The Sonajil region, renowned as a part the global copper belt, is situated within Eastern Azerbaijan province of Iran. Encircling the Sonajil copper belt are distinct halos, including potassic, phyllic, argillic, and propylitic alterations. This research employs remote sensing techniques to investigate the potential presence of porphyry mineralization in this area. Initially, the required pre-processing, including geometric and radiometric corrections, was performed on the Sonajil ASTER image. Following that, a range of alteration detection techniques was applied to the ASTER data, encompassing image-based methods such as band ratioing, as well as spectrum-based approaches including Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), Mixture-Tuned Matched Filtering (MTMF), Linear Spectral Unmixing (LSU), and binary coding (BE). The results of the extracted alterations from the utilized techniques are consistent and compatible with the region's rock formations, including quartz monzonite, granodiorite, and andesite. Therefore, the possible existence of a Cu-Au porphyry deposit is confirmed by remote sensing studies. For subsequent analyses, geochemical and geophysical studies are proposed for the Sonajil area to demonstrate the existence of the porphyry deposit. The research findings and the proposed approach hold promise for identifying and targeting hydrothermally altered zones in other high-potential regions worldwide, providing a valuable tool for exploration geologists in their quest to map prospective ore deposits.

The northeast Mojave Desert in California has a high potential for rare earth element (REE) mining because of its unique geodynamic circumstances and the presence of vast carbonate platforms. This region hosts the Sulfide Queen rare-earth element mine at Mountain Pass, California, which is the only significant producer of REE ore in the United States. Evaluation of the Landsat-9 Operational Land Imager (OLI-2) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image of the northeast Mojave Desert in California indicates that several important lithologic groups and hydrothermal alteration zones can be mapped in areas with good exposure by using image-based techniques. Image processing methods, including band ratios (BR) and minimum noise fraction (MNF) transform, were used to generate thematic layers of each satellite's data. The results of this investigation demonstrate the capability of these approaches in distinguishing various lithological units from the multispectral satellite datasets.

Remote sensing aided exploration of REE-bearing carbonate and phosphate minerals distributed in the carbonatite intrusions is challenging. The electronic processes of REE oxides in VNIR and the overtones of vibrational modes of carbonate and phosphate in the SWIR are the main spectral characteristics for direct identification of REE-bearing minerals but they are generally masked by the strong spectral features of common minerals such as phyllosilicates and iron-oxides. Here, we present spectrally augmented multispectral multisensory data and compare it with hyperspectral data for direct and indirect identification of REE-bearing minerals and their spectral features in the Mountain Pass district.

Nowadays, remote sensing studies are considered as one of the best methods in mineral prospecting. Considering that most of the important deposits of the world, such as porphyry copper and epithermal gold deposits are widely associated with alteration zones. Identification of the alterations can be a significant exploratory guide for these types of deposits. The spectral difference between altered and unaltered rocks is the most important way of detecting alteration areas and thus exploring ore deposits by means of remote sensing. In this research, ASTER image was used to identify alteration areas in the Hemich Area, NE Iran. Geometric corrections were made on images in order to reduce the spatial errors caused by displacements and distortions related to sensors. Radiometric corrections were also applied to reduce the spectral errors caused by atmospheric effects. Subsequently, mineral prospectus areas were identified using false-color composite, band ratio, and principal components analysis. Since the results of these methods are grayscale images, a concentration-area fractal method was used to distinguish the regions containing the alterations. Using the results of these methods, some areas with the highest probability of mineralization were discovered, which were compatible with the ground control points.

The Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was instigated to Hyperion remote sensing imagery to map alteration minerals related to porphyry copper deposit. The DPSB clustering results were evaluated using Normalized Information Distance (NID), Normalized Mutual Information (NMI) and Modified adjusted Rand index (MARI) methods. Comparing the DPSB results with the geological map of the study area reveals the MARI of 0.2253, NMI of 0.1799 and MARI of 0.2253, respectively. To verify the extent of propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones associated with porphyry copper deposit, a total number of 24 rock samples were measured by a SVC XHR-1024i field portable spectroradiometer. Results derived from the DPSB model-based clustering algorithm show high accuracy in distinguishing propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones. It is advocated that the DPSB model-based clustering algorithm can be broadly implemented to hyperspectral and multispectral remote sensing data for detecting alteration zones associated with porphyry mineralization systems in other metallogenic provinces around the world.

Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) algorithms was applied to some selected Landsat-8 mineral indices for mapping gossan and clay-rich zones for Zn-Pb exploration in the Franklinian Basin of North Greenland. This region contains a unique potential for exploration of world-class zinc deposits. Numerous potential zones for Zn-Pb deposits were identified using the fusion technique of DPCA/ICA. Their identification was based on detecting alteration mineral patterns consist of ferric iron, ferrous iron and clay minerals within a background of sedimentary rocks using Landsat-8 spectral bands. Several zones of gossan and clay mineral assemblages were identified in the trough sequences of the Citronen Fjord, Peary Land that may represent potential undiscovered CD Zn-Pb deposits and warrant further investigation. This investigation indicates that satellite remote sensing mapping techniques can aid in identifying unknown/undiscovered Zn-Pb sulfide deposits in the High Arctic Franklinian Basin by targeting the location of alteration zones that are feasible location for mineral occurrences.

Several regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistical difficulties. Application of specialized image processing techniques is capable of revealing the hidden linearly mixed spectral sources in multispectral and hyperspectral satellite images. In this study, the application of Constrained Energy Minimization (CEM) algorithm was evaluated for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. The results of this investigation demonstrate the capability of the algorithms in distinguishing subpixel targets in the multispectral satellite data. The application of the method for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.

This article reports on the use of selected spectral image transform technique for detecting and mapping of snow algae growth using multi-temporal Landsat Thematic Mapper (TM), archived from early 80's to the recent Landsat-8 Operational Land Imager (OLI) acquired in March 2015. In-situ spectral radiometry samples during UTM-Antarctica summer 2015 expedition were used in air-to-ground correlation of the corresponding satellite data sets, later yield to retrieve snow algae occurrences in 2009–2015 summer. Multi-temporal analysis of the snow-vegetation growth extents extracted was then compared to against the climate-change effects of the corresponding area in Antarctic Peninsula. Hence, the indicator for snow-vegetation growth as effects of the climate-change could be inferred. Results indicated good agreement (Pearson's coefficient r=0.85, p<0.01) between snow-vegetation growth extent with the temperature changes measured in the corresponding area. Recent in-situ verification of the selected sites in the region confirmed the agreements.

Identification of high potential risk and susceptible zones for natural hazards of geological origin is one of the most important applications of advanced remote sensing technology in tropical environments. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan river basin, Peninsular Malaysia, which are obviously connected to geological structures and topographical features of the region. In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geologic structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides and flooding areas. A ScanSAR and two fine mode dual polarization level 3.1 images cover Kelantan state were processed for comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. Red-Green-Blue (RGB) colour-composite was applied to different polarization channels of PALSAR-2 data to extract variety of geological information. Directional convolution filters were applied to the data for identifying linear features in particular directions and edge enhancement in the spatial domain. The analysis of the data indicate that many of flooded areas were associated with high potential risk zones for hydro-geological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topography regions. Numerous landslide points were located in rectangular drainage system that associated with topographic slope of metamorphic and Quaternary rock units. Geo-hazard mitigation programmes could be conducted in the landslide recurrence regions and flooded areas for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin.

Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR) data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to analyze major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the Bentong-Raub Suture Zone (BRSZ) of Peninsular Malaysia, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. Major transcrustal lineaments such as the Bentong-Raub Suture Zone (BRSZ) and Lebir Fault Zone, ductile deformation related to crustal shortening, brittle disjunctive structures (faults and fractures) and collisional mountain range (Main Range Granites) were detected at regional scale using PALSAR ScanSAR data. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR fine and polarimetric data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for inaccessible regions in tropical environments.