scholarly journals Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland

2018 ◽  
Vol 10 (8) ◽  
pp. 1186 ◽  
Author(s):  
Amin Beiranvand Pour ◽  
Tae-Yoon Park ◽  
Yongcheol Park ◽  
Jong Hong ◽  
Basem Zoheir ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Thermal Emission ◽  
Mineral Exploration ◽  
Component Analysis ◽  
High Arctic ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Mineral Assemblages ◽  
North Greenland

Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc deposits. In this research, multi-sensor remote sensing satellite data (e.g., Landsat-8, Phased Array L-band Synthetic Aperture Radar (PALSAR) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) were used for exploring zinc in the trough sequences and shelf-platform carbonate of the Franklinian Basin. A series of robust image processing algorithms was implemented for detecting spatial distribution of pixels/sub-pixels related to key alteration mineral assemblages and structural features that may represent potential undiscovered Zn–Pb deposits. Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) was applied to some selected Landsat-8 mineral indices for mapping gossan, clay-rich zones and dolomitization. Major lineaments, intersections, curvilinear structures and sedimentary formations were traced by the application of Feature-oriented Principal Components Selection (FPCS) to cross-polarized backscatter PALSAR ratio images. Mixture Tuned Matched Filtering (MTMF) algorithm was applied to ASTER VNIR/SWIR bands for sub-pixel detection and classification of hematite, goethite, jarosite, alunite, gypsum, chalcedony, kaolinite, muscovite, chlorite, epidote, calcite and dolomite in the prospective targets. Using the remote sensing data and approaches, several high potential zones characterized by distinct alteration mineral assemblages and structural fabrics were identified that could represent undiscovered Zn–Pb sulfide deposits in the study area. This research establishes a straightforward/cost-effective multi-sensor satellite-based remote sensing approach for reconnaissance stages of mineral exploration in hardly accessible parts of the High Arctic environments.

scholarly journals Mapping Listvenite Occurrences in the Damage Zones of Northern Victoria Land, Antarctica Using ASTER Satellite Remote Sensing Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1408 ◽  
Author(s):  
Amin Beiranvand Pour ◽  
Yongcheol Park ◽  
Laura Crispini ◽  
Andreas Läufer ◽  
Jong Kuk Hong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Thermal Emission ◽  
Remote Sensing Data ◽  
Component Analysis ◽  
Spectral Unmixing ◽  
Metasomatic Alteration ◽  
Sensing Data ◽  
Victoria Land ◽  
Mineral Assemblages

Listvenites normally form during hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represent a key indicator for the occurrence of ore mineralizations in orogenic systems. Hydrothermal/metasomatic alteration mineral assemblages are one of the significant indicators for ore mineralizations in the damage zones of major tectonic boundaries, which can be detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data were used to detect listvenite occurrences and alteration mineral assemblages in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL), Antarctica. Spectral information for detecting alteration mineral assemblages and listvenites were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineralogical assemblages containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were detected in the damage zones of the study area by implementing PCA/ICA fusion to visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate lithological groups were mapped and discriminated using PCA/ICA fusion to thermal infrared (TIR) bands of ASTER. Fraction images of prospective alteration minerals, including goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and possible zones encompassing listvenite occurrences were produced using LSU and CEM algorithms to ASTER VNIR+SWIR spectral bands. Several potential zones for listvenite occurrences were identified, typically in association with mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. Comparison of the remote sensing results with geological investigations in the study area demonstrate invaluable implications of the remote sensing approach for mapping poorly exposed lithological units, detecting possible zones of listvenite occurrences and discriminating subpixel abundance of alteration mineral assemblages in the damage zones of the Wilson-Bowers and Bowers-Robertson Bay terrane boundaries and in intra-Bowers and Wilson terranes fault zones with high fluid flow. The satellite remote sensing approach developed in this research is explicitly pertinent to detecting key alteration mineral indicators for prospecting hydrothermal/metasomatic ore minerals in remote and inaccessible zones situated in other orogenic systems around the world.

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 APPLICATION OF MULTISPECTRAL SATELLITE DATA FOR GEOLOGICAL MAPPING IN ANTARCTIC ENVIRONMENTS

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 77-81 ◽  
Author(s):  
A. B. Pour ◽  
M. Hashim ◽  
J. K. Hong
Keyword(s):  
Remote Sensing ◽  
Antarctic Peninsula ◽  
Thermal Emission ◽  
Structural Data ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Radar Satellite ◽  
Band Depth ◽  
The Antarctic

Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica’s geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM), Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Contrast-enhanced Red-Green-Blue (RGB) composites, band ratios and Relative Band Depth (RBD) image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.

scholarly journals EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO

2020 ◽  
Vol XLIV-M-2-2020 ◽  
pp. 79-85
Author(s):  
A. H. Ngandam Mfondoum ◽  
P. G. Gbetkom ◽  
R. Cooper ◽  
S. Hakdaoui ◽  
M. B. Mansour Badamassi
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Satellite Data ◽  
Kappa Coefficient ◽  
Landsat 8 ◽  
Experimental Site ◽  
Soil Features ◽  
Mixed Pixels ◽  
Shortwave Infrared ◽  
Normalization Process

