Foreword to the special Issue on hyperspectral remote sensing and imaging spectroscopy

Saurabh Prasad, Wenzhi Liao, Mingyi He, Jocelyn Chanussot

Research output: Contribution to journalSpecial issue

1 Citation (Scopus)

Abstract

The twenty six papers in this special issue focus on the technologies of hyperspectral remote sensing (HRS)and imaging spectroscopy. HRS has emerged as a powerful tool to understand phenomena at local and global scales by virtue of imaging through a diverse range of platforms, including terrestrial in-situ imaging platforms, unmanned and manned aerial vehicles, and satellite platforms. By virtue of imaging over a wide range of spectral wavelengths, it is possible to characterize object specific properties very accurately. As a result, hyperspectral imaging (also known as imaging spectroscopy) has gained popularity for a wide variety of applications, including environment monitoring, precision agriculture, mineralogy, forestry, urban planning, and defense applications. The increased analysis capability comes at a cost—there are a variety of challenges that must be overcome for robust image analysis of such data, including high dimensionality, limited sample size for training supervised models, noise and atmospheric affects, mixed pixels, etc. The papers in this issue represent some of the recent developments in image analysis algorithms and unique applications of hyperspectral imaging data.
LanguageEnglish
Pages1019-1021
Number of pages3
Journal IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume11
Issue number4
DOIs
Publication statusPublished - 10 Apr 2018

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image analysis
remote sensing
platforms
spectroscopy
precision agriculture
urban planning
forestry
pixel
mineralogy
agriculture
wavelength
vehicles
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monitoring
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costs
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Keywords

  • special issues and sections
  • hperspectral imaging
  • image analysis
  • data integration
  • remote sensing
  • compressed sensing
  • image classification

Cite this

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title = "Foreword to the special Issue on hyperspectral remote sensing and imaging spectroscopy",
abstract = "The twenty six papers in this special issue focus on the technologies of hyperspectral remote sensing (HRS)and imaging spectroscopy. HRS has emerged as a powerful tool to understand phenomena at local and global scales by virtue of imaging through a diverse range of platforms, including terrestrial in-situ imaging platforms, unmanned and manned aerial vehicles, and satellite platforms. By virtue of imaging over a wide range of spectral wavelengths, it is possible to characterize object specific properties very accurately. As a result, hyperspectral imaging (also known as imaging spectroscopy) has gained popularity for a wide variety of applications, including environment monitoring, precision agriculture, mineralogy, forestry, urban planning, and defense applications. The increased analysis capability comes at a cost—there are a variety of challenges that must be overcome for robust image analysis of such data, including high dimensionality, limited sample size for training supervised models, noise and atmospheric affects, mixed pixels, etc. The papers in this issue represent some of the recent developments in image analysis algorithms and unique applications of hyperspectral imaging data.",
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author = "Saurabh Prasad and Wenzhi Liao and Mingyi He and Jocelyn Chanussot",
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Foreword to the special Issue on hyperspectral remote sensing and imaging spectroscopy. / Prasad, Saurabh; Liao, Wenzhi; He, Mingyi; Chanussot, Jocelyn.

In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , Vol. 11, No. 4, 10.04.2018, p. 1019-1021.

Research output: Contribution to journalSpecial issue

TY - JOUR

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AU - Prasad, Saurabh

AU - Liao, Wenzhi

AU - He, Mingyi

AU - Chanussot, Jocelyn

PY - 2018/4/10

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N2 - The twenty six papers in this special issue focus on the technologies of hyperspectral remote sensing (HRS)and imaging spectroscopy. HRS has emerged as a powerful tool to understand phenomena at local and global scales by virtue of imaging through a diverse range of platforms, including terrestrial in-situ imaging platforms, unmanned and manned aerial vehicles, and satellite platforms. By virtue of imaging over a wide range of spectral wavelengths, it is possible to characterize object specific properties very accurately. As a result, hyperspectral imaging (also known as imaging spectroscopy) has gained popularity for a wide variety of applications, including environment monitoring, precision agriculture, mineralogy, forestry, urban planning, and defense applications. The increased analysis capability comes at a cost—there are a variety of challenges that must be overcome for robust image analysis of such data, including high dimensionality, limited sample size for training supervised models, noise and atmospheric affects, mixed pixels, etc. The papers in this issue represent some of the recent developments in image analysis algorithms and unique applications of hyperspectral imaging data.

AB - The twenty six papers in this special issue focus on the technologies of hyperspectral remote sensing (HRS)and imaging spectroscopy. HRS has emerged as a powerful tool to understand phenomena at local and global scales by virtue of imaging through a diverse range of platforms, including terrestrial in-situ imaging platforms, unmanned and manned aerial vehicles, and satellite platforms. By virtue of imaging over a wide range of spectral wavelengths, it is possible to characterize object specific properties very accurately. As a result, hyperspectral imaging (also known as imaging spectroscopy) has gained popularity for a wide variety of applications, including environment monitoring, precision agriculture, mineralogy, forestry, urban planning, and defense applications. The increased analysis capability comes at a cost—there are a variety of challenges that must be overcome for robust image analysis of such data, including high dimensionality, limited sample size for training supervised models, noise and atmospheric affects, mixed pixels, etc. The papers in this issue represent some of the recent developments in image analysis algorithms and unique applications of hyperspectral imaging data.

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