Detection of geological structures by remote sensingmethods using satellite images

The exploration of natural resources to meet the raw material needs of developing and advanced societies is increasingly gaining importance. However, these resources are limited. Therefore, it has become extremely critical to reach information and results quickly and efficiently using the right technology and effective methods. Societies should aim to work with fast and efficient methods, making the most of technology to discover and utilize raw material resources. The use of remote sensing methods provides significant advantages in identifying the current status and potential of underground and surface natural resources, as well as monitoring changes over time. These methods enable the acquisition of accurate, fast, and cost-effective data. As a result, remote sensing techniques optimize data collection and analysis processes, leading to time and cost savings during the evaluation of underground and surface natural resources. Additionally, they serve as effective tools for monitoring the current status and tracking changes. Remote sensing is a widely used method in the mining sector. Various satellite instruments located in the atmosphere or space are used to obtain information from objects without direct contact. This technique is widely applied not only in mining but also in geology, atmospheric science, agriculture, geographic information systems, oceanography, environmental studies, and cartography, as well as military fields. The remote sensing method is based on spectral analysis techniques used for mapping faults, fractures, and fissures, as well as detecting mineral-rich rocks for determining the locations of intense mineralization and formation areas. Remote sensing aims to examine objects on the Earth's surface using data collected from different bands of the electromagnetic spectrum (usually visible and infrared). These data represent numerical values reflecting the spectral signatures or characteristics of objects. Band ratioing involves using these spectral values to create ratios for detecting specific object features. The band ratioing method can be used to emphasize differences between spectral signatures or highlight specific attributes. For instance, the ratio of data obtained from the infrared (infrared) and green bands, reflecting plant chlorophyll activity, can be used to determine the health status of vegetation. This method enables the extraction of information about plant health, such as stress, diseases, or nutrient deficiencies. Band ratioing is also employed in other fields to analyze and classify surface features. For instance, the ratio of data obtained from blue and red bands can be used to distinguish between water and terrestrial areas. However, the band ratioing technique may require different band combinations depending on the object and application. Band ratioing provides a fast and effective method for analyzing surface features in remote sensing data. However, achieving successful results requires the careful selection of appropriate band combinations and meticulous data analysis. Band ratios used in remote sensing involve mathematically ratioing bands encompassing two different energy ranges. The resulting images are grayscale. Based on the energies of the ratioed bands and the response of the desired mineral to these energies, the images express results in various tones of light or dark colors. Landsat satellites play an indispensable role in the field of remote sensing. Utilizing these data to monitor environmental changes on Earth's surface and manage natural resources is of significant importance in sustainability and environmental sciences. The remote sensing data provided by Landsat satellites assists humanity in gaining a better understanding of the Earth and taking measures for the future. Minerals are essential economic resources for humans and hold great significance in terms of natural resource management. Effectively identifying and managing these resources are crucial for sustainability. Remote sensing data from Landsat satellites serve as an important tool in detecting mining areas. Mining areas possess distinct spectral signatures that can be detected using Landsat data. For instance, the reflective properties of metallic minerals are prominently visible in infrared bands. Hence, potential mining sites can be identified by analyzing Landsat imagery. In this study, Landsat satellite images were utilized to detect iron mineralization within the study area and establish a correlation with fieldwork conducted on-site. In the study area, a series of geophysical measurements were taken to determine the distribution, direction, and approximate reserves of hematite ore. Before conducting geophysical measurements, a literature review was performed to establish the method's priority and methodology. Initially, the area to the south of the open mining operation was investigated systematically with a 5m x 5m grid, covering an area of approximately 110m x 70m, using two-dimensional geophysical methods: Natural Potential and Magnetic Method. In order to determine the relationship between ore occurrences and the rocks surrounding them, as well as their structural features and subsurface distribution, two-dimensional electrical resistivity measurements were conducted at 12 survey profiles, and one-dimensional vertical electrical resistivity measurements were made at three points within the designated areas of the study site. Observations in the study area include hematite, limestone, graphite, graphite schist, limonite, and clayey-sandy units. Hematite and graphite occurrences hold economic value and are limited to areas near faults and in association with surrounding rocks. Faults where occurrences take place are usually shallow and close to the surface. The fragmentation of limestone at the surface is mainly caused by faulting, allowing them to reach the Earth's surface through weak environments. Secondary and tertiary faults in the study area contain ore. As a result of evaluating the images obtained through remote sensing techniques and correlating them with geological and geophysical studies conducted in the field, the locations of existing deposits were successfully determined.