scholarly journals Identification of clays and Fe oxide minerals rich alteration zones using a Landsat 8 image of Pu Sam Cap area, Lai Chau

2021 ◽  
Vol 62 (2) ◽  
pp. 12-24
Author(s):  
Hieu Trung Tran ◽  
Cuong Quoc Tran ◽  
Dung My Tran ◽  
Chung Minh Bui ◽  
Dung Van Chu ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Mineral Exploration ◽  
Principal Component ◽  
Landsat 8 ◽  
Remote Sensing Images ◽  
Band Ratio ◽  
Alteration Zones ◽  
Tropical Area ◽  
Important Sign ◽  
Hydrothermal Alteration Zones

The hydrothermal alteration zones are the important sign for mineral exploration and can be identified by remote sensing images completely, but this is limited due to the effect of vegetable. We address this problem by a method called “Directed Principal Component Analysis” (DPCA) that involves calculating principal components on two input band ratio images. One ratio is a geological discriminant, confused by the presence of vegetation; the second ratio is chosen for its suitability as a vegetation index. DPCA applied on Landsat 8 image in Pu Sam Cap area, Lai Châu characteristied by argilic alteration, sericite alteration, etc., with the typical minerals like kaolinite, illite, etc., and pyrite, chalcopyrite, magnetite; specularite, etc., The results have identified Fe - rich zones in Bai Bang and Nam Tra areas; clay minerals are concentrated mainly in Nam Tra area and along the main faults. The results are also compared with previous research data and fieldtrip data that shows similarity and feasibility. This paper indicated limitation of Landsat image such as spatial resolution, spectral resolution, etc., when applied in the tropical area.

scholarly journals The Exploration of Metallic Deposits Using Satellite Image Processing in the Parwan-Panjsher Area, Afghanistan

2021 ◽  
Vol 6 (1) ◽  
pp. 30
Author(s):  
Mahdi Khalaj ◽  
Ziba Karimi ◽  
Mohsen Rabbani
Keyword(s):  
Satellite Image ◽  
Principal Component ◽  
Field Studies ◽  
High Heat ◽  
Landsat 8 ◽  
Band Ratio ◽  
Copper Mineralization ◽  
Hindu Kush ◽  
Carbonate Host Rock ◽  
Resource Data

Unique tectonic features have resulted in diverse metallic and non-metallic mineralization in Afghanistan. Hence, this paper is focused on the development of exploration and mineral resource data in Afghanistan. The study area is located in the western Hindu Kush tract and on the northern verge of the Hari Rud–Panjsher fault, Afghanistan, which mainly associates with the western Hindu Kush and Badakhshan plutonic belts. The rock units include crystalline limestones and diabase formed during the Paleozoic era and Triassic period. The aim of this study was to employ Remote Sensing (RS) methods by using the Landsat-8 satellite and ASTER sensor to spot iron and copper mineralization zones in the Parwan-Panjsher area. Therefore, Band Composition, Principal Component Analysis (PCA), and Band Ratio were applied to identify the iron oxide minerals. The detected area provided by satellite images had very good conformability with the results of field studies. Furthermore, mineralization of carbonate host-rock iron and Fe–Cu–(Au) skarn were observed during the field surveys. Hematite–Magnetite, Chalcopyrite, and pyrite mineralization have resulted from the injection of various diabase subvolcanic into carbonate units. Additionally, high heat flow has caused widespread marble formation in the area. The results were supported by microscopic and geochemical studies.

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 HYDROTHERMAL ALTERATION ZONES DETECTION IN LIMNOS ISLAND, THROUGH THE APPLICATION OF REMOTE SENSING

2017 ◽  
Vol 50 (3) ◽  
pp. 1596 ◽  
Author(s):  
A. Anifadi ◽  
Is. Parcharidis ◽  
O. Sykioti
Keyword(s):  
Hydrothermal Alteration ◽  
Field Work ◽  
High Spectral Resolution ◽  
General Distribution ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Alteration Zones ◽  
Multispectral Data ◽  
Band Ratios ◽  
Hydrothermal Alteration Zones

In this study we use Landsat 8 OLI satellite imagery in order to identify and map alteration zones in Limnos island (N. Aegean, Greece). Pre-processing included sea and vegetation masking. In order to enhance spatial resolution, data fusion to 15m is performed. A lineament map is extracted from the panchromatic image that gives the general tectonic view of the island. The detection and mapping of alteration minerals is performed using specific band ratios and consequent composite images. The colour composite using bands 10, 11, 7 (RGB) show the spectral signature and general distribution of silica. Band ratios 6/7, 4/2, 6/5, reveal alteration zones containing iron oxides, clay alteration and ferrous minerals correspondingly. The aforementioned analysis has shown that hydrothermally alteration areas in Limnos are located in the west part of the island and at the Fakos Peninsula, Sardes, Roussopouli and Paradeisi hill. These areas are compared and validated with the reported field work. We conclude that hydrothermal alteration zones can indeed be detected and mapped using medium resolution satellite multispectral data. However, for the identification and mapping of specific types of rocks and minerals, a sensor with high spectral resolution is required. 

