Environmental quality monitoring
Aliyeh Seifi Seifi; Mahdieh Hosseinjanizadeh; Hojatollah Ranjbar; Mehdi Honarmand
Abstract
The main objective of this research is to discriminate secondary iron minerals and investigate changes caused by their relocation during mining activities using multispectral satellite data collected over an 11-year period. To achieve this aim, MF and CEM performed using USGS library spectra, field spectra ...
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The main objective of this research is to discriminate secondary iron minerals and investigate changes caused by their relocation during mining activities using multispectral satellite data collected over an 11-year period. To achieve this aim, MF and CEM performed using USGS library spectra, field spectra and image spectra to identify secondary iron minerals and then the best result of the mineral identification stage implemented for changes detection of secondary iron minerals. The results of secondary iron minerals identification by MF method and images spectra have compatibility with the field data and laboratory analysis, so that the goethite is the most abundant secondary iron mineral in Darrehzar mine area. The change detection algorithm at the study area showed that mining activities and geochemical conditions cause change in the surface by transferring secondary iron minerals. The employed method including identifying minerals and detecting change of them allows users to find an effective technique for identifying the target material and apply it in the subtraction algorithm for change detection. Applying this method can be suggestions for future research in target change detection.
Samira Shayganpour; Majid Hashemi Tangestani
Abstract
Rock outcrops are generally covered by vegetation and the Quaternary deposits so that impede their enhancement on the satellite imagery. This fact leads that identification of pixels of rock outcrops be a challenging task for field sampling such as in lithogeochemical surveys. Therefore, in order to ...
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Rock outcrops are generally covered by vegetation and the Quaternary deposits so that impede their enhancement on the satellite imagery. This fact leads that identification of pixels of rock outcrops be a challenging task for field sampling such as in lithogeochemical surveys. Therefore, in order to map the rock type outcrops, it is required, first, to estimate the distribution of vegetation and the Quaternary deposits as the major Earth surface components. This paper is an attempt to map the outcrops of rock types as a prerequisite for lithogeochemical sampling surveys. To evaluate the efficacy of approach, geochemical anomalies of Cu, Au, and Fe in samples collected from enhanced rock outcrops of a metamorphosed area were analyzed. In order to obtain the objectives of study, we firstly utilized the (ML), (SAVI), and mixture-tuned matched filtering (MTMF) methods on reflective bands of advanced space-borne (ASTER) to map the Quaternary deposits, vegetation, and lithological units in Kowli-Kosh metamorphic complex, SW Iran. Pixels matched to lithological units were identified wherever the matched filter (MF) scores were > 0.65. These areas were then cross-tabulated with vegetation and Quaternary maps to differentiate the representative areas of rock outcrops. A grid network was subsequently generated and overlaid on the map of rock outcrops, and the rock chip samples for lithogeochemical analysis were collected from cells containing more than 15 pixels of rock outcrops. The spatial distribution analysis of rock types and the geochemical statistics showed the relationships between outcrops and the anomalies of the desired elements.
Mineral exploration and mining
Ahmad Pourshamsoddin Motlagh; Hojjatollah Ranjbar
Abstract
The purpose of this study was to use the multisensor images for the exploration of porphyry copper deposits in the southeast of Kerman province, Rabor region. ASTER, Sentinel-2A and IKONOS images were used. IARR correction was performed on IKONOS, Sentinel-2A and 5 bands of the ASTER TIR dataset and ...
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The purpose of this study was to use the multisensor images for the exploration of porphyry copper deposits in the southeast of Kerman province, Rabor region. ASTER, Sentinel-2A and IKONOS images were used. IARR correction was performed on IKONOS, Sentinel-2A and 5 bands of the ASTER TIR dataset and FLAASH correction was applied on ASTER VNIR-SWIR bands, respectively. Upon initial identification of alteration zones and geochemical anomalies, these hydrothermal alterations and anomalies were visited and samples were collected for laboratory studies. Thin sections were prepared and studied under the microscope, and selected samples were used for spectroradiometric study. Argillic, sericitic and propylitic hydrothermal alteration zones were identified with SFF method by using samples’ spectra. Iron oxide minerals were also characterized using the b4/b2 ratio of Sentinel-2A and b3/b1 ratio of IKONOS. Bands 2 and 4 of Sentinel-2A were combined with ASTER SWIR data for identifying areas with sericitic and argillic alteration types that are stained with iron oxides. The results of the combination of the selected bands of Sentinel-2A and ASTER images gave better results due to the higher resolution. Field observations and laboratory studies were used to validate the results. Geochemical Mineral Potential Index (GMPI) method also identified porphyry copper potential areas and was used as a validation method. Finally, the alteration zones were subdivided into eight zones for detailed exploration.
