Using Landsat-8 Data in Preliminary Exploration for Geothermal Resources

Authors

  • Kathurima C. Eric  Geothermal Energy Training and Research Institute, Dedan Kimathi University of Technology, Nyeri, 10100, Kenya

DOI:

https://doi.org//10.32628/IJSRSET196312

Keywords:

Land Surface Temperature, Landsat-8, Geothermal, Split Window, Single Channel, Thermal Anomalies

Abstract

To characterize geothermal potential areas, conventional surface exploration activities involve field surveys, gathering geothermal information from locals and review of any existing geothermal literature. This is not only time consuming and costly but also unreliable for inaccessible geothermal potential areas. Thus, this study explores the cost-effectiveness and powerful tools of satellite remote sensing in preliminary land surface characterization for expansive geothermal exploration. The main approach entailed the use of free-access Landsat-8 and atmospheric data to retrieve land surface temperature (LST) using split-window and single channel algorithm, analysis of retrieved surface products, validation using in-situ ground temperature data, and finally delineation of surface thermal anomalies associated with geothermal features. Gilgil district and Baringo County in Kenya made the study areas. The former is a known and confirmed geothermal area while the latter is only a geothermal prospect. The two areas sit on the central section of the Kenyan rift; geothermal belt, and combined form a suitable case study for preliminary exploration using Landsat-8 data. The main objective of the study was to demonstrate the use of satellite remote sensing data to identify surface thermal anomalies associated with geothermal features as a cost-effective geothermal exploration support tool. Identify the best LST retrieval method between split window and single channel method using Landsat 8 data, and finally employ the better retrieval method to characterize geothermal prospect area and suggest targets for further investigations. Results showed that free-access satellite remote sensing imagery can conveniently be used to identify and map surface thermal anomalies associated with geothermal features and thus can be employed to complement the main geothermal exploration studies namely geological, geochemical and geophysical. Further, single channel method had better LST retrieval results compared to split-window method when using Landsat-8 data

