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Aggiungi al carrelloHardcover. Condizione: Brand New. 2015 edition. 68 pages. 9.00x6.00x0.25 inches. In Stock.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery | Nasrin Nasrollahi | Taschenbuch | xxi | Englisch | 2016 | Springer | EAN 9783319363325 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer International Publishing, 2014
ISBN 10: 3319120808 ISBN 13: 9783319120805
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 106,99
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed 'big data.' The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
Da: Revaluation Books, Exeter, Regno Unito
EUR 152,11
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Aggiungi al carrelloPaperback. Condizione: Brand New. reprint edition. 92 pages. 9.25x6.10x0.22 inches. In Stock.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Springer, 2016
ISBN 10: 3319363328 ISBN 13: 9783319363325
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 109,94
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed 'big data.' The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
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Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Condizione: As New. Unread book in perfect condition.
Editore: Springer 978-3-319-12080-5, Cham
ISBN 10: 3319120808 ISBN 13: 9783319120805
Da: Burton Lysecki Books, ABAC/ILAB, Winnipeg, MB, Canada
EUR 109,23
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Aggiungi al carrello[978-3-319-12080-5] 2015. (Hardcover) Fine, no dust jacket. 68pp. Black & white and color illustrations, tables, formulas, references. Publisher series: Springer Theses Recognizing Outstanding PH.D Research. (Science, Earth Sciences, Science).
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing Nov 2014, 2014
ISBN 10: 3319120808 ISBN 13: 9783319120805
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 106,99
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed 'big data.' The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation. 92 pp. Englisch.
Lingua: Inglese
Editore: Berlin Springer International Publishing Springer Sep 2016, 2016
ISBN 10: 3319363328 ISBN 13: 9783319363325
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 106,99
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed 'big data.' The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation. 68 pp. Englisch.
Lingua: Inglese
Editore: Springer International Publishing, 2014
ISBN 10: 3319120808 ISBN 13: 9783319120805
Da: moluna, Greven, Germania
EUR 92,27
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated by the University of California, Irvine, USA, as an outstanding Ph.D. thesisPresents data sets that reduce false rain signals in satellite precipitation measurementsProvides advances in the accuracy of satellite-based precipitatio.
Lingua: Inglese
Editore: Springer International Publishing, 2016
ISBN 10: 3319363328 ISBN 13: 9783319363325
Da: moluna, Greven, Germania
EUR 93,00
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated by the University of California, Irvine, USA, as an outstanding Ph.D. thesisPresents data sets that reduce false rain signals in satellite precipitation measurementsProvides advances in the accuracy of satellite-based precipitatio.
Da: Majestic Books, Hounslow, Regno Unito
EUR 152,13
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Palgrave Macmillan Nov 2014, 2014
ISBN 10: 3319120808 ISBN 13: 9783319120805
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed 'big data.' The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch.