Reza Parhizcar isalu; Khalil Valizadeh Kamran; Bakhtiar Faizizadeh
Abstract
Extended Abstract
Introduction
Geothermal energy is one of the major sources of new and environmentally friendly energieswhich, if used correctly and based on environmental parameters, plays an important role in the energy balance of the country and the goals of sustainable development.However, detecting ...
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Extended Abstract
Introduction
Geothermal energy is one of the major sources of new and environmentally friendly energieswhich, if used correctly and based on environmental parameters, plays an important role in the energy balance of the country and the goals of sustainable development.However, detecting and exploring sources of this energy using modern and low cost methods –as a replacement for land surveying methods-can help planners and authorities working in the field of energy. In this regard, thermal remote sensing with a vast coverage of the earth’s surface, and the possibilityof calculating land surface temperature using satellite imagery plays an important role as a new economic tool.Mapping land surface temperature is a key point in achieving geothermal anomalies and different algorithms play an important role in land surface temperature estimation. Therefore, identifying potential sources of geothermal energyusingremotely sensed thermal data is a challenging and yet interesting subject.
Materials and Methods
The present study takes advantage of images received from OLI and TIRS sensors (Landsat 8) to estimate land surface temperature, analyze thermal anomalies, and identify areas with potential geothermal resources in Meshkinshahr.The images were retrieved fromUSGSin Geo TIFF format.Envi 5.3, eCognition 9.1, MATLAB and ArcMap 10.4.1 were used to prepare, process and analyze the images.Moreover, meteorological data received fromMeshkinshahr station was collected from the General Department and Meteorological Center of Ardabil Provincewith the aim of identifying the optimal algorithm for calculation ofland surface temperature. Data wascollected for a one-day period (31/08/2017), i.e. the same day Landsat 8 passed over the areaunder study.
Results and Discussion
The present study sought to identify areas with potential geothermal resources using thermal remote sensing and a combination of surface temperature and thermal anomaly models. In order to calculate thermal anomaly, an observational thermal image is required, which is in fact the same land surface temperature calculated using Split Window and Mono Window algorithmsfor the image received from the satellite thermal band at the moment of collecting images. It should be noted that the land surface temperature calculated with these algorithms was evaluated using statistical data recorded in the temperature monitoring station. Results indicated higher accuracy of Split Window algorithm (3 ° C difference). Since, temperature obtained from this algorithm was more consistent with the actual temperature, its results were used as the observational thermal image.A thermal model was also defined to model factors responsible for heat variation from one pixel to another one. These two images were calculated and subtracted to reach the thermal anomaly image.In order to identify thermal anomalies caused by undergroundfactors heating the earthsurface, other factors responsible for increasing/decreasinglandsurfacetemperature should be normalized in the image. Thus, the effect of parameters such as solar energy, environmental degradation and evaporation on land surface temperature obtained from split window algorithm was investigated and finally, areas with heat anomalies and evidences indicating the presence of geothermal resources around themwere selected as areas with potential geothermal resources.Results indicate that inthe area surroundingSabalanmountains,two regions with 5.5 and 10.05 hectares in the northern and northeastern parts of Moyelvillage, a1.4 hectares area in the southwestern part of Qutursouli Spa, and the southern part of the Qinrjah Spa with an area of 1.1 hectare had potentialgeothermal resources and a high potential for exploration of geothermal resources.
Conclusion
The presence of hot springs, a geothermal power plant and other evidences shows that Ardabil Province and especially Meshkinshahr city has the potential for geothermal energy production as one of the major sources of new and environmentally friendly energies.However, no effective studies have been performed to identify these resources using modern and low-cost methods including thermal remote sensing.Therefore, the present study for the first time took advantage ofGIS and remote sensingto identify areas appropriate for geothermal energy extraction inMeshkinshahr city and concluded that remote sensing studies on Landsat 8 satellite images have a high efficiency for identifying areas with potential geothermal resources. Thus, areas identified in the present study have a strong spatial correlation with the geothermal evidences founded in the region.
Javad Javdan; Mohammad Hossein Rezaei Moghaddam; Yousef Ebadi
Abstract
Extended Abstract
Introduction
Land surface temperature (LST) is one of the key parameters in environmental studies on local to global scales. Considering the limitations of local meteorological stations, remote sensing has opened a new horizon in collection of suchinformation. Recently, successful ...
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Extended Abstract
Introduction
Land surface temperature (LST) is one of the key parameters in environmental studies on local to global scales. Considering the limitations of local meteorological stations, remote sensing has opened a new horizon in collection of suchinformation. Recently, successful launch of Landsat 8 with two thermal bands has provided a good opportunity for retrieving land surface temperature usingthermal remote sensing technology. Many studies had been performedwith the aim of retrieving land surface temperature, but available evidencesshow a significant calibration uncertainty inThermal Infrared Sensor (TIRS) of Landsat 8 band 11 and thus development of new studies based on onethermal band seems to be necessary. However, calibration documents issued by the United States Geological Survey (USGS) indicated uncertainty ofdata received from Band 11 Thermal Infrared Sensor (TIRS) of Landsat 8 and suggested using Band 10 data as a single spectral band for LST estimation.
