scholarly journals Towards Multiscale and Multisource Remote Sensing Mineral Exploration Using RPAS: A Case study in the Lofdal Carbonatite-Hosted REE Deposit, Namibia

2019 ◽  
Vol 11 (21) ◽  
pp. 2500 ◽  
Author(s):  
Booysen ◽  
Zimmermann ◽  
Lorenz ◽  
Gloaguen ◽  
Nex ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mineral Exploration ◽  
Field Work ◽  
Relevant Information ◽  
Hyperspectral Data ◽  
Multiscale Approach ◽  
Carbonatite Complex ◽  
Lithological Mapping ◽  
Aircraft System ◽  
Difficult Terrain

Traditional exploration techniques usually rely on extensive field work supported by geophysical ground surveying. However, this approach can be limited by several factors such as field accessibility, financial cost, area size, climate, and public disapproval. We recommend the use of multiscale hyperspectral remote sensing to mitigate the disadvantages of traditional exploration techniques. The proposed workflow analyzes a possible target at different levels of spatial detail. This method is particularly beneficial in inaccessible and remote areas with little infrastructure, because it allows for a systematic, dense and generally noninvasive surveying. After a satellite regional reconnaissance, a target is characterized in more detail by plane-based hyperspectral mapping. Subsequently, Remotely Piloted Aircraft System (RPAS)-mounted hyperspectral sensors are deployed on selected regions of interest to provide a higher level of spatial detail. All hyperspectral data are corrected for radiometric and geometric distortions. End-member modeling and classification techniques are used for rapid and accurate lithological mapping. Validation is performed via field spectroscopy and portable XRF as well as laboratory geochemical and spectral analyses. The resulting spectral data products quickly provide relevant information on outcropping lithologies for the field teams. We show that the multiscale approach allows defining the promising areas that are further refined using RPAS-based hyperspectral imaging. We further argue that the addition of RPAS-based hyperspectral data can improve the detail of field mapping in mineral exploration, by bridging the resolution gap between airplane- and ground-based data. RPAS-based measurements can supplement and direct geological observation rapidly in the field and therefore allow better integration with in situ ground investigations. We demonstrate the efficiency of the proposed approach at the Lofdal Carbonatite Complex in Namibia, which has been previously subjected to rare earth elements exploration. The deposit is located in a remote environment and characterized by difficult terrain which limits ground surveys.

scholarly journals Measuring the Morphology and Dynamics of the Snake River by Remote Sensing

2011 ◽  
Vol 33 ◽  
pp. 3-15
Author(s):  
Carl Legleiter
Keyword(s):  
Remote Sensing ◽  
Image Data ◽  
River System ◽  
Field Work ◽  
Hyperspectral Data ◽  
Snake River ◽  
Central Component ◽  
Data Sets ◽  
Channel Form ◽  
And Behavior

The Snake River is a central component of Grand Teton National Park, and this dynamic fluvial system plays a key role in shaping the landscape and creating diverse aquatic and terrestrial habitat. The river’s complexity and propensity for change make effective characterization of this resource difficult, however, and conventional, ground-based methods are simply inadequate. Remote sensing provides an appealing alternative approach that could facilitate resource management while providing novel insight on the factors controlling channel form and behavior. In this study, we evaluate the potential to measure the morphology and dynamics of a large, complex river system such as the Snake using optical image data. Initially, we made use of existing, publicly available images and basic digital aerial photography acquired in August 2010. Analysis to date has focused on estimating flow depths from these data, and preliminary results indicate that remote bathymetric mapping is feasible but not highly accurate, with important constraints related to the limited radiometric resolution of these data sets. Additional, more sophisticated hyperspectral data are scheduled for collection in 2011, along with further field work.

