Identification of Promising Areas for Geothermal Energy Using Satellite Data in Sahand Region

Document Type : Research Paper

Authors

1 Professor, Department of Physical Geography, Faculty of Social Science, University of Mohaghegh Ardabili, Ardabil, Iran.

2 Student in RS & GIS, Department of Physical Geography, Faculty of Social Science, University of Mohaghegh Ardabili, Ardabil, Iran.

Abstract

Areas with geothermal potential naturally have evidence on the ground surface that is used in geothermal energy exploration projects to initially locate these areas. The aim of this study is to identify surface geothermal areas by combining surface temperature and energy currents obtained from the SEBAL method using TIRS thermal data of Landsat 8 satellite in the Sahand region of East Azerbaijan province located in the northwest of Iran. For this purpose, one image of Landsat 8 data was used for September 25, 2022, then using single channel James-Sobrino algorithms and split window, the Land surface temperature map was estimated. Then estimated Land surface Temperature image with the thermal data of SLSTR sensor of the Sentinel 3 satellite (for pass time of the Landsat satellite) was validated using the analysis of the linear regression model in the TerrSet software environment, until in the process of identifying geothermal energy to be use. Next, using with Sebal Algorithm the amount of net surface radiation(Rn), net energy directed to the ground(G) and the amount of solar radiation absorbed by the Surface(Rsolar) was estimated for minimized the effect of solar radiation on the land surface temperature. By combining the heat flows obtained from the Sebal algorithm and the Land surface temperature, the potential areas of geothermal energy were identified and determined. The final results of Maps showed that there are pixels in the study area that are prone to geothermal energy and the presence of natural hot springs in different cities of East Azerbaijan province, especially in the study area increases the probability of geothermal sources and this fact confirm that our study area have a hight  potential for exploration of geothermal Energy. 

Keywords

Main Subjects


Abedini, M., Ghale, E., Aghazadeh, N., & Mohamadzadeh Shishegaran, M, 2021, Monitoring the surface temperature and studying the land use relationship with surface temperature using oli and tm image sensors (Case Study: Meshginshahr City), Journal of Applied Researches In Geographical Sciences, 22(67): 375-393. (in Persian)http://dx.doi.org/10.52547/jgs.22.67.375
Ahamzeh, S., Mijani, N., & Karimi Firozjaei, M, 2018, Modeling the Relationship between Land Surface Temperature, Topography and Vegetation Cover Using Landsat 8 Satellite Imagery. Physical Geography Research, 50(1): 35-55. (in Persian)https://doi.org/10.22059/jphgr.2018.215259.1006930
Ahmadizadeh, S.S.R., Arasteh, F., Fanaee Kheirabad Gh. A., & Ashrafi, A, 2015, Detection of geothermal potentials using thermal remote sensing in south khorasan, Environmental Researches, 5(10): 135. (in Persian)https://dor.isc.ac/dor/20.1001.1.20089597.1393.5.10.12.7
Akbari, E., Bahrami, SH., Doran, A., & Ebrahimi, M, 2017, The Effect of some Geographical Parameters on the Land Surface Temperature by Using SEBAL and Decision Tree Methods in Taftan Volcanic Cone, Geographic Space, 17(57): 105-126. (in Persian)http://geographical-space.iau-ahar.ac.ir/article-1-1821-fa.html
Alavipanah, S.K., Goodarzi Mehr, S., & Khakba, B, 2012, Thermal remote sensing technology and its application to phenomena identification, Science Cultivation Journal, 2(1): 25. (in Persian)https://www.sciencecultivation.ir/article_242567.html
Arvin, A, 2019, Land Surface Temperature Detection Using of Satellite Images. Journal of Natural Environmental Hazards, 8(19): 91-102. (in Persian)https://doi.org/10.22111/jneh.2017.20855.1284
Atmospheric correction module: Quac and flaash user’s guide, 2009, ITT Visual Information Solutions, powered by idl, Version(4.7).https://www.nv5geospatialsoftware.com/portals/0/pdfs/envi/flaash_module.pdf
Bastiaanssen, W. G., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F., Roerink, G. J., & Van der Wal, T, 1998, A remote sensing surface energy balance algorithm for land (SEBAL).: Part 2: Validation. Journal of hydrology, (212): 213-229.https://doi.org/10.1016/S0022-1694(98)00254-6
Cook, M., Schott, J. R., Mandel, J., & Raqueno, N, 2014, Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a Land Surface Temperature (LST) Product from the archive. Remote Sensing, 6(11): 11244-11266.https://doi.org/10.3390/rs61111244
Coolbaugh, M. F., Kratt, C., Fallacaro, A., Calvin, W. M., & Taranik, J. V, 2007, Detection of geothermal anomalies using advanced spaceborne thermal emission and reflection radiometer (ASTER) thermal infrared images at Bradys Hot Springs, Nevada, USA. Remote Sensing of Environment, 106(3): 350-359.https://doi.org/10.1016/j.rse.2006.09.001
Darvishi, Sh., Rashidpour, M., & Solaimani, K, 2018, Impact of Urban Surface Characteristics On Spatiotemporal Patterns Of Surface Temperature (Case Study: Sanandaj City), MSc Thesis, Faculty Of Environmental Sciences, Haraz, Amol. (in Persian)https://civilica.com/doc/871680/
Dash, P., Göttsche, F.M., Olesen, F.S. and Fischer, H. 2001. Retrieval of land surface temperature and emissivity from satellite data: physics, theoretical limitations and current methods. Journal of the Indian Society of Remote Sensing, 29: 23-30.https://doi.org/10.1007/BF02989910
Du, C., Ren, H., Qin, Q., Meng, J., & Li, J, 2014, Split-window algorithm for estimating land surface temperature from Landsat 8 TIRS data. In 2014 IEEE Geoscience and Remote Sensing Symposium, 3578-3581.https://doi.org/10.1109/IGARSS.2014.6947256
Du, C., Ren, H., Qin, Q., Meng, J., & Zhao, S, 2015, A practical split-window algorithm for estimating land surface temperature from Landsat 8 data. Remote sensing, 7(1): 647-665.https://doi.org/10.3390/rs70100647
Ebrahimi Heravi, B., Rangzan, K., Riahi Bakhtiari H. R., & Taghi Zadeh, A, 2016, Introducing the most appropriate method to extract land surface temperature using landsat 8 satellite images in karaj metropolitan, Iranian Journal Of Remote Sensing & Gis, 8(3): 59-76. (in Persian)https://gisj.sbu.ac.ir/article_96139.html
Emami, H., & Jafari, A, 2018, Shadow geothermal energy detection using integrating of temperature anomalies and sebal algorithm, Journal of Geomatics Science and Technology, 7(4): 25-44. (in Persian)https://dor.isc.ac/dor/20.1001.1.2322102.1397.7.4.2.2
