QLSU (QGIS Linear Spectral Unmixing) Plugin: An open source linear spectral unmixing tool for hyperspectral &amp; multispectral remote sensing imagery

Celik, Bahadir

doi:10.1016/j.envsoft.2023.105782

Cited by 4 publications

(2 citation statements)

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“…This leads to photons interacting with more than one surface, causing a greater number of reflections, which can then be exacerbated by dark or highly absorbing minerals (Clark, 1983). Given the relative simplicity of linear unmixing methods, the non-linear spectral modeling algorithms are by comparison still considered immature and much more complex (Celik, 2023). However, other approaches to spectral analysis have been developed and work well on hyperspectral data by determining statistical metrics of diagnostic spectral feature [e.g., the USGS Tetracorder (formerly Tricorder) algorithm (Clarke and Swayze, 1995;Clark et al, 2003)].…”

Section: Spectral Modelingmentioning

confidence: 99%

“…Furthermore, linear methods are widely available in different software packages. For example, QGIS, an open-source GIS and remote sensing software package that is maintained by the user community, has modules that can be installed to provide MESMA or the QGIS Linear Spectral Unmixing (QLSU) plugin (Celik, 2023). Tetracorder is directly available from the USGS (https://www.usgs.gov/labs/spectroscopy-lab), and commercial software packages such as ENVI (Environment for Visualizing Images) also contain SMA-based algorithms.…”

Section: Spectral Modelingmentioning

confidence: 99%

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Infrared spectroscopy of volcanoes: from laboratory to orbital scale

Williams,

Ramsey

2024

Front. Earth Sci.

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Understanding the composition, texture, and morphology of volcanic rocks that have erupted at the surface better constrains the eruption style and is vital to infer subsurface processes, the development of magma upon ascent, and the potential for future eruptions. The reflectance and emission spectroscopy of these rocks, collected from the near-infrared (NIR) through the thermal infrared (TIR) portion of the electromagnetic (EM) spectrum, provides the data necessary to retrieve composition, micron-scale surface roughness, and particle size. Remote imaging systems enable the analyses of active volcanoes in remote regions, where sample collection for laboratory analysis poses a significant challenge. Laboratory hyperspectral data of samples acquired at volcanic deposits are easily resampled to the spectral resolution of any infrared sensor and provide a means of estimating the composition of volcanoes and their products worldwide, as well as those on other planetary bodies such as the Moon and Mars. In this review paper, we provide an overview of the current use of infrared reflectance and emission spectroscopy as an analysis tool in volcanology, including ground-based imaging systems that acquire unprecedented detail and serve as testbeds for new orbital concepts. We also discuss the potential impact that future satellite missions will have on volcano science as spectral, spatial, and temporal resolutions improve.

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Section: Spectral Modelingmentioning

confidence: 99%

Section: Spectral Modelingmentioning

confidence: 99%