Mapping lithology in Canada's Arctic: application of hyperspectral data using the minimum noise fraction transformation and matched filtering

2005 ◽  
Vol 42 (12) ◽  
pp. 2173-2193 ◽  
Author(s):  
J R Harris ◽  
D Rogge ◽  
R Hitchcock ◽  
O Ijewliw ◽  
D Wright
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Hyperspectral Data ◽  
Matched Filtering ◽  
Lithological Mapping ◽  
Minimum Noise Fraction ◽  
Logical Mapping ◽  
End Members ◽  
Noise Fraction ◽  
Minimum Noise

A test site in southern Baffin Island, Canada has been established to study the applications of hyperspectral data to lithological mapping. Good bedrock exposure and minimal vegetation cover provide an ideal environment for the evaluation of hyperspectral remote sensing. Airborne PROBE hyperspectral data were collected over the study site during the summer of 2000. Processing methods involved (1) applying a minimum noise fraction (MNF) transformation to the data and visual interpretation of a ternary colour MNF image to produce a lithological–compositional map, and (2) selection of end members from the MNF image followed by matched filtering based on the selected end members to produce a lithological–compositional map. Both methods have produced a lithological map that compares favourably with the existing geological map. Although lichen imparts a similarity to the spectra throughout the visible and near infrared and short-wave infrared ranges, this study has shown that enough variability in the spectra as a function of different mineralogy was present to successfully discriminate one major lithological group (metatonalites) and three compositional units (psammites, quartzites, and monzogranites). Vegetation could be clearly distinguished, which in this area only is a good proxy for mapping metagabbroic rocks. Furthermore, discrimination of slightly different compositional units within the psammites and the metatonalites was also possible. The results from this study indicate that hyperspectral remotely sensed imagery holds promise for lithological mapping in Canada's North, although further analysis is required in different geologic environments in Canada's North to validate hyperspectral remote sensing as a useful aid to litho logical mapping.

scholarly journals A preliminary approach on the use of satellite hyperspectral data for geological mapping

2007 ◽  
Vol 40 (4) ◽  
pp. 1998
Author(s):  
G. K. Nikolakopoulos ◽  
D. A. Vaiopoulos ◽  
G. A. Skianis
Keyword(s):  
Remote Sensing ◽  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Mineral Exploration ◽  
Hyperspectral Data ◽  
Geological Mapping ◽  
Atmospheric Effects ◽  
Extensive Information ◽  
Hyperion Image ◽  
Noise Fraction

During the last decades remote sensing imagery has contributed significantly to mineral exploration. Motivated by the increasing importance of hyperspectral remote sensing, this study investigates the potential of the current-generation satellite hyperspectral data for geological mapping. A narrow-band Hyperion image, acquired in summer 2001, was used. The study area is situated at Milos island. Two different approaches were used for the reduction of the Hyperion bands. First, on the basis of histogram statistics the uncalibrated bands were selected and removed. Then the Minimum Noise Fraction was used to classify the bands according to their signal to noise ratio. The noisiest bands were removed and sixty bands were selected for further processing. In order to make meaningful comparisons between image spectra and laboratory reflectance spetra, the image radiance values must be corrected (calibrated) to reflectance by removing the atmospheric effects. Atmospheric corrections techniques were applied to the selected Hyperion bands. The comparison of the Hyperion hyperspectral data with the JPL spectral library gave quite encouraging results. Further processing of the data has to be done using the image analysis algorithms that have been developed specifically to exploit the extensive information contained in hyperspectral imagery.

scholarly journals The Rocklea Dome 3D Mineral Mapping Test Data Set

2020 ◽  
Author(s):  
Carsten Laukamp ◽  
Maarten Haest ◽  
Thomas Cudahy
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Test Data ◽  
Mineral Exploration ◽  
Hyperspectral Data ◽  
Mineral Deposits ◽  
Drill Core ◽  
Data Set ◽  
Mineral Mapping ◽  
Barren Ground