Eneva, M., Coolbaugh, M., & Combs, J, 2006, Application of satellite thermal infrared imagery to geothermal exploration in east central California. GRC Transactions, (30): 407-412.https://api.semanticscholar.org/CorpusID:130523869
Feizizadeh, B., Didehban, Kh., & Gholamnia, Kh, 2016, Extraction of land surface temperature (LST) based on landsat satellite images and split window algorithm study area: mahabad catchment, Journal of Geographical Data (SEPEHR), 25(98):171-181. (in Persian)https://doi.org/10.22131/sepehr.2016.22145
García-Haro, F. J., Camacho-de Coca, F., Meliá, J., & Martínez, B, 2005, Operational derivation of vegetation products in the framework of the LSA SAF project. In Proceedings of 2005 EUMETSAT Meteorological Satellite Conference, Dubrovnik, Croatia,19-23.https://www.researchgate.net/publication/229022280
Haselwimmer, C., & Prakash, A, 2013, Thermal infrared remote sensing of geothermal systems. In Thermal infrared remote sensing: sensors, methods, applications  Dordrecht: Springer Netherlands, 453-473.https://link.springer.com/chapter/10.1007/978-94-007-6639-6_22
Isaya Ndossi, M., & Avdan, U, 2016, Application of open-source coding technologies in the production of land surface temperature (LST) maps from Landsat: A PyQGIS plugin. Remote sensing, 8(5): 413..https://doi.org/10.3390/rs8050413
Jiménez-Muñoz, J. C., & Sobrino, J. A, 2008, Split-window coefficients for land surface temperature retrieval from low-resolution thermal infrared sensors. IEEE geoscience and remote sensing letters, 5(4):806-809.http://dx.doi.org/10.1109/LGRS.2008.2001636
Jimenez-Munoz, J. C., Sobrino, J. A., Skoković, D., Mattar, C., & Cristobal, J, 2014, Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geoscience and remote sensing letters, 11(10): 1840-1843.https://doi.org/10.1109/LGRS.2014.2312032
Keynejhad, S., Fathianpour, N., & Irannejhad, M.R, 2011, Investigating the potential of geothermal resources in east azerbaijan using geological and exploration data. Dissertation For Master's Degree in Mining Exploration, Faculty Of Mining Engineering, Isfahan University Of Technology, Iran. (in Persian)https://www.virascience.com/thesis/532074/
Kiavarzmoghadam, M., Samadzadegan, F., Noorollahi, Y., & Sharifi, M.A, 2015, Identification of thermal anomaly points on the earth's surface with the aim of exploring geothermal resources. National Geomatics Conference, (22). (in Persian)https://sid.ir/paper/893047/fa
Kogan, F, 1993, United States droughts of late 1980's as seen by NOAA polar orbiting satellites. In Proceedings of IGARSS'93-IEEE International Geoscience and Remote Sensing Symposium, IEEE, 197-199.https://doi.org/10.1109/IGARSS.1993.322522
Lee, K., 1978, Analysis of thermal infrared imagery of the Black Rock Desert geothermal area, Colorado School of Mines Quarterly, 4 (2): 31-44.https://api.semanticscholar.org/CorpusID:130181817
Li, Z.L.; Tang, B-H.; Wu, H.; Ren, H.; Yan, G.; Wan, Z.; Trigo, I.F. and Sobrino, J.A. (2013). Satellite-derived land surface temperature: Current status and perspectives, Remote Sensing of Environment, 131: 14-37.https://doi.org/10.1016/j.rse.2012.12.008
LU, S. L., SHEN, X. H., ZOU, L. J., ZHANG, G. F., WU, W. Y., LI, C. J., & MAO, Y. J, 2008, Remote sensing image enhancement method of the fault thermal information based on scale analysis: A case study of Jiangshan‐Shaoxing Fault between Jinhua and Quzhou of Zhejiang Province, China. Chinese Journal of Geophysics, 51(5): 1048-1058.http://dx.doi.org/10.1002/cjg2.1299
Maleki, M., Ahmadi, Z., & Dousti, R, 2019, Land surface temperature changes in during 1393-1397 periods, Journal of Geography and Human Relations, 2(3): 309-319. (in Persian)https://www.magiran.com/p1452921
McMillin, L. M, 1975, Estimation of sea surface temperatures from two infrared window measurements with different absorption. Journal of geophysical research, 80(36): 5113-5117.https://doi.org/10.1029/JC080i036p05113
Melesse, A. M., & Nangia, V, 2005, Estimation of spatially distributed surface energy fluxes using remotely‐sensed data for agricultural fields. Hydrological Processes: An International Journal, 19(14): 2653-2670.https://doi.org/10.1002/hyp.5779
Mojarad, S., Aghajani, H., & Nejati, A, 2019, Thermal remote sensing studies and comparison with aeromagnetic studies in the northern sabalan to sarab area in order to potential geothermal energy promising areas, Journal of Analytical and Numerical Methods In Mining Engineering, 9(20): 67-80. (in Persian)https://anm.yazd.ac.ir/article_1626.html
