scholarly journals Utilisation De L’image Multispectrale Pour L’exploration Et La Recherche Des Ressources Minérales : État Des Connaissances Et Proposition D’un Modèle De Traitement

2018 ◽  
Vol 14 (24) ◽  
pp. 350
Author(s):  
Abdessamad El Atillah ◽  
Zine El Abidine El Morjani ◽  
Mustapha Souhassou
Keyword(s):  
Remote Sensing ◽  
Principal Component ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Geological Maps ◽  
Landsat 7 ◽  
Sentinel 2A ◽  
Terrestrial Globe ◽  
The Cost ◽  
Methods Of Treatment

Multiband space remote sensing is an indirect tool for prospecting the Earth's surface. It is very powerful especially in its applications related to the field of geology including geological mapping, mining and oil exploration. It can also significantly reduce the cost of exploration, reach inaccessible areas, guide mining research to favorable regions and reach a large surface. In this article, we highlight in details the state of knowledge in this field of research by citing the different methods and approaches carried out by several specialists who generally define the use of remote sensing for lithostructural and mineralogical mapping and particularly for the exploration and research of mineral substances. We also create methods derived from the aforementioned methods of treatment by means of a logical analogy between the different bands of several satellites of observation of the terrestrial globe, particularly between : Landsat 7 ETM +; Landsat 8 OLI / TIRS; Aster and Sentinel 2A. At the end, we synthesize these results by proposing a multispectral image-processing model that can be applied directly. This model starts with the calculation of Optimum Index Factor (OIF), which allows us to detect only the most important colored composites; and the reports of the bands, rations, the principal component analysis, ACI and the classification that allow the realization of a lithological and mineralogical mapping as well as maps of lineaments by means of directional filters. The validity of the models is tested by comparison with field data and geological maps of the studied site.

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 MONITORING AND ASSESSMENT OF ECOLOGICAL CHANGE IN COASTAL CITIES BASED ON RSEI

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 461-470
Author(s):  
X. Y. Liu ◽  
X. X. Zhang ◽  
Y. R. He ◽  
H. J. Luan
Keyword(s):  
Remote Sensing ◽  
Water Body ◽  
Principal Component ◽  
Vegetation Coverage ◽  
Weighting Coefficient ◽  
Landsat 8 ◽  
Ecological Change ◽  
Remote Sensing Images ◽  
Environment Change ◽  
Sentinel 2A

Abstract. With the speeding up of urbanization process, ecological problems, such as unsustainable land use and environmental pollution,have emerged one after another in cites. Nowadays, green development and ecological priority are the important concepts and trends of the current new urban planning in China. In this study, Pingtan County, a coastal city in Fujian Province, China, was taken as the research area. Based on two Landsat 8 remote sensing images (2016, 2017), and two Sentinel-2A remote sensing images (2016, 2017), we first adopt the modified normalized water body index (MNDWI) to mask the water body. Four indicators, including greenness, humidity, dryness and heat were extracted to synthesize the remote sensing ecological index (RSEI), which were obtained by principal component analysis method. Based on the RSEI values acquired from Landsat 8 and Sentinel-2A images, the ecological environment change trend in Pingtan County was evaluated .The experimental results show that: 1) The RSEI indicators based on Landsat 8 and sentinel data all show a downward trend, but due to due to the influence of image spatial resolution and PCA weighting coefficient, the RSEI index has different degrees of decline. 2) The main reason for the decline in RSEI is the increase in NDSI indicators. Compared with July 2016, the bare ground increased in April 2017. Although the NDVI has increased, the overall trend is still declining. Therefore, it is necessary to ecologically return farmland and improve vegetation coverage in the future development process. 3) In recent years, the ecological quality of new construction land near drinking water sources has declined, so it is necessary to strengthen monitoring of changes in the region.

scholarly journals A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: A case study of central region Kenya

2015 ◽  
Vol XL-7/W3 ◽  
pp. 897-903 ◽  
Author(s):  
M. W. Mwaniki ◽  
M. S. Moeller ◽  
G. Schellmann
Keyword(s):  
Remote Sensing ◽  
Knowledge Base ◽  
Remote Sensing Data ◽  
Factor Loading ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Data ◽  
Landsat 7 ◽  
Loading Analysis

