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Comparison of lithological mapping results from airborne hyperspectral VNIR-SWIR, LWIR and combined data

Feng, Jilu and Rogge, Derek and Rivard, Benoit (2017) Comparison of lithological mapping results from airborne hyperspectral VNIR-SWIR, LWIR and combined data. International Journal of Applied Earth Observation and Geoinformation, 64, pp. 340-353. Elsevier. DOI: 10.1016/j.jag.2017.03.003 ISSN 0303-2434

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Official URL: http://www.sciencedirect.com/science/article/pii/S0303243417300661

Abstract

This study investigates using the Airborne Hyperspectral Imaging Systems (AISA) visible and short- wave infrared (SWIR) and Spatially Enhanced Broadband Array Spectrograph System (SEBASS) longwave infrared (LWIR) (2 and 4 m spatial resolution, respectively) imagery independently and in combination to produce detailed lithologic maps in a subarctic region (Cape Smith Belt, Nunavik, Canada) where regionally metamorphosed lower greenschist mafic, ultramafic and sedimentary rocks are exposed in the presence of lichen coatings. We make use of continuous wavelet analysis (CWA) to improve the radiometric quality of the imagery through the minimization of random noise and the enhancement of spectral features, the minimization of residual errors in the ISAC radiometric correction and target tem- perature estimation in the case of the LWIR data, the minimization of line to line residual calibration effects that lead to inconsistencies in data mosaics, and the reduction in variability of the spectral con- tinuum introduced by variable illumination and topography. The use of CWA also provides a platform to directly combine the wavelet scale spectral profiles of the SWIR and LWIR after applying a scalar correc- tion factor to the LWIR such that the dynamic range of two data sets have equal weight. This is possible using CWA as the datasets are normalized to a zero mean allowing spectra from different spectral regions to be adjoined. Lithologic maps are generated using an iterative spectral unmixing approach with image spectral end- members extracted from the SWIR and LWIR imagery based on locations defined from previous work of the study area and field mapping information. Unmixing results of the independent SWIR and LWIR data, and the combined data show clear benefits to using the CWA combined imagery. The analysis showed SWIR and LWIR imagery highlight similar regions and spatial distributions for the three ultramafic units (dunite, peridotite, pyroxenite). However, significant differences are observed for quartz-rich sediments, with the SWIR overestimating the distribution of these rocks whereas the LWIR provided more consis- tent results compared with existing maps. Both SWIR and LWIR imagery were impacted by the pervasive lichen coatings on the mafic rocks (basalts and gabbros), although the SWIR provided better results than the LWIR. Limitations observed for the independent data sets were removed using the combined spectral data resulting in all geologically meaningful units mapped correctly in comparison with existing geological maps.

Item URL in elib:https://elib.dlr.de/111807/
Document Type:Article
Title:Comparison of lithological mapping results from airborne hyperspectral VNIR-SWIR, LWIR and combined data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Feng, Jilujfeng (at) ualberta.caUNSPECIFIED
Rogge, Derekderek.rogge (at) dlr.deUNSPECIFIED
Rivard, Benoitbenoit.rivard (at) ualberta.caUNSPECIFIED
Date:2017
Journal or Publication Title:International Journal of Applied Earth Observation and Geoinformation
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:64
DOI :10.1016/j.jag.2017.03.003
Page Range:pp. 340-353
Publisher:Elsevier
ISSN:0303-2434
Status:Published
Keywords:Short wave infrared Long wave infrared Wavelet analysis Airborne hyperspectral Geological mapping
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Rogge, Derek
Deposited On:27 Jul 2017 14:56
Last Modified:06 Sep 2019 15:16

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