Mapping of NiCu–PGE ore hosting ultramafic rocks using airborne and simulated EnMAP hyperspectral imagery, Nunavik, Canada

Rogge, Derek; Rivard, Benoît; Segl, Karl; Grant, Brian; Feng, Jiang

doi:10.1016/j.rse.2014.06.024

Cited by 56 publications

(26 citation statements)

References 28 publications

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“…Whereas, for the two extra BS sub classes derived from HyMap, pixel size likely influenced their ability to be extracted. Similar conclusions were drawn by Rogge et al [43], whom considered airborne AISA and simulated EnMAP data for mapping geology, pointing out that the different spatial resolutions (2 and 30 m pixels) was the main reason for important differences in the extracted endmembers.…”

Section: Fractional Cover Estimatessupporting

confidence: 85%

“…Since no ground truth data were available in this study, plausibility checks concerning the spectral and spatial capabilities of EnMAP have been carried out using the airborne HyMap data. A similar approach was used in Rogge et al [43] which used airborne data for plausibility checks to assess simulated EnMAP data for geological mapping. Although an independent reference is missing, the detailed qualitative and quantitative comparison of the EnMAP and HyMap results derived using the same methodological approach will give valuable insights into the capacities of the upcoming EnMAP satellite to provide useful information related to estimating soil erosion potential at a regional scale.…”

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confidence: 99%

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Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

et al. 2015

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Soil erosion can be linked to relative fractional cover of photosynthetic-active vegetation (PV), non-photosynthetic-active vegetation (NPV) and bare soil (BS), which can be integrated into erosion models as the cover-management C-factor. This study investigates the capability of EnMAP imagery to map fractional cover in a region near San Jose, Costa Rica, characterized by spatially extensive coffee plantations and grazing in a mountainous terrain. Simulated EnMAP imagery is based on airborne hyperspectral HyMap data. Fractional cover estimates are derived in an automated fashion by extracting image endmembers to be used with a Multiple End-member Spectral Mixture Analysis approach. The C-factor is calculated based on the fractional cover estimates determined independently for EnMAP and HyMap. Results demonstrate that with EnMAP imagery it is possible to extract quality endmember classes with important spectral features related to PV, NPV and soil, and be able to estimate relative cover fractions. This spectral information is critical to separate BS and NPV which greatly can impact the C-factor OPEN ACCESS Remote Sens. 2015, 7 11777 derivation. From a regional perspective, we can use EnMAP to provide good fractional cover estimates that can be integrated into soil erosion modeling.

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Section: Fractional Cover Estimatessupporting

confidence: 85%

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confidence: 99%

Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

et al. 2015

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“…Hyperspectral images can have considerable utility in the identification and mapping of exposed geological classes [53][54][55][56][57][58][59]. The Hyperion sensor, on board the orbiting EO-1 (Earth Observing One) satellite, collects data with a 30 m pixel size in 242 bands in the visible, near-infrared, and shortwave infrared ranges [60,61].…”

Section: Hyperion Imagesmentioning

confidence: 99%

Detection and Mapping of Black Rock Coatings Using Hyperion Images: Sudbury, Ontario, Canada

Leverington

Schindler

2016

Remote Sensing

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Base metal smelting activities can produce acidic rain that promotes vegetation loss and the development of black coatings on bedrock. Such coatings can form over large areas and are among the most prominent long-term vestiges of past smelting activities. In this study, multispectral images derived from Hyperion reflectance data were evaluated with regard to their utility in the discrimination and mapping of black rock coatings near Sudbury. Spectral angle mapper (SAM) classifications generated on the basis of image-derived endmember spectra could not be used to properly identify major exposures of coated bedrock without also producing substantial confusion with uncoated classes. Neural network and maximum likelihood classifications produced improved representations of the spatial distribution of coated bedrock, though confusion between coated and uncoated classes is problematic in most outputs. Maximum likelihood results generated using a null class are noteworthy for their effectiveness in highlighting exposures of coated bedrock without substantial confusion with uncoated classes. Although challenges remain, classification results confirm the potential of remote sensing techniques for use in the worldwide detection, mapping, and monitoring of coating-related environmental degradation in the vicinities of base metal smelters.

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“…The two different types of rock coatings include biogenic (e.g., lichens, which consist mostly of mosses and cyanobacteria and form in humid environments [18,19]) and non-biogenic (e.g., desert varnish) coatings. Desert varnish is a mixed layer of illite clays and nanocrystalline iron and manganese oxides, which partially cover rock surfaces in arid and semi-arid environments [20][21][22].…”

Section: Introductionmentioning

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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Mapping of NiCu–PGE ore hosting ultramafic rocks using airborne and simulated EnMAP hyperspectral imagery, Nunavik, Canada

Cited by 56 publications

References 28 publications

Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

Detection and Mapping of Black Rock Coatings Using Hyperion Images: Sudbury, Ontario, Canada

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

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