Using aster image processing for geothermal energy potential areas

Geothermal systems are an important source of energy commonly available in active volcanic areas across Colombia and Latin-America. To build geothermal plants and generate electricity it is necessary to explore potential areas with meaningful temperature gradients and reservoirs. Geologic and feasibility studies are necessary to determine the potentials of such areas. This process requires a great amount of time and resources, so satellite imagery analysis is a widely used approach for a first survey, especially in remote areas that present logistic challenges. Freely available ASTER images allow the study of potential areas for geothermal energy, through the detection of certain minerals present in the surface generated by geothermal alteration. In this work, digital image processing techniques are applied across three study areas, El Tatio in Chile, Azufral and Nevado del Ruiz in Colombia. First, in order to carry out the image analysis, an atmospheric correction was performed to obtain reflectance values. Second, false color images were generated for an exploratory analysis. Third, band ratios were calculated to enhance absorption features for different clay minerals. Fourth, principal component analysis was applied, and component images were used to generate compositions to highlight areas with hydrothermal alterations. It was determined that 468 RGB color composition enhanced alterations, 4/7 band ratio eliminates errors of color composites and PCA discriminates between alteration minerals such as Kaolinite, Smectite, Illite and Alunite

• Autores: Rojas Aparicio, Miguel Ángel
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2017
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: eng
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/40380
• Acceso en línea: http://hdl.handle.net/1992/40380
• Palabra clave: Geología estructural; Procesamiento digital de imágenes; Fuentes hidrotermales; Sensores remotos; Geociencias
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/