Number of the records: 1  

Data mining for geoinformatics

  1. Title statementData mining for geoinformatics : methods and applications / Guido Cervone, Jessica Lin, Nigel Waters, editors
    PublicationNew York : Springer, [2013?]
    Copyright notice date©2014
    Phys.des.1 online zdroj (xi, 166 stran) : ilustrace
    ISBN9781461476696 (online)
    1461476690 (online)
    1461476682
    9781461476689
    Internal Bibliographies/Indexes NoteObsahuje bibliografické odkazy
    ContentsComputation in hyperspectral imagery (HSI) data analysis: role and opportunities / Mark Salvador and Ron Resmini -- Toward understanding tornado formation through spatiotemporal data mining / Amy McGovern, Derek H. Rosendahl, and Rodger A. Brown -- Source term estimation for the 2011 Fukushima nuclear accident / Guido Cervone and Pasquale Franzese -- GIS-based traffic simulation using OSM / Jörg Dallmeyer, Andreas D. Lattner, and Ingo J. Timm -- Evaluation of real-time traffic applications based on data stream mining / Sandra Geisler and Christoph Quix -- Geospatial visual analytics of traffic and weather data for better winter road management / Yuzuru Tanaka [and five others] -- Exploratory visualization of collective mobile objects data using temporal granularity and spatial similarity / Tetsuo Kobayashi and Harvey Miller.
    Another responsib. Cervone, Guido (editor)
    Lin, Jessica (editor)
    Waters, Nigel M. (Nigel Michael), 1950- (editor)
    Subj. Headings dolování dat data mining * geoinformatika geoinformatics
    Form, Genre elektronické knihy electronic books
    Conspect004.4/.6 - Programování. Software
    UDC 004.659 , 004:91 , (0.034.2:08)
    CountryNew York
    Languageangličtina
    Document kindElectronic sources
    URLhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=632499
    book

    book


    The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radiation from the Fukushima nuclear power plant, simulations of traffic data using OpenStreetMap, real time traffic applications of data stream mining, visual analytics of traffic and weather data and the exploratory visualization of collective, mobile objects such as the flocking behavior of wild chickens. This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the areas of data mining and geoscience will also find this book to be a valuable reference.

    Computation in hyperspectral imagery (HSI) data analysis: role and opportunities / Mark Salvador and Ron Resmini -- Toward understanding tornado formation through spatiotemporal data mining / Amy McGovern, Derek H. Rosendahl, and Rodger A. Brown -- Source term estimation for the 2011 Fukushima nuclear accident / Guido Cervone and Pasquale Franzese -- GIS-based traffic simulation using OSM / Jörg Dallmeyer, Andreas D. Lattner, and Ingo J. Timm -- Evaluation of real-time traffic applications based on data stream mining / Sandra Geisler and Christoph Quix -- Geospatial visual analytics of traffic and weather data for better winter road management / Yuzuru Tanaka [and five others] -- Exploratory visualization of collective mobile objects data using temporal granularity and spatial similarity / Tetsuo Kobayashi and Harvey Miller.

Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.