Abstract
Most of the studies using hyperspectral data for geological applications have addressed areas in aridto semi-arid climates. This Ph.D. thesis presents research examining how well geological mappingworks under the arctic, high relief conditions of Greenland, using hyperspectral data acquired fromdifferent platforms and at various scales. Building upon the results derived from regional airbornehyperspectral data, it is demonstrated that one of the main sources for potential misclassification ofpixels in the Arctic is the subpixel spectral mixing of lichens and their rock substrate. To address thegaps in current knowledge about the effect of lichens with respect to geological applications, Iinvestigate here a) how lichens affect spectral recognition of common rock-forming minerals (paperI), b) how to estimate lichens abundance by developing generic indices that can be used regardless ofthe mineralogy of underlying rocks and the species of lichens (paper II) and c) how to tackle thisobstacle by using suitable mapping approaches (paper III).The second major challenge that has been addressed is the lack of feasible approaches to capture thehyperspectral data as part of a large-scale operation (i.e., areas of hundreds or thousands of squarekilometres) in a time- and cost-effective manner, in particular for areas of difficult access. Coastalcliffs are examples of major well-exposed outcrops in the Arctic that are mostly inaccessible and notobservable by air/spaceborne nadir remote sensing sensors due to steep topography. The applicationof close range sub-horizontal hyperspectral imaging using terrestrial platforms and integration ofspectral data with accurate terrain models has recently gained attention for mapping of steep outcrops.However, observing a geological target at close range (i.e. within a range of one to several hundredmetres) is not always feasible. In other words, larger targets such as steep mountain slopes, sea- orlake-faced cliffs are often only fully visible from an opposing location such as a neighbouringmountain or shoreline. The distance between the sensor and the target of interest can then easilyextend to several kilometres. For this reason, I proposed a new data acquisition strategy, namely longrangeterrestrial outcrop sensing, which is tested for the first time during a field campaign I led in thesummer of 2016 in South West Greenland in the region between the fjords Ikertoq and SøndreStrømfjord. Karrat region in West Greenland was selected as the second test site for demonstratingthe applicability of this new data acquisition approach. The results of both surveys are discussed inmore details in (Rosa et al. 2017; Salehi and Thaarup 2018).
Despite the promising results achieved by using this approach, the rugged topography and difficultterrain accessibility in the Arctic often hinder the instrumentation setup and limit the employment ofsuch a data acquisition strategy. To overcome these limitations, I have investigated the potential of5using a platform in motion (such as a boat/ship) to continuously acquire the hyperspectral data whilesailing along the fjords (paper IV). In addition, the two-dimensional maps generated fromhyperspectral imaging are transformed to three-dimensional hyperclouds and integrated with terrainmodels generated from oblique photogrammetry. The high spatial resolution of terrain models allowsinvestigating e.g. faults and the general morphology of lithologies whereas spectral data providesinformation regarding the mineralogy and chemical composition of the rocks.
My observations suggest that regardless of using terrestrial or moving platforms, performing therequired preprocessing for data captured from distant targets is not straight-forward. Firstly, thelogistical setup of “visible” reference targets for radiometric correction with the same orientation anddistance as the distant target outcrop is not possible. Secondly, large distances between the sensor andthe outcrop lead to major atmospheric distortions. Thirdly, owing to the large scale of the observedsurface and the sensor viewing perspective, pixels within one scene can represent a range of differentdistances and orientations, leading to highly variable radiometric distortions. For those reasons,correction methods established for nadir acquisitions need to be adapted to account for the specialconditions of long-range sub-horizontal sensing of outcrops (paper V).
Despite the promising results achieved by using this approach, the rugged topography and difficultterrain accessibility in the Arctic often hinder the instrumentation setup and limit the employment ofsuch a data acquisition strategy. To overcome these limitations, I have investigated the potential of5using a platform in motion (such as a boat/ship) to continuously acquire the hyperspectral data whilesailing along the fjords (paper IV). In addition, the two-dimensional maps generated fromhyperspectral imaging are transformed to three-dimensional hyperclouds and integrated with terrainmodels generated from oblique photogrammetry. The high spatial resolution of terrain models allowsinvestigating e.g. faults and the general morphology of lithologies whereas spectral data providesinformation regarding the mineralogy and chemical composition of the rocks.
My observations suggest that regardless of using terrestrial or moving platforms, performing therequired preprocessing for data captured from distant targets is not straight-forward. Firstly, thelogistical setup of “visible” reference targets for radiometric correction with the same orientation anddistance as the distant target outcrop is not possible. Secondly, large distances between the sensor andthe outcrop lead to major atmospheric distortions. Thirdly, owing to the large scale of the observedsurface and the sensor viewing perspective, pixels within one scene can represent a range of differentdistances and orientations, leading to highly variable radiometric distortions. For those reasons,correction methods established for nadir acquisitions need to be adapted to account for the specialconditions of long-range sub-horizontal sensing of outcrops (paper V).
| Originalsprog | Engelsk |
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| Forlag | Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen |
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| Status | Udgivet - 2018 |
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