Abstract. The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible datasets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel-iron deposits (CID) through cover. We present hyperspectral airborne, surface and drill core reflectance spectra collected in the visible-near infrared and shortwave infrared wavelength ranges (VNIR-SWIR; 350 to 2500 nm), as well as whole rock geochemistry obtained by means of X-Ray fluorescence analysis and loss on ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean geology (i.e. barren ground) has significant implications for other areas where cover (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programs. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed to quantify iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the already published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The here newly presented white mica and chlorite abundance maps derived from airborne hyperspectral highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.

scholarly journals QUALITY ASSESSMENT OF DIMENSIONALITY REDUCTION TECHNIQUES ON HYPERSPECTRAL DATA: A NEURAL NETWORK BASED APPROACH

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 389-394
Author(s):  
C. Deepa ◽  
A. Shetty ◽  
A. V. Narasimhadhan
Keyword(s):  
Remote Sensing ◽  
Dimensionality Reduction ◽  
Visual Analysis ◽  
Mineral Exploration ◽  
Evaluation Criteria ◽  
Single Layer ◽  
Remote Sensing Data ◽  
Hyperspectral Data ◽  
Machine Learning Algorithms ◽  
Underlying Structure

Abstract. Dimensionality reduction of hyperspectral images plays a vital role in remote sensing data analysis. The rapid advances in hyperspectral remote sensing has brought in a lot of opportunities to researchers to come up with advanced algorithms to analyse such voluminous data to better explore earth surface features. Modern machine learning algorithms can be applied to explore the underlying structure of high dimensional hyperspectral data and reduce the redundant information through feature extraction techniques. Limited studies have been carried out on dimensionality reduction for mineral exploration. The current study mainly focuses on the application of autoencoders for dimensionality reduction and provides a qualitative (visual) analysis of the obtained representations. The performance of autoencoders are investigated on Cuprite scene. Coranking matrix is used as evaluation criteria. From the obtained results it is evident that, deep autoencoders provide better results compared to single layer autoencoders. An increase in the number of hidden layers provides a better embedding. The neighborhood size K ≥ 40 of deep autoencoders provides a better transformation compared to autoencoders which shows an improved embedding only after K ≥ 80.

scholarly journals Remote sensing data for Geological mapping and gold prospecting of Inteet area, northern Sudan

2021 ◽  
Vol 258 ◽  
pp. 03009
Author(s):  
Mohammed Ibrahim ◽  
Alexander Kotelnikov ◽  
Pavel Podolko ◽  
Elena Kotelnikova
Keyword(s):  
Remote Sensing ◽  
Gold Mineralization ◽  
Mineral Exploration ◽  
Mining Industry ◽  
Remote Sensing Data ◽  
Field Work ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Office Work ◽  
Rock Types

The mineral exploration has improved in the last decades, today there are different methods of remote exploration, that are applied in mining industry worldwide, helping to discover ore minerals deposits in zones that have not access to them. The study area of this article is located about 400 km from Khartoum, characterized by low reliefs covered by sand and gravely sand. The study wants to carry out the geological mapping and the prospective zones using remote sensing and GIS techniques. Sudan is characterized by geological formations over inaccessible areas, in that way the remote sensing technique has a great value in these conditions, saving time and money. The used methodology has been divided into three phases: Pre-field office work, field work and post-field work. The processing of the satellite images includes color band composites, in order to obtain the lithological and geological features, the different types of rocks were defined by a different color. Obtaining the following rock types: High-grade gneisses and migmatites described to comprise the basement complex, ophiolitic mafic-ultramafic rocks that appear in the northern and southern sides of the area, metasediments that cover most of the study area, syn-orogenic intrusions that cut the older mafic-ultramafic units and the metavolcanosedimentary sequences, post-orogenic intrusions and gold mineralization. Based on the image analysis results of Landsat 8 OLI, 32 ore samples were collected to analysis gold and pathfinder elements obtaining high anomalies results for Au, Ag, Cu, Zn, Pb and Fe.

