4075-4 http://cds.cern.ch/record/1501913 |
work_keys_str_mv | AT lakshmananvalliappa automatingtheanalysisofspatialgridsapracticalguidetodatamininggeospatialimagesforhumanenvironmentalapplications |