Identifying Geothermal Resources Using Remotely Sensed Data

Document Type : مروری


Geothermal energy serves as a renewable and clean energy. Thanks to its great advantages such as relatively harmless, low costs and environmental friendly, it may be a good substitute for fossil fuels. In the present study, a geothermal survey is conducted in an area prone geothermal Ferdows of South Khorasan province in eastern Iran using ETM+ data Landsat 7 geo-referenced to topography map in scale 1:50000 of Ferdows city. Pixel number of thermal bands was converted to spectral radiance and then radiance temperature was measured. NDVI index was calculated from the visible bands in and near infra-red bands and subsequently radiance potential layer obtained. Earth surface temperature was determined by integrating both reflective and radiative temperatures. The method of least squares fitting, was used to produce layered zones of iron oxides and clay minerals and regions faults was extracted from map in scale 1:100.000. Through integration of produced layers using weighted overlapping method, geothermal prone area in Ferdows city was recognized. The potential geothermal of Ferdows in east part of Iran were evaluated and identified with the key factors associated with the formation of geothermal resources. Synthesizing the information layers, prone areas in order to geothermal energy utilizing were recognized. Hence, two resources of geothermal energy within the area were identified, which is spatially correlated with geothermal evidences such as hot spring and two inactive volcanoes. Based on the outcomes of this research, the remote sensing approaches are cost effective for determining surface temperature anomalies and area geological features such as alterations and rock units’ identification. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection. Keywords: Remote Sensing, Geothermal Energy, Land Surface Temperature, Landsat.