Processing Analysis Hyperspectral Data (22 results)

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Taschenbuch. Condition: Neu. Snow Grain Size Mapping using Hyperspectral Remote Sensing Data | Spectral Analysis, Pre-processing & Snow Grain Size Mapping of EO-1 Hyperion Data in a Part of Lower Himalayan Region | Arnab Saha | Taschenbuch | 68 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137321973 | Verantwo…rtliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Snow is the part of atmosphere in the climate system of the earth and its physical parameters play an important role in hydrological and climate models. The present study explained that the imaging spectroscopy to produce the snow cover…maps and estimation of snow grain size in the North-Western Himalayan region. It is necessary to develop an approach to map snow cover, snow grain size spatially using advance remote sensing technique. Remote sensing techniques can provide spatial information of a large extent at good temporal scale. In the present study, one of the important snow physical parameters (i.e snow grain size) has been estimated using Spectral angle mapper (SAM) classification method and Grain index (GI) method. Study was carried out by using NASA's hyperspectral EO-1 Hyperion sensor data of 12th January and 23rd January 2016 were used to map grain size of snow. The snow map generating for dry snow, small grain size snow, medium grain size snow, large grain size snow and wet snow classes. This study is of importance in this mapping of snow-cover characteristics, which can provide valuable input for climatology, hydrology, and mountain hazard applications.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Snow is the part of atmosphere in the climate system of the earth and its physical parameters play an important role in hydrological and climate models. The present study explained that the imaging spectroscopy to produce the snow cover…maps and estimation of snow grain size in the North-Western Himalayan region. It is necessary to develop an approach to map snow cover, snow grain size spatially using advance remote sensing technique. Remote sensing techniques can provide spatial information of a large extent at good temporal scale. In the present study, one of the important snow physical parameters (i.e snow grain size) has been estimated using Spectral angle mapper (SAM) classification method and Grain index (GI) method. Study was carried out by using NASA's hyperspectral EO-1 Hyperion sensor data of 12th January and 23rd January 2016 were used to map grain size of snow. The snow map generating for dry snow, small grain size snow, medium grain size snow, large grain size snow and wet snow classes. This study is of importance in this mapping of snow-cover characteristics, which can provide valuable input for climatology, hydrology, and mountain hazard applications.

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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnHyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional…imaging techniques. It has a wide rang.

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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of appl…ications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods. 136 pp. Englisch.

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Buch. Condition: Neu. Processing and Analysis of Hyperspectral Data | Jie Chen (u. a.) | Buch | Gebunden | Englisch | 2020 | IntechOpen | EAN 9781789851090 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applicat…ions, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.Books on Demand GmbH, Überseering 33, 22297 Hamburg 136 pp. Englisch.

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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applicati…ons, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.