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Snow Grain Size Mapping using Hyperspectral Remote Sensing Data

Snow Grain Size Mapping using Hyperspectral Remote Sensing Dataaf Arnab Saha
Bag om Snow Grain Size Mapping using Hyperspectral Remote Sensing Data

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9786137321973
  • Indbinding:
  • Paperback
  • Sideantal:
  • 68
  • Udgivet:
  • 24. januar 2018
  • Størrelse:
  • 150x5x220 mm.
  • Vægt:
  • 119 g.
  • BLACK NOVEMBER
Leveringstid: 2-3 uger
Forventet levering: 4. december 2024

Beskrivelse af Snow Grain Size Mapping using Hyperspectral Remote Sensing Data

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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