Hyperspectral Sensors and Applications

Lucas, Richard; Rowlands, Alun; Niemann, O.; Merton, Ray

doi:10.1007/978-3-662-05605-9_2

Cited by 20 publications

(9 citation statements)

References 104 publications

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“…Hyperspectral images from the spaceborne Hyperion sensor are less commonly used for alien species mapping, probably due to the coarse GSI (30 m) and low signal-to-noise ratio compared to airborne imaging spectrometer data [ 63 , 64 ]. Nevertheless, Hyperion provides an opportunity for systematic data collection over a remote region on a stable platform (EO-1 satellite) and at much lower cost than many airborne mapping efforts.…”

Section: Hyperspectral Remote Sensingmentioning

confidence: 99%

Applications of Remote Sensing to Alien Invasive Plant Studies

Huang

Asner

2009

Sensors

242

177

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Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR) system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions.

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Section: Hyperspectral Remote Sensingmentioning

confidence: 99%

Applications of Remote Sensing to Alien Invasive Plant Studies

Huang

Asner

2009

Sensors

242

177

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“…Christian Fischer and Ioanna Kakoulli development phases of spectral imaging in remote sensing [18,19].…”

Section: Multispectral and Hyperspectral Imaging Technologies In Consmentioning

confidence: 99%

Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications

Fischer¹,

Kakoulli²

2006

Studies in Conservation

269

162

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Spectral imaging technology, which records simultaneously spectral and spatial information about an object, was initially developed for remote sensing and has since been successfully applied to other areas of research. Although relatively new to the field of conservation, this non-invasive method of investigation has already provided promising results in the analysis of paintings and written documents, the characterization of materials and digital documentation. This article reviews the published literature relating to the application of multispectral and hyperspectral imaging for the study and conservation of works of art and presents some new perspectives offered by this innovative and fast-developing technology.

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“…Hyperspectral images are able to convey much more spectral information than RGB or other multispectral data: each pixel is in fact a high-dimensional vector typically containing reflectance measurements from hundreds of contiguous narrow band spectral channels (full width at half maximum, FWHM between 2 and 20 nm) covering one or more relatively wide spectral intervals (typically, but not exclusively, in the 400–2500 nm wavelength range) [ 9 ]. Current HSI acquisition technologies are able to provide high spectral resolution while guaranteeing enough spatial resolution and data throughput for advanced visual data analysis [ 10 ] in a variety of quality demanding application contexts [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review

et al. 2019

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Modern hyperspectral imaging systems produce huge datasets potentially conveying a great abundance of information; such a resource, however, poses many challenges in the analysis and interpretation of these data. Deep learning approaches certainly offer a great variety of opportunities for solving classical imaging tasks and also for approaching new stimulating problems in the spatial–spectral domain. This is fundamental in the driving sector of Remote Sensing where hyperspectral technology was born and has mostly developed, but it is perhaps even more true in the multitude of current and evolving application sectors that involve these imaging technologies. The present review develops on two fronts: on the one hand, it is aimed at domain professionals who want to have an updated overview on how hyperspectral acquisition techniques can combine with deep learning architectures to solve specific tasks in different application fields. On the other hand, we want to target the machine learning and computer vision experts by giving them a picture of how deep learning technologies are applied to hyperspectral data from a multidisciplinary perspective. The presence of these two viewpoints and the inclusion of application fields other than Remote Sensing are the original contributions of this review, which also highlights some potentialities and critical issues related to the observed development trends.

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Hyperspectral Sensors and Applications

Cited by 20 publications

References 104 publications

Applications of Remote Sensing to Alien Invasive Plant Studies

Applications of Remote Sensing to Alien Invasive Plant Studies

Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications

Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review

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