Motahhar, S, 2016, Renewable energy education in Iran. Iranian Journal of Engineering Education, 18(69): 77-90.https://doi.org/10.22047/ijee.2016.14608
Ou, X., Jin, Z., Wang, L., Xu, H. J., & Jin, S. Y, 2004, Thermal conductivity and its anisotropy of rocks from the depth of 100 similar to 2000m mainhole of Chinese Continental Scientific Drilling: Revelations to the study on thermal structure of subduction zone. Acta Petrologica Sinica, 20(1): 109-118.https://api.semanticscholar.org/CorpusID:130002059
Parhizcar Isalu, R., Valizadeh Kamran, Kh., & Faizizadeh, B, 2020 Determining the best algorithm to calculate land surface temperature with the aim of identifying geothermal areas - case study: meshkinshahr county, Journal of Geographical Data (SEPEHR), 29(114): 79-98. (in Persian)https://doi.org/10.22131/sepehr.2020.44583
Peng, F., Xiong, Y. Z., Cheng, Y. X., Fan, Q. C., & Huang, S. P, 2013, Towards Application of remote sensing technology in geothermal prospecting in Xilingol in eastern Inner Mongolia, NE China. Advanced Materials Research, (610): 3628-3631.https://doi.org/10.4028/www.scientific.net/AMR.610-613.3628
Qin, Z., & Karnieli, A, 1999, Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data. International journal of remote sensing, 20(12): 2367-2393.https://doi.org/10.1080/014311699212074
Rahimian, M. H., shayannejad, M., Eslamian, S., Jafari, R., Gheysari, M., & Taghvaeian, S, 2017, Evaluation of different LST approaches for determination of pistachio tree canopy temperature through Landsat 8 satellite data, 5(2): 79-98. (in Persian)http://dx.doi.org/10.29252/jgit.5.2.79
Richter, R., & Schläpfer, D, 2013, Atmospheric/Topographic Correction for Satellite Imagery (ATCOR-2/3 UserGuide, Version 8.3. 1, February 2014), 2-238.https://www.academia.edu/download/34690612/atcor3_manual_2013.pdf
Rongali, G., Keshari, A. K., Gosain, A. K., & Khosa, R, 2018, Split-window algorithm for retrieval of land surface temperature using Landsat 8 thermal infrared data. Journal of Geovisualization and Spatial Analysis, (2): 1-19.https://doi.org/10.1007/s41651-018-0021-y
Rozenstein, O., Qin, Z., Derimian, Y., & Karnieli, A, 2014, Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors, 14(4): 5768-5780.https://doi.org/10.3390/s140405768
Sanyal, S. K, 2018, Sustainability and renewability of geothermal power capacity. In: L.Y. Bronicki (Eds), Geology and Hydrology of Geothermal Energy, Springer, New York, N, 47-60.http://repository.usgin.org/sites/default/files/dlio/files/2011/u19/sustainability__renewability_of_geothermal_power_capaciity.pdf
Sheikhzadeh, S., & Jafari, H, 2009, Using geothermal energy to reach a sustainable city, International Research Conference on Science and Technology, (3). (in Persian)https://sid.ir/paper/856891/fa
Shenavaei, H, 2006, Renewable energies (with a special look at hydroelectric energy), Journal of Energy Economics Reviews, (7): 75-92. (in Persian)http://noo.rs/RdTZw
Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L, 2004, Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of environment, 90(4): 434-440.https://doi.org/10.1016/j.rse.2004.02.003
Sobrino, J. A., Jiménez‐Muñoz, J. C., Sòria, G., Gómez, M., Ortiz, A. B., Romaguera, M., ... & Libonati, R, 2008, Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications. International Journal of Remote Sensing, 29(17-18): 4961-4991.https://doi.org/10.1080/01431160802036516
Sobrino, J. A., Li, Z. L., Stoll, M. P., & Becker, F, 1997, Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data. Oceanographic Literature Review, 2(44): 162-163.https://doi.org/10.1080/01431169608948760
Soleimani, A., & Abroumand Azar, P, 2015, Review of renewable energies and their environmental effects in iran, International Conference on Research In Science and Technology, (1). (in Persian)https://civilica.com/doc/446754/
Xiao, J., & Moody, A. (2005). A comparison of methods for estimating fractional green vegetation cover within a desert-to-upland transition zone in central New Mexico, USA. Remote sensing of environment, 98(2-3), 237-250.https://doi.org/10.1016/j.rse.2005.07.011
Yamaguchi Y., Hase H., Ogawa K, 1992, Remote sensing for geothermal applications. Episodes Journal of International Geoscience.15(1): 62-7.https://doi.org/10.18814/epiiugs/1992/v15i1/010