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 ...
Read More
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.
Seyedeh Sareh Dabiri; Mohammad Taleai; Ghasem Javadi
Abstract
Introduction
The study of the areas with geothermal energy potential is of particular importance in realizing the goals ofsustainable development. Areas with geothermal potential areof great importance in terms of application as renewable energy resources, tourist attraction, greenhouse construction, ...
Read More
Introduction
The study of the areas with geothermal energy potential is of particular importance in realizing the goals ofsustainable development. Areas with geothermal potential areof great importance in terms of application as renewable energy resources, tourist attraction, greenhouse construction, etc.Generally, in geothermal exploration projects, studies are initially carried out with regard to the existing indicators, and the outcome of the primary location is used for more detailed studies. The identification of the areas with geothermal potential, which is the first phase of geothermal energy exploration, is complex and difficult.
Determining areas with geothermal energypotential as a basis for clean and environment friendly natural energyexploration studies, is important for achieving sustainable development. The purpose of this paper is to identify the areas with geothermal potential with regard to the characteristics of the northwest regions of Iran and the application of Geospatial Information Systems and Multi-criteria analysis methods, which have many advantages in the field of exploring the regions with geothermal potential.
In this study, the spatial Multi-criteria analysis package of ILWIS software and also the decision-making method based on the Ordered Weighted Average (OWA) in TerrSet(IDRISI) software have been used
Different scenarios of decision-making were implemented in the case study area and, the results were compared with the location of hot water springs in the region. The results indicate that the location of the determined sites is close to the hot water springs, which confirms the results of the proposed model of the paper.
Materials & Methods
The study of geothermal energy with the help of the spatial information system has drawn the attention in recent years. The purpose of this paper is to study areas with geothermal potential in the northwestern regions of Iran. These regions have different effects on the Earthand the researchers of this field use these effects to find new methods for measuring geothermal resources (Yousefy, 2006). Nowadays, GIS-based MCDM techniques are effectively used in these types of studies. Therefore, it has been tried to use some of these techniques in this research. In addition to the novelty of the topic of the geothermal studies in Iran, the issue of modeling different decision-making scenarios has been taken into consideration fromthe pessimistic view (with low risk) to the optimistic one (with high risk). Therefore, in this research,areas with geothermal potential have been identified and compared, with the help of study with the help of spatial data and Multi-criteria decision-making methods. In this study, decision-making criteria are evaluated and selected usinglibrary studies from previous researches. Also, based on the weighting methods and the integration of criteria, 8 scenarios were produced and their results were compared with each other. Meanwhile, the weight of the criteria was calculated using questionnaires and the analytic hierarchy process (AHP) method. The Ordered Weighted Average (OWA) method was applied to create various scenarios. Figure-1 shows the stages of this research.
Results & Discussion
The two software (ILWIS and TerrSet), provide powerful tool for standardizing, weighting and integratingthe standard maps associated with the decision-making process. In the implementation stage, the maps are standardizedafter the preparation of thestandard maps in the acceptable format of each software. In this study, fuzzy and AHP methods were used for standardization and weighting,respectively. Finally, the input factors are integrated according to different scenarios. The results are shown in Fig-8. In order to evaluate the results, the geothermal map produced based on the model proposed in this article has been compared with the location of hot water springs. The results of most scenarios show that, hot water springs are generally located in two classes with high suitability which confirms the results of the research. In Fig-9, hot springs are located in the classes with high suitability, as it was expected. This means that the results of this research are acceptable. Adaptation and compatibility of the geothermal map and the existing situation provide the possibility of using the results of the case study area in the exploration studies of other regions.
Conclusion
In this research, multi-criteria decision-making based on the use of GIS tool was used as a feasibility study in the first phase of geothermal exploration. The layers were processed and using theAHP-OWA integration methods in the 8 scenarios, they were integrated and the obtained results were investigated and compared. In most scenarios, hot water springs are in suitable or very suitable classes. This reflects the acceptable results obtained from the proposed modeling of this research.