scholarly journals Detection of kimberlitic rocks in West Greenland using airborne hyperspectral data: the HyperGreen 2002 project

2005 ◽  
Vol 7 ◽  
pp. 69-72 ◽  
Author(s):  
Tapani Tukiainen ◽  
Leif Thorning
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Field Work ◽  
Hyperspectral Data ◽  
West Greenland ◽  
Sensing Data ◽  
Important Target ◽  
Viable Method

Previous investigations by the Geological Survey of Denmark and Greenland (GEUS) and exploration companies have demonstrated that some of the kimberlites in West Greenland are diamond bearing, making the region an important target for diamond prospecting. High-resolution hyperspectral (HS) remote sensing data have been successfully used for the location of kimberlitic rocks, e.g. in Australia and Africa. However, its potential as a viable method for the mapping of kimberlite occurrences in Arctic glaciated terrain with high relief was previously unknown. In July–August 2002, GEUS conducted an airborne hyperspectral survey in central West Greenland (Fig. 1) using the commercially available HyMap hyperspectral scanner operated by HyVista Corporation, Australia. Data were processed in 2003, and in 2004 follow-up field work was carried out in the Kangerlussuaq region to test possible kimberlites indicated by the HS data (Fig. 1). The project wasfinanced by the Bureau of Minerals and Petroleum, Government of Greenland.

scholarly journals The Rocklea Dome 3D Mineral Mapping Test Data Set

2021 ◽  
Vol 13 (3) ◽  
pp. 1371-1383
Author(s):  
Carsten Laukamp ◽  
Maarten Haest ◽  
Thomas Cudahy
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Test Data ◽  
Mineral Exploration ◽  
Hyperspectral Data ◽  
Mineral Deposits ◽  
Data Sets ◽  
Drill Core ◽  
Data Set ◽  
Mineral Mapping

Abstract. The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible data sets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open-access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel iron deposits (CIDs) through cover. We present hyperspectral airborne, surface, and drill core reflectance spectra collected in the visible–near-infrared and shortwave infrared wavelength ranges (VNIR–SWIR; 350 to 2500 nm), as well as whole-rock geochemistry obtained by means of X-ray fluorescence analysis and loss-on-ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean bedrock (i.e. barren ground) has significant implications for other areas where “cover” (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programmes. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed the quantification of iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the previously published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The white mica and chlorite abundance maps derived from airborne hyperspectral, presented here for the first time, highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.

Upernavik 98: reconnaissance mineral exploration in North-West Greenland

1999 ◽  
pp. 39-45 ◽  
Author(s):  
Bjørn Thomassen ◽  
Johannes Kyed ◽  
Agnete Steenfelt ◽  
Tapani Tukiainen
Keyword(s):  
Mineral Exploration ◽  
Mining Industry ◽  
Field Work ◽  
Geological Survey ◽  
Original Series ◽  
West Greenland ◽  
North West ◽  
One Year

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Thomassen, B., Kyed, J., Steenfelt, A., & Tukiainen, T. (1999). Upernavik 98: reconnaissance mineral exploration in North-West Greenland. Geology of Greenland Survey Bulletin, 183, 39-45. https://doi.org/10.34194/ggub.v183.5203 _______________ The Upernavik 98 project is a one-year project aimed at the acquisition of information on mineral occurrences and potential in North-West Greenland between Upernavik and Kap Seddon, i.e. from 72°30′ to 75°30′N (Fig. 1A). A similar project, Karrat 97, was carried out in 1997 in the Uummannaq region 70°30′–72°30′N (Steenfelt et al. 1998a). Both are joint projects between the Geological Survey of Denmark and Greenland (GEUS) and the Bureau of Minerals and Petroleum (BMP), Government of Greenland, and wholly funded by the latter. The main purpose of the projects is to attract the interest of the mining industry. The field work comprised systematic drainage sampling, reconnaissance mineral exploration and spectroradiometric measurements of rock surfaces.

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