Availability of multispectral remote sensing data cheaply and its higher spectral resolution compared to remote sensing data with higher spatial resolution has proved valuable for geological mapping exploitation and mineral mapping. This has benefited applications such as landslide quantification, fault pattern mapping, rock and lineament mapping especially with advanced remote sensing techniques and the use of short wave infrared bands. While Landsat and Aster data have been used to map geology in arid areas and band ratios suiting the application established, mapping in geology in highland regions has been challenging due to vegetation land cover. The aim of this study was to map geology and investigate bands suited for geological applications in a study area containing semi arid and highland characteristics. Therefore, Landsat 7 (ETM+, 2000) and Landsat 8 (OLI, 2014) were compared in determining suitable bands suited for geological mapping in the study area. The methodology consist performing principal component and factor loading analysis, IHS transformation and decorrelation stretch of the FCC with the highest contrast, band rationing and examining FCC with highest contrast, and then performing knowledge base classification. PCA factor loading analysis with emphasis on geological information showed band combination (5, 7, 3) for Landsat 7 and (6, 7, 4) for Landsat 8 had the highest contrast and more contrast was enhanced by performing decorrelation stretch. Band ratio combination (3/2, 5/1, 7/3) for Landsat 7 and (4/3, 6/2, 7/4) for Landsat 8 had more contrast on geologic information and formed the input data in knowledge base classification. Lineament visualisazion was achieved by performing IHS transformation of FCC with highest contrast and its saturation band combined as follows: Landsat 7 (IC1, PC2, saturation band), Landsat 8 (IC1, PC4, saturation band). The results were compared against existing geology maps and were superior and could be used to update the existing maps.

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 Use of the Sentinel-2A Multispectral Image for Litho-Structural and Alteration Mapping in Al Glo’a Map Sheet (1/50,000) (Bou Azzer–El Graara Inlier, Central Anti-Atlas, Morocco)

2019 ◽  
Vol 54 (3) ◽  
pp. 73-96
Author(s):  
Abdessamad El Atillah ◽  
Zine El Abidine El Morjani ◽  
Mustapha Souhassou
Keyword(s):  
Hydrothermal Alteration ◽  
Thermal Emission ◽  
Principal Component ◽  
Alteration Zone ◽  
Efficient Manner ◽  
Geological Maps ◽  
Analysis Technique ◽  
Landsat 7 ◽  
Earth Observation Satellites ◽  
Sentinel 2A

Abstract The discovery of natural resources remains the main mission of Earth observation satellites, especially in geographical areas that have a very difficult accessibility as those of the Bou Azzer–El Graara inlier (Central Anti-Atlas, Morocco). This work investigates the use of different satellite data, such as Sentinel-2A’s multispectral imagery, in order to direct the prospection program in an efficient manner, saving both time and cost. The image processing methods of Landsat 7, 8, and “Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)” (30 m/15 m) were used to create methods for Sentinel-2A images (10 m). The red, green, blue (RGB) image 12.8.2, 11/12.11/2.11/8, principal component (PC) 1,2,3(11.12.2), and other new images were the result of principal component analysis (PCA), and classification by the Iterative Self-Organizing Data Analysis Technique (ISODATA) and K-Means allowed realization of a lithological cartography as well as maps of lineaments through directional filters and the ratio of 11/12 for hydrothermal alteration zone mapping. The assembly of lithological, structural, and hydrothermal alteration data gave an idea of the mineralogy of the study area. Validity of the results was tested by comparison with the field data and the geological maps of the studied site (62% for the hydrothermal alteration zone, 81% for the lithological map, and 74% for the structural map).

scholarly journals Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil)

2018 ◽  
Vol 90 (2 suppl 1) ◽  
pp. 1987-2000 ◽  
Author(s):  
FERNANDA WATANABE ◽  
ENNER ALCÂNTARA ◽  
THANAN RODRIGUES ◽  
LUIZ ROTTA ◽  
NARIANE BERNARDO ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Landsat 8 ◽  
Sentinel 2A

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

scholarly journals Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data

2019 ◽  
Vol 23 (4) ◽  
pp. 265-282
Author(s):  
Rafael Andrés Calderón-Chaparro ◽  
German Vargas-Cuervo
Keyword(s):  
Remote Sensing ◽  
Soil Temperature ◽  
Field Data ◽  
Hot Springs ◽  
Landsat 8 ◽  
Geothermal Resources ◽  
Temperature Index ◽  
Landsat 7 ◽  
Geothermal Region

