A simple quadratic method of absorption feature wavelength estimation in continuum removed spectra

Rodger, Andrew; Laukamp, Carsten; Haest, Maarten; Cudahy, Thomas

doi:10.1016/j.rse.2011.11.025

Cited by 54 publications

(40 citation statements)

References 25 publications

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“…Imaging spectrometers acquire data in many but discrete spectral bands, and multi-spectral sensors have even wider gaps in wavelength coverage. To model the shape of an absorption feature from spectrally lower resolution bands, interpolation techniques are often used, e.g., [30][31][32]. In our approach, we fit a polynomial function through the reflectance-at-surface values of Sentinel-2 bands.…”

Section: Methods and Study Areamentioning

confidence: 99%

Sentinel-2 for Mapping Iron Absorption Feature Parameters

Werff

Meer

2015

Remote Sensing

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Iron is an indicator for soil fertility and the usability of an area for cultivating crops. Remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval, yet a relative high spectral resolution is needed for mapping iron contents with reflectance data. Sentinel-2 has several bands that cover the 0.9 µm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we introduce a curve-fitting technique for Sentinel-2 that approximates the iron absorption feature at a hyperspectral resolution. We test our technique on library spectra of different iron bearing minerals and we apply it to a Sentinel-2 image synthesized from an airborne hyperspectral dataset. Our method finds the wavelength position of maximum absorption and absolute absorption depth for minerals Beryl, Bronzite, Goethite, Jarosite and Hematite. Sentinel-2 offers information on the 0.9 µm absorption feature that until now was reserved for hyperspectral instruments. Being a satellite mission, this information comes at a lower spatial resolution than airborne hyperspectral data, but with a large spatial coverage and frequent revisit time.

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Section: Methods and Study Areamentioning

confidence: 99%

Sentinel-2 for Mapping Iron Absorption Feature Parameters

Werff

Meer

2015

Remote Sensing

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“…This spectral difference permits the detection of changes related to the slope and brightness in the spectra. Moreover, as a complementary tool, the continuum removal technique was used for detecting subtle differences among the spectra [34,35]. Continuum removal is commonly normalized in the range of spectral reflectance from 0 to 1, which is used in spectroscopy for enhancement of the intensity of the characteristic peaks and absorption features [34,36].…”

Section: Resultsmentioning

confidence: 99%

Spectral properties of weathered and fresh rock surfaces in the Xiemisitai metallogenic belt, NW Xinjiang, China

Zhou

Wang

2017

Open Geosciences

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Surfaces weathering of rocks in which mineral materials may be similar to or quite different from the minerals in the underlying parent rock completely control the reflectance spectra of the terrain. Our study of typical weathered and fresh rock samples from the Xiemisitai metallogenic belt, Western Junggar region, Xinjiang, found that weathering results in the formation of new materials that cause differences in the spectral features of fresh and weathered rock surfaces. Alterations induce variations in spectrum brightness, presence and intensity of characteristic absorption features, and spectral slope. Spectral differences between weathered and fresh rock surfaces are small for rhyolite, granite, and tuffaceous sandstone, but large for andesite, basalt, and diorite. Spectral changes in the 350-1000 nm wavelength region are attributed to alteration of iron oxides by atmospheric processes or secondary alteration of iron-rich minerals. Spectral features between 1000-2500 nm are caused by O-H vibrations, with features at 2200-2500 nm solely attributed to hydroxyl groups. The strongest Al-OH bands appear near 2200 nm, while Mg-OH bands are found near 2300 nm and 2350 nm. Results from this study can be used to better characterize and discriminate lithological units and potential mineral zones using hyperspectral and multispectral remote sensing techniques.

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“…Such parameters were used to interpret the data in terms of the known alteration phases or to estimate heavy metal contents [81]. Rodger et al [82] proposed a simple quadratic method (SQM) to estimate the wavelengths of absorption features in the shortwave infrared (SWIR) spectral region. The SQM method was tested using spectral data convolved to four different instrument configurations differing in sampling regimes and spectral resolutions.…”

Section: Discussionmentioning

confidence: 99%

Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

Kopačková

Koucká

2017

Remote Sensing

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Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS), near-infrared (NIR), shortwave infrared (SWIR) and longwave infrared (LWIR) spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data) and Airborne Hyperspectral Scanner (AHS, LWIR image data). Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved.

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A simple quadratic method of absorption feature wavelength estimation in continuum removed spectra

Cited by 54 publications

References 25 publications

Sentinel-2 for Mapping Iron Absorption Feature Parameters

Sentinel-2 for Mapping Iron Absorption Feature Parameters

Spectral properties of weathered and fresh rock surfaces in the Xiemisitai metallogenic belt, NW Xinjiang, China

Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

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