Abstract. This paper addresses the remote sensing challenging field of urban mixed pixels on a medium spatial resolution satellite data. The tentatively named Normalized Difference Built-up and Surroundings Unmixing Index (NDBSUI) is proposed by using Landsat-8 Operational Land Imager (OLI) bands. It uses the Shortwave Infrared 2 (SWIR2) as the main wavelength, the SWIR1 with the red wavelengths, for the built-up extraction. A ratio is computed based on the normalization process and the application is made on six cities with different urban and environmental characteristics. The built-up of the experimental site of Yaoundé is extracted with an overall accuracy of 95.51% and a kappa coefficient of 0.90. The NDBSUI is validated over five other sites, chosen according to Cameroon’s bioclimatic zoning. The results are satisfactory for the cities of Yokadouma and Kumba in the bimodal and monomodal rainfall zones, where overall accuracies are up to 98.9% and 97.5%, with kappa coefficients of 0.88 and 0.94 respectively, although these values are close to those of three other indices. However, in the cities of Foumban, Ngaoundéré and Garoua, representing the western highlands, the high Guinea savannah and the Sudano-sahelian zones where built-up is more confused with soil features, overall accuracies of 97.06%, 95.29% and 74.86%, corresponding to 0.918, 0.89 and 0.42 kappa coefficients were recorded. Difference of accuracy with EBBI, NDBI and UI are up to 31.66%, confirming the NDBSUI efficiency to automate built-up extraction and unmixing from surrounding noises with less biases.

scholarly journals A Spectral Analysis of Snow in Mt. Rainier

2018 ◽  
Vol 10 (3) ◽  
pp. 20
Author(s):  
Shrinidhi Ambinakudige ◽  
Pushkar Inamdar ◽  
Aynaz Lotfata
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Thermal Emission ◽  
Major Influence ◽  
Landsat 8 ◽  
Run Off ◽  
Snow Covered Area ◽  
Covered Area ◽  
Local Water ◽  
Normalized Difference Snow Index

Snow cover helps regulate the temperature of the Earth's surface. Snowmelt recharges groundwater, provides run-off for rivers and creeks, and acts as a major source of local water for many communities around the world. Since 2000, there has been a significant decrease in the snow-covered area in the Northern Hemisphere. Climate change is the major factor influencing the change in snow cover amount and distribution. We analyze spectral properties of the remote sensing sensors with respect to the study of snow and examine how data from some of the major remote sensing satellite sensors, such as (Advanced Spaceborne Thermal Emission and Reflection Radiometer) ASTER, Landsat-8, and Sentinel-2, can be used in studying snow. The study was conducted in Mt. Rainier. Although reflectance values recorded were lower due to the timing of the data collection and the aspect of the study site, data can still be used calculate normalized difference snow index (NDSI) to clearly demarcate the snow from other land cover classes. NDSI values in all three satellites ranged from 0.94 to 0.97 in the snow-covered area of the study site. Any pollutants in snow can have a major influence on spectral reflectance in the VIS spectrum because pollutants absorb more than snow.

Remote Sensing Prospecting Deposit Model Using Aster Data: A Case Study from Southern Part of Taxkorgan Tajik Autonomous County, China

2015 ◽  
Vol 733 ◽  
pp. 124-129
Author(s):  
Hui Zhi Wu ◽  
Qi Gang Jiang ◽  
Chao Jun Bai
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Mineral Exploration ◽  
Information Source ◽  
Remote Sensing Data ◽  
Screening Methods ◽  
Data Sets ◽  
Sensing Data ◽  
Work Area ◽  
Geological Conditions

This work uses multiple types of remote sensing data to develop a model-based mineral exploration method. Data used include Worldview-2 satellite data as the main information source supplemented by QuickBird satellite data to assist in geological interpretations and ASTER satellite data to extract remote sensing anomalies. We have enhanced the spectral and spatial resolution of the remote sensing data using ENVI software. Human-computer interaction methods have been used to confirm the geological conditions. We have interpreted 24 distinct lithologic units, including various types of metamorphic and sedimentary rocks. A total of 471 remote sensing anomalies were delineated, consisting of 173 hydroxyl anomalies and 298 iron-staining anomalies. Geological background screening methods were applied to identify 98 remote sensing anomalies, of which 29 were recommended for further study. Based on the interpretation of anomalies extracted from the ASTER and other geological remote sensing data sets, we have established a typical-deposit prospecting model. In the model, we delineated remote sensing prospecting targets by considering: remote sensing anomalies, geologic bodies and structures, geophysical anomalies and geochemical anomalies. Using this model, we divided the work area into two zones based on types of mineral generation. Seven prospecting targets (one A class, three B class and three C class) were identified. Trenching and block sorting methods were conducted for field verification, and resulted in the discovery of two copper and two iron occurrences with commercial potential.

