Showing papers by "Amin Beiranvand Pour published in 2018"

Mapping alteration mineral zones and lithological units in Antarctic regions using spectral bands of ASTER remote sensing data

Abstract: Geological mapping is one of the primary tasks of remote sensing. Remote sensing applications are especially useful when extreme environmental conditions inhibit direct survey such as in Antarctica. In this investigation, a satellite-based remote sensing approach was used for mapping alteration mineral zones and lithological units using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data in the Oscar II coast area, north-eastern Graham Land, Antarctic Peninsula. Specialized band ratios and band combinations were developed using visible and near infrared, shortwave infrared (SWIR) and thermal infrared spectral bands of ASTER for detecting alteration mineral assemblages and lithological units in Antarctic environments. Constrained Energy Minimization, Orthogonal Subspace Projection and Adaptive Coherence Estimator algorithms were tested to ASTER SWIR bands for detecting sub-pixels’ abundance of spectral features related to muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite. Results indicate valuable applicability of ASTER data for Antarctic geological mapping.

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

Abstract: 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.

A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment

Abstract: Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to a Multilayer Perceptron (MLP) neural network for producing an Earthquake Vulnerability Map (EVM). Finally, an EVM was produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for decision-makers and government authorities to obtain a better knowledge of a city’s vulnerability dimensions, and to adopt preparedness strategies in the future for Tabriz City. The developed hybrid framework of ANP and ANN Models can easily be replicated and applied to other urban regions around the world for sustainability and environmental management.

Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran

Abstract: This study presents the application of an artificial neural network (ANN) and geographic information system (GIS) for estimating the social vulnerability to earthquakes in the Tabriz city, Iran Thereby, seven indicators were identified and used for earthquake vulnerability mapping, including population density, household density, employed density, unemployed density, and literate people To obtain more accuracy in our analysis, all of the indicators were entered into a geographic information system (GIS) After the standardization of the data, an artificial neural network (ANN) model was applied for deriving a social vulnerability map (SVM) of different hazard classes for Tabriz city The results showed that 077% of the total area was found to be very highly vulnerable Very low vulnerability was recorded for 7631% of the total study area The comparison of data provided by (SVM) and the residential building vulnerability (RBV) of Tabriz city indicated the validity of the results obtained by ANN processes Scatter plots are used to plot the data These scatter plots indicate the existence of a strong positive relationship between the most vulnerable zones (1, 4, and 5) and the least (3, 7, and 9) of the SVM and RBV The results highlight the importance of using social vulnerability study for defining seismic-risk mitigation policies, emergency management, and territorial planning in order to reduce the impacts of disasters

Application of Landsat-8 and ASTER satellite remote sensing data for Porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran

Abstract: The Shahr-e-Babak region located in the Kerman metallogenic belt is one of the high potential segments of Urumieh–Dokhtar magmatic arc for porphyry copper and epithermal gold mineralization in the ...

Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings

Abstract: Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.

Band ratios matrix transformation (BRMT): A sedimentary lithology mapping approach using ASTER satellite sensor

Abstract: Remote sensing imagery has become an operative and applicable tool for the preparation of geological maps by reducing the costs and increasing the precision. In this study, ASTER satellite remote sensing data were used to extract lithological information of Deh-Molla sedimentary succession, which is located in the southwest of Shahrood city, Semnan Province, North Iran. A robust and effective approach named Band Ratio Matrix Transformation (BRMT) was developed to characterize and discriminate the boundary of sedimentary rock formations in Deh-Molla region. The analysis was based on the forward and continuous division of the visible-near infrared (VNIR) and the shortwave infrared (SWIR) spectral bands of ASTER with subsequent application of principal component analysis (PCA) for producing new transform datasets. The approach was implemented to ASTER spectral band ratios for mapping dominated mineral assemblages in the study area. Quartz, carbonate, and Al, Fe, Mg –OH bearing-altered minerals such as kaolinite, alunite, chlorite and mica were appropriately mapped using the BRMT approach. The results match well with geology map of the study area, fieldwork data and laboratory analysis. Accuracy assessment of the mapping result represents a reasonable kappa coefficient (0.70%) and appropriate overall accuracy (74.64%), which verified the robustness of the BRMT approach. This approach has great potential and capability for mapping sedimentary succession with diverse local–geological–physical characteristics around the world.

Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting

Abstract: The integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive fi...

Landslide Mapping and Assessment by Integrating Landsat-8, PALSAR-2 and GIS Techniques: A Case Study from Kelantan State, Peninsular Malaysia

Abstract: Integration of satellite remote sensing data and GIS techniques is an applicable approach for landslide mapping and assessment in highly vegetated regions with a tropical climate. In recent years, there have been many severe flooding and landslide events with significant damage to livestock, agricultural crop, homes, and businesses in the Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and phased array type L-band synthetic aperture radar-2 (PALSAR-2) datasets and analytical hierarchy process (AHP) approach were used to map landslide in Kelantan river basin, Peninsular Malaysia. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after flooding. The PALSAR-2 data were used for comprehensive analysis of major geological structures and detailed characterizations of lineaments in the state of Kelantan. AHP approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index, land cover, distance to drainage, precipitation, distance to fault, and distance to the road were extracted from remotely sensed data and fieldwork to apply AHP approach. The excessive rainfall during the flood episode is a paramount factor for numerous landslide occurrences at various magnitudes, therefore, rainfall analysis was carried out based on daily precipitation before and during flood episode in the Kelantan state. The main triggering factors for landslides are mainly due to the extreme precipitation rate during the flooding period, apart from the favorable environmental factors such as removal of vegetation within slope areas, and also landscape development near slopes. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire Kelantan state. Modeled/predicted landslides with a susceptible map generated prior and post-flood episode, confirmed that intense rainfall throughout Kelantan has contributed to produce numerous landslides with various sizes. It is concluded that precipitation is the most influential factor for landslide event. According to the landslide susceptibility map, 65% of the river basin of Kelantan is found to be under the category of low landslide susceptibility zone, while 35% class in a high-altitude segment of the south and south-western part of the Kelantan state located within high susceptibility zone. Further actions and caution need to be remarked by the local related authority of the Kelantan state in very high susceptibility zone to avoid further wealth and people loss in the future. Geo-hazard mitigation programs must be conducted in the landslide recurrence regions for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin. This investigation indicates that integration of Landsat-8 and PALSAR-2 remotely sensed data and GIS techniques is an applicable tool for Landslide mapping and assessment in tropical environments.

Gondwana-Derived Terranes Structural Mapping Using PALSAR Remote Sensing Data

Abstract: Gondwana-derived terranes are now separated by major faults or suture zone, which are rarely simple and easily recognizable lineaments Different association of ore mineral systems such as deposits of sediment-hosted/orogenic gold and granite-related minerals is discovered in collision and subduction zones of the Gondwana-derived terranes They are associated with large-scale, terrane-bounding fault systems and broad areas of deformation Mineralization mostly associated with structurally-controlled complex lodes, veins, sheeted veins and veinlets in diverse orientations Recognizing the structural significance of lineaments and curvilinear is very difficult in tropical, arid and Antarctic regions due to environmental obstacles Remote sensing data could be used to detect geological structures associated with suture zones between Gondwana-derived terranes especially for large inaccessible regions where fieldwork is limited or nonexistent In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to map major geological structures in the Bentong-Raub Suture Zone of Peninsular Malaysia It is one of the major structural zones in Sundaland, Southeast Asia, which forms the boundary between the Gondwana-derived the Sibumasu terrane and Sukhothai-Indochina arc Structural features associated with sediment-hosted/orogenic gold deposits in the Central Gold Belt and tin mineralization in S-type granites in the Main Range were investigated using PALSAR data and comprehensive fieldwork Results indicate that main faults strike along 340° to 350° that are intersected by many shear or lateral fault zones are high potential zone for gold mineralization in the Central Gold Belt Hydrothermally alteration mineral zones and cataclastic rocks are also the other indicators of gold mineralized veins in the gold belt High potential zones for tin mineralization are N–S strike-slip faults, fault zones and shear zones trending E–W, NE–SW and WNW–ESE in dissected crystalline granitic rocks that are associated with hydrothermal alteration zones in the Western Tin Belt Lineament analysis using PALSAR satellite remote sensing data is a useful tool for mapping major geological structural features and detection of the boundary between the Gondwana-derived terranes and detailed structural analysis of fault systems and deformation with high potential for a variety of mineral resources, especially in tropical, arid and Antarctic regions