Materials & Methods
In this study, mono-window algorithm with its three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature)has been developedunderan automated algorithmin MATLABand was used for Landsat 8 data.Thermal band 10 was used to estimate brightness temperature. Bands 4 and 5 were also used to calculate the NDVI. Retrieval of LST from Landsat 8 TIRS data is performed based on the premise that brightness temperature (Ti)can be computed for any pixel of Band 10 using the mono-window algorithm.Since the observed thermal radiance for Band 10 of Landsat 8 TIRS is stored and transferredasa digital number (DNs) with 16 digits between 0 and 65,535, it is possible toconvertthe DN value into thermal radiance and then convert radiance into brightness temperature.Ground emissivity is calculatedusing land cover patterns received from other bands of Landsat 8, and the other two parameters are estimated based on the local meteorologicaldata. Usually, obtaining an accurate estimate of ground emissivity is very difficult, and the atmospheric water vapor content is considered to be a sensitive parameter in traditional LST retrieval methods.
Results & Discussion
The algorithm has been successfully applied to Tabriz city in north west of Iran with the aim of analyzing spatial distribution of LST. After running the algorithm on the satellite images of the study area on July 18,2016, a lower land surface temperature was observed in green spaces with 1.2°C accuracy as compared to urban areas and wastelands. The lowest temperature in the study area was 20°C and the highest temperature was 53°C and mean temperature was 38.78°C.Results indicate that the algorithm candiscover natural urban heat islands accurately. Moreover, spatial distribution of LST in the region is quite well matched with the land covers. Successful application of the algorithm proves the efficiency of improved mono-window algorithm as a method used for retrieving LST from Landsat 8 data.
Conclusion
Compared to common methods,the proposed algorithm estimates land surface temperature with minimum requirement for user intervention, least possible time and an acceptable accuracy. Itgives researches an opportunity to easily compute LST and apply it in other studies, and thus it is a significant tool.
yasin kazemi; Saeid Hamzeh; Seyed Kazem Alavipanah; Bahram Bahrambeygi
Abstract
Extended Abstract Introduction Faults are fractures in the earth’s crust that has the ability to move. Faults are one of the most important geological structures, and since they have paths for emersion of heat from the lower parts of the earth’s crust to the surface, can be considered as ...
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Extended Abstract Introduction Faults are fractures in the earth’s crust that has the ability to move. Faults are one of the most important geological structures, and since they have paths for emersion of heat from the lower parts of the earth’s crust to the surface, can be considered as one of the essential reasons of potential of geothermal energy. Geothermal energy is one of the major sources of renewable energy and compatible with the environment, which if properly utilized and bases on environmental parameters, can play an important role in the energy balance of the country and the goals of sustainable development. There are many methods that can be used to identify potential geothermal, one of which is remote sensing that is part of new technologies, and it is also cost-effective. Among the various methods of remote sensing for exploration of geothermal resources, thermal remote sensing has unique advantages. Thermal infrared remote sensing is an effective method to identify the Earth’s surface temperature anomalies whose combination with the analysis of geological and understanding of geothermal mechanism, can be an appropriate approach for exploration of geothermal areas. Materials and Methods Data used in this study included images of Landsat-8, geological map of the region and the layer of active faults as well. Images were taken on February 2015, and the reason for selecting this time of year for image processing is to reduce the impacts of solar radiation on the earth’s surface temperature and therefore less impact on the heat causes by faults. The study area of this research is the Shahdad county of Kerman city. Two faults of Shahdad and Nayband are in this region. In this research, the method of Single Chanel is used to retrieve the surface temperature. The software used in this study include ENVI5.3, ERDAS Imagine 2014, and ArcGIS 10.3. After the calculation of the Earth’s surface temperature by Landsat 8, the thermal behavior of the faults was analyzed. Results and discussion In this part of the study, two transversal profiles with an approximate length of 12 km were taken for each one of the faults, from the surface temperature map of the region. By examining the graphs of the temperature profiles, it was found that temperature changes along the profile increase with the approach to the location of the fault’s surface outcrop. The heat accumulation along the Nayband fault corresponds to the closeness to the fault central zone, but this correspondence has been less for the Shahdad fault. Also, by creating a 6 kilometer buffer around the faults, it was observed that the average temperature of the pixels of this buffer is about two degrees higher than the average temperature of pixels of the entire region. Conclusion Investigating the possibility of instrumental use of the Landsat-8 satellite’s analyzing capability of thermal data to determine the position of the fault based on the thermal anomalies created around the central zone of the faults in the present research showed that LST calculation from the aforementioned data is considered as an appropriate method for extracting the linear anomalies and tracking the possible fault zones. Also, the temperature processing on the areas surrounding the Shahdad fault and the southern part of the Nayband fault and the presence of the thermal aggregates associated with the aforementioned faults are considered as the land index areas. These thermal aggregates in transections created on the faults indicate that the amount of LST increases clearly with approaching the location of the central zone of the above-mentioned faults on the earth’s surface. Linear thermal accumulations around the faults are the effects of the superficial and deep causes, so that sometimes the basement faults of the lava exit area have been the constituent of the surface lithology of an area at the time of the formation, which are younger and have less weathering and higher capacity for absorbing the sunlight, while approaching the central zone of the faults as the eruption openings of the volcanic rocks. On the other hand, due to the depth of the faults and their depth’s access to the hot material forming the asthenosphere part beneath the earth’s crust, the geothermal gradient in the central zones of these fault is higher than the surrounding areas. Considering the lack of introducing the volcanic rocks in the geologic map of the study area, it can be concluded that the linear thermal anomaly around the existing faults in the area is mainly associated with the deep heat sources and it is less likely to be associated with the absorption of the surface heat. Regarding the evident increase in temperature on the isothermal diagrams close to the central zone of the faults in the study area, two areas with the highest slope of increasing temperature along the central zone of the faults were identified and introduced as the possible geothermal potentials for more precise studies and future surveys. These two areas are located 45 kilometers southeast and about 15 kilometers northwest of the town of Shahdad.