Published

2019-10-01

Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data

Determinación de Prospectos Hidrotermales en la Región Geotérmica de Paipa (Boyacá, Colombia), Utilizando Sensores Remotos y Datos de Campo

DOI:

https://doi.org/10.15446/esrj.v23n4.77810

Keywords:

Remote sensing, Thermal Infrared, Temperature, Geothermal, Prospects, Paipa. (en)
Sensores Remotos, Infrarrojo Termal, Temperatura, Geotermia, Prospectos, Paipa (es)

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Authors

  • Rafael Andrés Calderón-Chaparro Universidad Nacional de Colombia
  • German Vargas-Cuervo Universidad Nacional de Colombia

Geothermal resources (e.g. hot springs) are found with the help of field techniques, such as geological, geochemistry and geophysical. These techniques in some occasions are difficult to apply because of the limit access to the research area, rising operational costs and constrained spatially the exploration areas. The thermal infrared (TIR) remote sensing is an important tool for the exploration of geothermal resources, due to the low cost and high efficiency in the study of large geographic areas. The aim of this study is to use thermal imagery of satellite remote sensing and combined with geological-geophysical data, for spatial determination of exploratory prospects of hot springs in the geothermal region of Paipa, Boyacá. The images used in this study are from satellites Landsat-7 ETM+, Landsat-8 OLI/TIRS, MODIS, ALOS-PALSAR and Pléiades. Also, field data is used, such as soil temperature, surface temperature, air temperature, relative humidity, atmospheric pressure and thermal imagery of surface geothermal manifestations. The Landsat thermal bands were radiometrically calibrated, then atmospherically and surface emissivity corrected, applying single channel and split window algorithms, for Landsat-7 ETM+ and Landsat-8 TIRS, respectively. The field data helped to correct the thermal bands. And the soil temperature data are used to create a subsurface temperature map at 1-meter depth. Once primary and secondary data is had, in a geographic information system (GIS) is implemented an unweighted spatial model, which use four input indicators (satellite temperature index, soil temperature index, structural lineaments index and iso-resistivity index) to determine the areas with higher probability to find geothermal fluids. Six prospects are highlighted for hydrothermal fluid extraction, in which two of them are already known. Results allow to concluded that thermal remote sensing are useful to map geothermal anomalies in the Paipa region, and by using these anomalies plus geological-geophysical information is possible to determine exact exploration areas.

Los recursos geotérmicos (ej: aguas calientes) han sido encontrados con ayuda de técnicas de campo, geológicas, geoquímicas y geofísicas, las cuales, en algunas ocasiones, el difícil acceso al área de investigación, dificulta su aplicación, aumentando los costos de operación y restringiendo espacialmente las áreas de exploración. Los sensores remotos con infrarrojo termal, son una herramienta importante en la exploración de recursos geotérmicos, debido al bajo costo y alta eficiencia en el estudio de grandes áreas geográficas. El objetivo de este estudio es integrar imágenes termales de sensores remotos satelitales, con información geológica-geofísica existente, para la determinación espacial de prospectos exploratorios de fuentes hidrotermales, en la región geotérmica de Paipa, Boyacá. Se utilizaron imágenes satelitales Landsat 7 ETM+, Landsat 8 OLI/TIRS, MODIS, ALOS-PALSAR y Pléiades. También, se utilizaron datos de campo, de temperatura de suelo, temperatura de superficie, temperatura de aire, humedad relativa, presión atmosférica e imágenes térmicas de las manifestaciones geotérmicas. Las bandas termales Landsat fueron calibradas radiométricamente, posteriormente corregidas por efectos atmosféricos y emisividad de la superficie, aplicando algoritmos de un solo canal y Split Window, para Landsat 7 ETM+ y Landsat 8 TIRS, respectivamente. Los datos de campo contribuyeron a la corrección de las bandas termales, y los datos de temperatura de suelo, ayudaron a la creación de un mapa de temperatura subsuperficial a un metro de profundidad. Una vez se contaba con los insumos primarios y secundarios, en un sistema de información geográfico (SIG), se implementó un modelo espacial no ponderado, el cual utilizó cuatro indicadores de entrada (índice temperatura satelital, índice temperatura de suelo, índice lineamientos estructurales e índice iso-resistividad), para determinar las zonas de mayor probabilidad de encontrar fluidos geotérmicos. Seis prospectos se identificaron para la extracción de fluidos hidrotermales, de los cuales dos son ya conocidos. Los resultados permitieron concluir que los sensores remotos termales son una herramienta útil, para el mapeo de anomalías geotérmicas en la región de Paipa, y utilizando estas anomalías en conjunto con información geológica-geofísica, es posible determinar áreas puntuales de exploración.

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How to Cite

APA

Calderón-Chaparro, R. A. and Vargas-Cuervo, G. (2019). Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data. Earth Sciences Research Journal, 23(4), 265–282. https://doi.org/10.15446/esrj.v23n4.77810

ACM

[1]
Calderón-Chaparro, R.A. and Vargas-Cuervo, G. 2019. Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data. Earth Sciences Research Journal. 23, 4 (Oct. 2019), 265–282. DOI:https://doi.org/10.15446/esrj.v23n4.77810.

ACS

(1)
Calderón-Chaparro, R. A.; Vargas-Cuervo, G. Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data. Earth sci. res. j. 2019, 23, 265-282.

ABNT

CALDERÓN-CHAPARRO, R. A.; VARGAS-CUERVO, G. Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data. Earth Sciences Research Journal, [S. l.], v. 23, n. 4, p. 265–282, 2019. DOI: 10.15446/esrj.v23n4.77810. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/77810. Acesso em: 14 jul. 2024.

Chicago

Calderón-Chaparro, Rafael Andrés, and German Vargas-Cuervo. 2019. “Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data”. Earth Sciences Research Journal 23 (4):265-82. https://doi.org/10.15446/esrj.v23n4.77810.

Harvard

Calderón-Chaparro, R. A. and Vargas-Cuervo, G. (2019) “Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data”, Earth Sciences Research Journal, 23(4), pp. 265–282. doi: 10.15446/esrj.v23n4.77810.

IEEE

[1]
R. A. Calderón-Chaparro and G. Vargas-Cuervo, “Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data”, Earth sci. res. j., vol. 23, no. 4, pp. 265–282, Oct. 2019.

MLA

Calderón-Chaparro, R. A., and G. Vargas-Cuervo. “Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data”. Earth Sciences Research Journal, vol. 23, no. 4, Oct. 2019, pp. 265-82, doi:10.15446/esrj.v23n4.77810.

Turabian

Calderón-Chaparro, Rafael Andrés, and German Vargas-Cuervo. “Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data”. Earth Sciences Research Journal 23, no. 4 (October 1, 2019): 265–282. Accessed July 14, 2024. https://revistas.unal.edu.co/index.php/esrj/article/view/77810.

Vancouver

1.
Calderón-Chaparro RA, Vargas-Cuervo G. Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data. Earth sci. res. j. [Internet]. 2019 Oct. 1 [cited 2024 Jul. 14];23(4):265-82. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/77810

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