scholarly journals SATELLITE-DRIVEN ASSESSMENT OF SURFACE URBAN HEAT ISLANDS IN THE CITY OF ZAGREB, CROATIA

2020 ◽  
Vol V-3-2020 ◽  
pp. 757-764
Author(s):  
A. Krtalić ◽  
A. Kuveždić Divjak ◽  
K. Čmrlec
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Principal Component ◽  
Urban Heat Islands ◽  
City Centre ◽  
Landsat 8 ◽  
Heat Islands ◽  
Critical Areas ◽  
Urban Heat ◽  
The City

Abstract. This study aims to assess surface urban heat islands (SUHIs) pattern over the city of Zagreb, Croatia, based on satellite (optical and thermal) remote sensing data. The spatio-temporal identification of SUHIs is analysed using the 12 sets of Landsat 8 imagery acquired during 2017 (in each month of the year). Vegetation cover within the city boundaries is extracted by using Principal Component Analysis (PCA) data fusion method on calculated three vegetation indices (VI): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Ratio Vegetation Index (RVI) for each set of bands. The first principal component was used to compute the land surface temperature (LST) and deductive Environmental Criticality Index (ECI). As expected, the relationship between LST and all VI scores shows a negative correlation and is most negative with RVI. The environmentally critical areas and the patterns of seasonal variations of the SUHIs in the city of Zagreb were identified based on the LST, ECI and vegetation cover. The city centre, an industrial area in the eastern part and an area with shopping centers and commercial buildings in the western part of the city were identified as the most critical areas.

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 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.

ESTIMATIVA DE MUDANÇAS TEMPORAIS COM O CÁLCULO DE ÍNDICES DE VEGETAÇÃO DO MUNICÍPIO DE ITABERÁ (SP)

2017 ◽  
Vol 32 (2) ◽  
pp. 195
Author(s):  
Ana Clara De Barros ◽  
Amanda Aparecida De Lima ◽  
Felipe De Souza Nogueira Tagliarini ◽  
Zacarias Xavier de Barros
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Near Infrared ◽  
Temporal Analysis ◽  
Landsat 8 ◽  
Remote Sensing Images ◽  
Chlorophyll Contents ◽  
Spectral Bands ◽  
Vegetation Water ◽  
Images Processing

O presente trabalho teve como objetivo realizar a análise temporal da cobertura vegetal, num período de 10 anos do município de Itaberá-SP, utilizando os índices de vegetação NDVI e NDWI por meio de imagens de satélite. Do ano de 2005 foram utilizadas duas imagens do Landsat 5 de órbita/ponto 221/76 e 221/77 e uma imagem de 2015 do Landsat 8, órbita/ponto 221/76. As bandas espectrais utilizadas foram: 3,4 e 5 do Landsat 5 e 4,5 e 6 do Landsat 8 que correspondem aos comprimentos de ondas do vermelho (RED), infravermelho próximo (NIR) e infravermelho médio (SWIR1), respectivamente. Através das análises dos índices, constatou que as áreas que possuem baixos valores de NDVI também possuem baixos valores de NDWI, o que indica uma vegetação que sofre estresse hídrico e com baixo teor de clorofila. Os valores mais altos indicam vegetação fotossinteticamente ativa, que contêm maior teor de umidade.PALAVRAS-CHAVE: Sensoriamento remoto, processamento de imagens, cobertura vegetal. TEMPORAL ANALYSISUSING VEGETATION INDEX OF VEGETATION COVER IN ITABERA (SP)ABSTRACT: The objective of this work was to carry out the temporal analysis of the vegetation cover, in a period of 10 years of Itaberá-SP county, making use of the vegetation index NDVI and NDWI of satellites images. Two Landsat 5’s images of 2005 with path/row 221/76 and 221/77 and one Landsat 8’s image, path/row 221/76 were used. The spectral bands used ware: 3, 4 and 5 of the Landsat 5 and 4, 5 and 6 of the Landsat 8 that correspond to red waves lengths (RED), near infrared (NIR) and medium infrared (SWIR1), respectively. It was found that areas with low NDVI values also have low NDWI values, indicating vegetation water stress and low chlorophyll contents. The highest values indicate Photosynthetically active vegetation, which contain higher moisture contents.KEYWORDS: Remote sensing, images processing, vegetal cover.

scholarly journals Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data

2020 ◽  
Vol 12 (8) ◽  
pp. 1261 ◽  
Author(s):  
Hodjat Shirmard ◽  
Ehsan Farahbakhsh ◽  
Amin Beiranvand Pour ◽  
Aidy M Muslim ◽  
R. Dietmar Müller ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Dimensionality Reduction ◽  
Hydrothermal Alteration ◽  
Mineral Exploration ◽  
Transformation Techniques ◽  
Thematic Layers ◽  
Alteration Zones ◽  
Reduction Techniques ◽  
Dimensionality Reduction Techniques ◽  
Hydrothermal Alteration Zones