scholarly journals Geological mapping and mineral prospectivity using remote sensing and GIS in parts of Hamissana, Northeast Sudan

2021 ◽  
Vol 11 (3) ◽  
pp. 1123-1138
Author(s):  
Mohamed Taha AlMakki Mohamed ◽  
Latifa Shaheen Al-Naimi ◽  
Tochukwu Innocent Mgbeojedo ◽  
Chidiebere Charles Agoha
Keyword(s):  
Remote Sensing ◽  
Gold Mineralization ◽  
Principal Component ◽  
Original Data ◽  
Wall Rock ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Alteration Zones ◽  
Wall Rock Alteration ◽  
Rock Alteration

AbstractIn recent years, various geological activities and different mineral prospecting and exploration programs have been intensified along the Red Sea hills in order to elucidate the geological maps and to evaluate the mineral potentials. This study is therefore aimed at testing the viability of using remote sensing and geographic information system (GIS) techniques for geological mapping and prospecting for gold mineralization in the area. The study area is located in northeast Sudan and covers an area of about 1379 km2. Different digital image processing techniques were applied to Landsat 8 Operational Land Imager image in order to increase the discrimination between various lithological units and to delineate wall rock alteration which represents target zones for gold mineralization. Image sharpening was performed to enhance the spatial resolution of the images for more detailed information. Contrast stretching was applied after the various digital processing procedures to produce more interpretable images. The principal component analysis transformations yielded saturated images and resulted in more interpretable images than the original data. Several ratio images were prepared, combined together and displayed in RGB color composite ratio images. This process revealed the existence of alteration zones in the study area. These zones extend from the northeast to the southwest in the acid meta-volcanic and silica barite rocks. The enhanced satellite images were implemented in the GIS environment to facilitate the final production of the geological map at scale 1:400,000. X-ray fluorescence analyses prove that selected samples taken from the wall rock alteration zones are gold-bearing.

scholarly journals Comparison of Different Multispectral Images to Map Hydrothermal Alteration Zones in Kokap, Kulon Progo

2021 ◽  
Vol 6 (2) ◽  
pp. 86
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari
Keyword(s):  
Remote Sensing ◽  
Hydrothermal Alteration ◽  
Remote Sensing Data ◽  
Component Analysis ◽  
Landsat 8 ◽  
Accuracy Evaluation ◽  
Multispectral Images ◽  
Band Ratio ◽  
Alteration Zones ◽  
Sentinel 2

Using remote sensing data for hydrothermal alteration mapping beside saving time and reducing  cost leads to increased accuracy. In this study, the result of multispectral remote sensing tehcniques has been compare for manifesting hydrothermal alteration in Kokap, Kulon Progo. Three multispectral images, including ASTER, Landsat 8, and Sentinel-2, were compared in order to find the highest overall accuracy using principle component analysis (PCA) and directed component analysis (DPC). Several subsets band combinations were used as PCA and DPC input to targeting the key mineral of alteration. Multispectral classification with the maximum likelihood algorithm was performed to map the alteration types based on training and testing data and followed by accuracy evaluation. Two alteration zones were succeeded to be mapped: argillic zone and propylitic zone. Results of these image classification techniques were compared with known alteration zones from previous study. DPC combination of band ratio images of 5:2 and 6:7 of Landsat 8 imagery yielded a classification accuracy of 56.4%, which was 5.05% and 10.13% higher than those of the ASTER and Sentinel-2 imagery. The used of DEM together with multispectral images was increase the accuracy of hydrothermal alteration mapping in the study area.

scholarly journals Hyperspectral analysis of lithologies in the Arctic in areas with abundant lichen cover

2018 ◽  
pp. 51-55
Author(s):  
Sara Salehi
Keyword(s):  
Remote Sensing ◽  
Chemical Composition ◽  
Mineral Exploration ◽  
Spectral Characteristics ◽  
Image Data ◽  
Geological Mapping ◽  
The Arctic ◽  
Electromagnetic Spectrum ◽  
Rock Types ◽  
The Impact

Lithological mapping using remote sensing depends, in part, on the identification of rock types by their spectral characteristics. Chemical and physical properties of minerals and rocks determine their diagnostic spectral features throughout the electromagnetic spectrum. Shifts in the position and changes in the shape and depth of these features can be explained by variations in chemical composition of minerals. Detection of such variations is vital for discriminating minerals with similar chemical composition. Compared with multispectral image data, airborne or spaceborne hyperspectral imagery offers higher spectral resolution, which makes it possible to estimate the mineral composition of the rocks under study without direct contact. Arctic environments provide challenging ground for geological mapping and mineral exploration. Inaccessibility commonly complicates ground surveys, and the presence of ice, vegetation and rock-encrusting lichens hinders remote sensing surveys. This study addresses the following objectives: 1. Modelling the impact of lichen on the spectra of the rock substrate; 2. Identification of a robust lichen index for the deconvolution of lichen and rock mixtures and 3. Multiscale hyperspectral analysis of lithologies in areas with abundant lichens.

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