Geothermal resources (e.g. hot springs) are found with the help of field techniques, such as geological, geochemistry and geophysical. These techniques in some occasions are difficult to apply because of the limit access to the research area, rising operational costs and constrained spatially the exploration areas. The thermal infrared (TIR) remote sensing is an important tool for the exploration of geothermal resources, due to the low cost and high efficiency in the study of large geographic areas. The aim of this study is to use thermal imagery of satellite remote sensing and combined with geological-geophysical data, for spatial determination of exploratory prospects of hot springs in the geothermal region of Paipa, Boyacá. The images used in this study are from satellites Landsat-7 ETM+, Landsat-8 OLI/TIRS, MODIS, ALOS-PALSAR and Pléiades. Also, field data is used, such as soil temperature, surface temperature, air temperature, relative humidity, atmospheric pressure and thermal imagery of surface geothermal manifestations. The Landsat thermal bands were radiometrically calibrated, then atmospherically and surface emissivity corrected, applying single channel and split window algorithms, for Landsat-7 ETM+ and Landsat-8 TIRS, respectively. The field data helped to correct the thermal bands. And the soil temperature data are used to create a subsurface temperature map at 1-meter depth. Once primary and secondary data is had, in a geographic information system (GIS) is implemented an unweighted spatial model, which use four input indicators (satellite temperature index, soil temperature index, structural lineaments index and iso-resistivity index) to determine the areas with higher probability to find geothermal fluids. Six prospects are highlighted for hydrothermal fluid extraction, in which two of them are already known. Results allow to concluded that thermal remote sensing are useful to map geothermal anomalies in the Paipa region, and by using these anomalies plus geological-geophysical information is possible to determine exact exploration areas.

scholarly journals Integrating Landsat 7 and 8 data to improve basalt formation classification: A case study at Buon Ma Thuot region, Central Highland, Vietnam

2019 ◽  
Vol 11 (1) ◽  
pp. 901-917
Author(s):  
Ngo Van Liem ◽  
Dang Van Bao ◽  
Dang Kinh Bac ◽  
Nguyen Hieu ◽  
Do Trung Hieu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Band ◽  
Landsat 8 ◽  
Central Highland ◽  
Band Ratios ◽  
Landsat 7 ◽  
Cenozoic Basalt ◽  
Geological Map ◽  
Geological Formations

Abstract Cenozoic basalt regions contain various natural resources that can be used for socio-economic development. Different quantitative and qualitative methods have been applied to understand the geological and geomorphological characteristics of basalt formations. Nowadays the integration of remote sensing and geographic information systems (GIS) has become a powerful method to distinguish geological formations. In this paper, authors combined satellite and fieldwork data to analyze the structure and morphology of highland geological formations in order to distinguish two main volcanic eruption episodes. Based on remote sensing analysis in this study, different spectral band ratios were generated to select the best one for basalt classification. Lastly, two spectral combinations (including band ratios 4/3, 6/2, 7/4 in Landsat 8 and 3/2, 5/1, 7/3 in Landsat 7) were chosen for the Maximum Likelihood classification. The final geological map based on the integration of Landsat 7 and 8 outcomes shows precisely the boundary of the basalt formations with the accuracy up to 93.7%. This outcome contributed significantly to the correction of geological maps. In further studies, authors suggest the integration of Landsat 7 and 8 data in geological studies and natural resource and environmental management at both local and regional scales.

scholarly journals ZAB RIVER (IRAQ) SINUOSITY AND MEANDERING ANALYSIS BASED ON THE REMOTE SENSING DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 91-95
Author(s):  
B. Kalantar ◽  
M. H. Ameen ◽  
H. J. Jumaah ◽  
S. J. Jumaah ◽  
A. A. Halin
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Geographic Information Systems ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Sinuosity Index ◽  
River Region ◽  
Landsat 7 ◽  
Landsat 5 Tm ◽  
River Migration

Abstract. This work studies the meandering and change of paths along the Zab River in Iraq. Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 (2-sets) images were acquired from the years 1989, 1999, 2015 and 2019, respectively, which were used together with Remote sensing and Geographic Information Systems (GIS) techniques to study the changes. To determine the river/stream shape, the Sinuosity Index was calculated to classify Zab River segments into either the straight, sinuous or meandering class. Our findings via image analysis show coarse river migration and that most river segments fall into the two classes of sinuous and meander. In addition, it seems that the east bank of the Zab River region of the basin has extremely shifted where the river passes near the Kirkuk governorate.

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