There are a significant number of image processing methods that have been developed during the past decades for detecting anomalous areas, such as hydrothermal alteration zones, using satellite images. Among these methods, dimensionality reduction or transformation techniques are known to be a robust type of methods, which are helpful, as they reduce the extent of a study area at the initial stage of mineral exploration. Principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF) are the dimensionality reduction techniques known as multivariate statistical methods that convert a set of observed and correlated input variables into uncorrelated or independent components. In this study, these techniques were comprehensively compared and integrated, to show how they could be jointly applied in remote sensing data analysis for mapping hydrothermal alteration zones associated with epithermal Cu–Au deposits in the Toroud-Chahshirin range, Central Iran. These techniques were applied on specific subsets of the advanced spaceborne thermal emission and reflection radiometer (ASTER) spectral bands for mapping gossans and hydrothermal alteration zones, such as argillic, propylitic, and phyllic zones. The fuzzy logic model was used for integrating the most rational thematic layers derived from the transformation techniques, which led to an efficient remote sensing evidential layer for mineral prospectivity mapping. The results showed that ICA was a more robust technique for generating hydrothermal alteration thematic layers, compared to the other dimensionality reduction techniques. The capabilities of this technique in separating source signals from noise led to improved enhancement of geological features, such as specific alteration zones. In this investigation, several previously unmapped prospective zones were detected using the integrated hydrothermal alteration map and most of the known hydrothermal mineral occurrences showed a high prospectivity value. Fieldwork and laboratory analysis were conducted to validate the results and to verify new prospective zones in the study area, which indicated a good consistency with the remote sensing output. This study demonstrated that the integration of remote sensing-based alteration thematic layers derived from the transformation techniques is a reliable and low-cost approach for mineral prospectivity mapping in metallogenic provinces, at the reconnaissance stage of mineral exploration.

scholarly journals Protocolo Metodológico para Obtenção dos Valores de Reflectância e de NDVI de Imagens Landsat 8/OLI Utilizando LEGAL

2021 ◽  
Vol 14 (2) ◽  
pp. 869
Author(s):  
João Pedro Ocanha Krizek ◽  
Luciana Cavalcanti Maia Santos
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Environmental Parameters ◽  
Biomass Productivity ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Remote Sensing Images ◽  
De Se ◽  
Correct Estimation

A obtenção dos valores de reflectância se mostra imprescindível para se calcular índices de vegetação, como o NDVI (Normalized Difference Vegetation Index). Este índice é utilizado para classificar a distribuição global da vegetação e para inferir variáveis ecológicas e ambientais, como a produção de fitomassa.  Apesar disso, não é incomum encontrar trabalhos que utilizam os números digitais (ND) para a obtenção direta dos índices de vegetação; entretanto, tais números digitais não representam valores físicos reais e, portanto, não podem ser utilizados diretamente para o cálculo do NDVI. Assim, o objetivo deste artigo é demonstrar um protocolo metodológico para a conversão dos ND das imagens Landsat 8/OLI em valores de reflectância e a subsequente obtenção do NDVI, através da linguagem LEGAL (Linguagem Espacial para Geoprocessamento Algébrico), e, dessa forma, possibilitar a replicação e execução de outras pesquisas que visem obter esse índice de vegetação no software SPRING. Além disso, objetivou-se também demonstrar a importância da conversão dos ND em reflectância, a partir da comparação de uma imagem NDVI gerada através da reflectância com a mesma imagem NDVI gerada por meio dos dados brutos. Os resultados apontaram que a obtenção do NDVI através dos valores brutos de imagens de sensoriamento remoto, sem a necessária conversão dos números digitais em valores reais de reflectância, leva a resultados incorretos na estimativa de dados ecológicos da vegetação, subestimando a fitomassa. Dessa forma, esse trabalho ressalta a importância de se seguir um protocolo metodológico para a estimativa correta da fitomassa, produtividade e outros parâmetros da vegetação.   Methodological protocol for obtaining reflectance and NDVI values from Landsat 8/OLI images using LEGALA B S T R A C TObtaining reflectance values is essential for calculating vegetation indices, such as the NDVI (Normalized Difference Vegetation Index). This index is used to classify the global distribution of vegetation and to infer the ecological and environmental parameters such as phytomass production. Nevertheless, it is common to find works that use digital numbers (DN) to directly obtain vegetation indices; however, such digital numbers do not represent actual physical values and therefore cannot be used directly for NDVI calculation. Thus, this paper aims to demonstrate a methodological protocol for DN conversion of Landsat 8/OLI images into reflectance values and then for obtaining NDVI through the LEGAL (Spatial Language for Algebraic Geoprocessing). Therefore, this protocol enables the replication and execution of other studies aimed to obtain this vegetation index using SPRING. In addition, the objective was also to demonstrate the importance of converting DN to reflectance by comparing an NDVI image generated from reflectance with the same NDVI image generated through the raw data. The results showed that obtaining the NDVI through the raw values of remote sensing images, without the conversion of digital numbers to real reflectance values, leads to incorrect results in the estimation of ecological vegetation data, underestimating phytomass, thus emphasizing the importance of following a methodological protocol for the correct estimation of biomass, productivity and other phytological parameters.Keywords: protocol, NDVI, reflectance, Landsat 8, SPRING

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