References

  1. J. C. Jiménez-Muñoz, J. A. Sobrino, D. Skokovi ?, C. Mattar, and J. Cristóbal, “Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data,” Geosci. Remote Sens. Lett. IEEE, vol. 11, no. 10, pp. 1840–1843, 2014.
  2. O. Rozenstein, Z. Qin, Y. Derimian, and A. Karnieli, “Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm,” Sensors (Switzerland), vol. 14, no. 4, pp. 5768–5780, 2014.
  3. T. Zhang et al., “Estimation of the Total Atmospheric Water Vapor Content and Land Surface Temperature Based on AATSR Thermal Data,” Sensors, vol. 8, no. 3, pp. 1832–1845, 2008.
  4. Z. L. Li et al., “Satellite-derived land surface temperature: Current status and perspectives,” Remote Sens. Environ., vol. 131, pp. 14–37, 2013.
  5. J. Mutua and G. Mibei, “Remote Sensing Application in Geothermal Exploration: Case Study of Barrier Volcanic Complex, Kenya,” GRC Trans., vol. 35, pp. 943–947, 2011.
  6. F. M. Howari, “Prospecting for geothermal energy through satellite based thermal data?: Review and the way forward,” Glob. J. Environ. Sci. Manag., vol. 1, no. 4, pp. 265–274, 2015.
  7. W. M. Calvin, M. Coolbaugh, and C. Kratt, “Application of remote sensing technology to geothermal exploration,” Geol. Surv. …, no. May, pp. 1083–1089, 2005.
  8. M. F. Coolbaugh, C. Kratt, A. Fallacaro, W. M. Calvin, and J. V. Taranik, “Detection of geothermal anomalies using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared images at Bradys Hot Springs, Nevada, USA,” Remote Sens. Environ., vol. 106, no. 3, pp. 350–359, 2007.
  9. M. Eneva, M. Coolbaugh, S. C. Bjornstad, J. Combs, C. Westchester, and S. Diego, “In Search for Thermal Anomalies in the Coso Geothermal Field (California) using Remote Sensing and Field Data,” in Geothermal Reservoir Engineering, 2007.
  10. S. Karki, S. K. Nawotniak, H. C. Bottenberg, M. Mccurry, and J. Welhan, “Determination of Geothermal Anomalies Through Multivariate Regression of Background Variables at Yellowstone National Park Using Landsat 5 TM Thermal Band Data,” vol. 38, 2014.
  11. M. Eneva and M. F. Coolbaugh, “Importance of elevation and temperature inversions for the interpretation of thermal infrared satellite images used in geothermal exploration,” GRC Trans., vol. 33, pp. 467–470, 2009.
  12. J. C. Jimenez-Munoz, J. Cristobal, J. A. Sobrino, G. Sòria, M. Ninyerola, and X. Pons, “Revision of the single-channel algorithm for land surface temperature retrieval from landsat thermal-infrared data,” IEEE Trans. Geosci. Remote Sens., vol. 47, no. 1, pp. 339–349, 2009.
  13. J. C. Jiménez-Muñoz and J. A. Sobrino, “A single-channel algorithm for land-surface temperature retrieval from ASTER data,” IEEE Geosci. Remote Sens. Lett., vol. 7, no. 1, pp. 176–179, 2010.
  14. Z. Zhang et al., “Towards an operational method for land surface temperature retrieval from Landsat 8 data,” Remote Sens. Lett., vol. 7, no. 3, pp. 279–288, 2016.
  15. C. Du, H. Ren, Q. Qin, J. Meng, and J. Li, “Split-Window algorithm for estimating land surface temperature from Landsat 8 TIRS data,” Int. Geosci. Remote Sens. Symp., no. Ldcm, pp. 3578–3581, 2014.
  16. U. Avdan and G. Jovanovska, “Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data,” J. Sensors, vol. 2016, pp. 1–8, 2016.
  17. USGS and NASA, Landsat 8 Data Users Handbook, vol. 2. Sioux Falls, 2016.
  18. F. Wang, Z. Qin, C. Song, L. Tu, A. Karnieli, and S. Zhao, “An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data,” Remote Sens., vol. 7, no. 4, pp. 4268–4289, 2015.
  19. J. A. Sobrino, J. C. Jiménez-Muñoz, and L. Paolini, “Land surface temperature retrieval from LANDSAT TM 5,” Remote Sens. Environ., vol. 90, no. 4, pp. 434–440, 2004.
  20. M. F. Coolbaugh, J. V. Taranik, and F. A. Kruse, “Mapping of surface geothermal anomalies at Steamboat Springs, NV using NASA Thermal Infrared Multispectral Scanner (TIMS) and Advanced Visible and Infrared Imaging Spectrometer (AVIRIS) data,” Proceedings, 14th Themat. Conf. Appl. Geol. Remote Sens., pp. 623–630, 2000.
  21. KenGen, “Geoscientific Study of Eburru- Badlands- Elementaita Geothermal Prospect,” 2017.
  22. P. A. Omenda, “Geothermal Exploration in Kenya,” United Nations Univeristy-Geothermal Dev. Co. Short Course V, p. 14, 2010.
  23. K. Valizadeh Kamran, M. Pirnazar, and V. Farhadi Bansouleh, “Land surface temperature retrieval from Landsat 8 TIRS: comparison between split window algorithm and SEBAL method,” Third Int. Conf. Remote Sens. Geoinf. Environ., vol. 9535, p. 953503, 2015.
  24. Q. Qin, N. Zhang, P. Nan, and L. Chai, “Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis-A case study in Tengchong, China,” Int. J. Appl. Earth Obs. Geoinf., vol. 13, no. 4, pp. 552–559, 2011.
  25. J. A. Sobrino, J. C. Jiménez-Munoz, J. El-Kharraz, M. Gómez, M. Romaguera, and G. Sòria, “Single-channel and two-channel methods for land surface temperature retrieval from DAIS data and its application to the Barrax site,” Int. J. Remote Sens., vol. 25, no. 1, pp. 215–230, 2004.
  26. Z. Qin, A. Karnieli, and P. Berliner, “A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region,” Int. J. Remote Sens., vol. 22, no. 18, pp. 3719–3746, 2001.
  27. M. Eneva, M. Coolbaugh, and J. Combs, “Application of Satellite Thermal Infrared Imagery to Geothermal Exploration in East Central California,” GRC Trans., vol. 30, pp. 407–412, 2006.
  28. S. Ke-Sheng and H. Ming-Yuan, “Application of Remote Sensing Technology in Geothermal Exploration: a Case Study of Taizhou City in Jiangsu Province,” Proc. World Geotherm. Congr. 2010, vol. 1100, no. April, pp. 25–29, 2010.
  29. R. G. Vaughan, J. B. Lowenstern, L. P. Keszthelyi, C. Jaworowski, and H. Heasler, “Mapping Temperature and Radiant Geothermal Heat Flux Anomalies in the Yellowstone Geothermal System Using ASTER Thermal Infrared Data,” GRC Trans., vol. 36, no. 2001, pp. 1403–1409, 2012.
  30. J. Mutua, a Friese, F. Kuehn, T. Lopeyok, M. Mutonga, and N. Ochmann, “High Resolution Airborne Thermal Infrared Remote Sensing Study , Silali Geothermal Prospect , Kenya,” Short Course VIII Explor. Geotherm. Resour., pp. 1–10, 2013.
  31. X. Yu, X. Guo, and Z. Wu, “Land surface temperature retrieval from landsat 8 TIRS-comparison between radiative transfer equation-based method, split window algorithm and single channel method,” Remote Sens., vol. 6, no. 10, pp. 9829–9852, 2014.
  32. P. Omenda, S. Simiyu, and G. Muchemi, “Geothermal Country Update Report for Kenya?: 2014,” in ARGeo-C5, 2014, no. Figure 1, pp. 29–31.

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Published

2019-06-30

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Section

Research Articles

How to Cite

[1]
Kathurima C. Eric, " Using Landsat-8 Data in Preliminary Exploration for Geothermal Resources, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 3, pp.223-240, May-June-2019. Available at doi : https://doi.org/10.32628/IJSRSET196312