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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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Detalles Bibliográficos
Autor principal: Lakshmanan, Valliappa
Lenguaje:eng
Publicado: Springer 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-94-007-4075-4
http://cds.cern.ch/record/1501913
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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.
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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