Hydrothermal alteration mapping of mineralogical imprints associated with subtle geothermal system using mixture tuned matched filtering approach on ASTER VNIR And SWIR data

Abstract: The purpose of this study is to evaluate the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible near infrared (VNIR) and Shortwave infrared (SWIR) bands in discriminating hydrothermal alteration mineralogy related to thermal springs as proxy for identifying subtle Geothermal (GT) systems at Yankari Park in north eastern Nigeria. The area is characterized by a number of thermal springs including, Gwana, Dimmil, Mawulgo and Wikki which is used directly for recreation and tourism. A Decorrelation Stretch (DCS) transform was initially used on ASTER to highlight alteration zones and generate regions of interest (ROIs) which guided field validation and identification of associated exposed alteration zones. GPS field survey and sampling of hydrothermally altered rocks and laboratory analysis using Analytical Spectral Device (ASD) and X-Ray Diffraction (XRD) is conducted for verification. Observed and validated alteration sites (ROIs) are subsequently used to extract mean image spectra from the ASTER data. We then explored the utility of mean image spectra for mapping subtle mineralogical imprints associated to geothermal systems as proxy for identifying targets in unexplored regions by using the Mixture Tuned Match Filtering (MTMF) algorithm on ASTER VNIR to SWIR spectral subsets. The results indicate that ASTER data could reliably be used for prefeasibility stage narrowing of targets and mapping of subtle alterations using image derived spectra. These could have significant implications especially for mapping unconventional GT systems in unexplored regions.

Per-pixel and sub-pixel mapping of alteration minerals associated with geothermal systems using ASTER SWIR data

Abstract: This paper is focused on assessing the applicability of the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) shortwave infrared data in proxy mapping of subtle geothermal (GT) systems by identifying hydrothermally altered indicator minerals. The study was carried out at Yankari Park NE Nigeria. Spectral mapping is applied on ASTER data using perpixel and subpixel algorithms to extract and discriminate associated altered areas of interest. Field checks and altered rock sampling was done using GPS around the Wikki and Mawulgo thermal springs to validate results. Sampling points were used as training sites for image spectral analysis. X-Ray Diffraction results shows presence of kaolinite, quartz, hematite and dickite. This investigation demonstrates the utility of alteration mapping as a tool for GT resource exploration in uncharted regions.

Evaluation and Detection of Geothermal Potential Zones in Yankari Park, South- Central Part of Bauchi State, North-Eastern Nigeria

Abstract: Exploiting geothermal (GT) resources requires first and foremost locating suitable areas for its development. The focus of this paper is to explore the applicability of mapping GT related anomalies by identifying mineralogy and lithological features at regional scale using image enhancement techniques on Landsat 8 satellite data. A combination of established Band ratios from literature were implemented on Landsat 8 optical bands using innovative digital image processing and knowledge-based spectral information extraction techniques which enhanced surface mineralogy and possible alteration areas of interest. The results indicate that ratios using bands; 7/4, 6/3, 5/7 and 6/7, 4/3, 5/6 and 7/5, 5/4, 6/7 respectively as RGB, were unique but corroborative in enhancing and identifying; clay rich rocks, iron oxides, micas, carbonates and possible hydrothermal alteration zones related to GT anomaly. The results could have implication for GT exploration in especially unexplored regions where expensive airborne surveys are unaffordable. Keywords : Band ratios, Landsat 8 (OLI), Geothermal, Minerals