Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil
The lineament analysis method consists in the mapping in the lineaments of a given area. This method can be a good alternative to the traditional exploration methods, because it is considerably cheaper than these ones, because most of the time the data sources are open to the public. The main purpos...
- Autores:
-
Bolaño De la Hoz, Juan Pablo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2022
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/59346
- Acceso en línea:
- http://hdl.handle.net/1992/59346
- Palabra clave:
- Remote sensing
Lineament
Ore deposits
Density map
Magnetic data
Geociencias
- Rights
- openAccess
- License
- Atribución-CompartirIgual 4.0 Internacional
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Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| title |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| spellingShingle |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil Remote sensing Lineament Ore deposits Density map Magnetic data Geociencias |
| title_short |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| title_full |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| title_fullStr |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| title_full_unstemmed |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| title_sort |
Effectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, Brazil |
| dc.creator.fl_str_mv |
Bolaño De la Hoz, Juan Pablo |
| dc.contributor.advisor.none.fl_str_mv |
Nitescu, Bogdan Pearse, Jillian |
| dc.contributor.author.none.fl_str_mv |
Bolaño De la Hoz, Juan Pablo |
| dc.contributor.jury.none.fl_str_mv |
Tary, Jean Baptiste |
| dc.subject.keyword.none.fl_str_mv |
Remote sensing Lineament Ore deposits Density map Magnetic data |
| topic |
Remote sensing Lineament Ore deposits Density map Magnetic data Geociencias |
| dc.subject.themes.es_CO.fl_str_mv |
Geociencias |
| description |
The lineament analysis method consists in the mapping in the lineaments of a given area. This method can be a good alternative to the traditional exploration methods, because it is considerably cheaper than these ones, because most of the time the data sources are open to the public. The main purpose of this method is to identify the zones with the highest density of lineaments, which can be the zones hosting ore deposits. This method can be performed using optical, radar remote sensing data, but also magnetic data, which makes this method more feasible, due to it is not limited to a certain type of data. Moreover, the results from the different data can change because each one of the type of data reflects different features of the zone. This study will analyze the relation between the density of lineament and the presence of ore deposits in the northwest of the city of Macapá in Brazil. In order to achieve this, magnetic and satellite data will be use to extract the lineaments of the area using the Arcgis pro software.The lineaments extracted from the sentinel 1 VV and VH polarization images resulted to be the ones that better located the known ore deposits of the study area. Also, the directional filtered image from the S1A VH polarization images made a good localization of the ore deposits of the study area and also enhance the lineaments. |
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2022 |
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2022-07-29T15:00:04Z |
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2022-07-29T15:00:04Z |
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2022-07-06 |
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Trabajo de grado - Pregrado |
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Alavi-Sereshki, M. M. (1972). Analytic signals and hilbert transforms (Doctoral dissertation, Texas Tech University). Balasubramanian, A. (2017). Digital elevation model (DEM) in GIS. University of Mysore. Canada Natural Resources. (2015). Passive vs. Active Sensing. Natural Resources Canada. Retrieved from https://www.nrcan.gc.ca/maps-tools-publications/satelliteimagery-air-photos/remote-sensing-tutorials/introduction/passive-vs-active-sensing/14639 Carr, J. R. (1996). Numerical analysis for the geological sciences. Estudios Geogr´aficos, 57, 166. Dasgupta, S., & Mukherjee, S. (2019). Remote sensing in lineament identification: Examples from western India. In Developments in Structural geology and Tectonics (Vol. 5, pp. 205-221). Elsevier. ESA. (n.d.). Snap. SNAP - Earth Online. Retrieved from:https://earth.esa.int/ eogateway/tools/snap ESA. (n.d.). Sentinel-1. Sentinels. Retrieved March 17, 2022. Retrieved from: https: //sentinels.copernicus.eu/web/sentinel/missions/sentinel-1 Filipponi, F. (2019). Sentinel-1 GRD preprocessing workflow. In Multidisciplinary digital publishing institute proceedings (Vol. 18, No. 1, p. 11). Guth, P. L., Van Niekerk, A., Grohmann, C. H., Muller, J. P., Hawker, L., Florinsky, I. V., ... & Strobl, P. (2021). Digital elevation models: Terminology and definitions. Remote Sensing, 13(18), 3581. Han, L., Liu, Z., Ning, Y., & Zhao, Z. (2018). Extraction and analysis of geological lineaments combining a DEM and remote sensing images from the northern Baoji loess area. Advances in Space Research, 62(9), 2480-2493 Javhar, A., Chen, X., Bao, A., Jamshed, A., Yunus, M., Jovid, A., & Latipa, T. (2019). Comparison of multi-resolution optical Landsat-8, Sentinel-2 and radar Sentinel-1 data for automatic lineament extraction: A case study of Alichur area, SE Pamir. Remote Sensing, 11(7), 778. Jong, S. M. D., Meer, F. D., & Clevers, J. G. (2004). Basics of remote sensing. In Remote sensing image analysis: Including the spatial domain (pp. 1-15). Springer, Dordrecht. Li, X. (2006). Understanding 3D analytic signal amplitude. Geophysics, 71(2), L13- L16. Lowrie, W., & Fichtner, A. (2020). Fundamentals of geophysics. Cambridge university press. Manuel, R., Brito, M. D. G., Chichorro, M., & Rosa, C. (2017). Remote sensing for mineral exploration in central Portugal. Minerals, 7(10), 184. Marston, B. E., Jenny, B. (2015). Improving the representation of major landforms in analytical relief shading. International Journal of Geographical Information Science, 29(7), 1144-1165. Mårtensson, U. (2011). Introduction to Remote Sensing and Geographical Information Systems. Middleton, M., Schnur, T., Sorjonen-Ward, P., & Hyv¨onen, E. (2015). Geological lineament interpretation using the object-based image analysis approach: results of semi-automated analyses versus visual interpretation. Geological Survey of Finland, Special Paper, 57, 135-154. Mostafa, M. E., Qari, M. Y. H. (1995). An exact technique of counting lineaments. Engineering Geology, 39(1-2), 5-15. NASA. (2021). Landsat 8. NASA. Retrieved from https://landsat.gsfc.nasa.gov/satellites/landsat8/ Pour, A. B., Hashim, M. (2015). Structural mapping using PALSAR data in the Central Gold Belt, Peninsular Malaysia. Ore Geology Reviews, 64, 13-22. Prost, G. L. (2013). Remote sensing for geoscientists (pp. 309-310). New York: CRC Press. Barbosa, J. D. P. D. O., Chaves, C. L., Costa Neto, M. C. D., Anjos, G. C. D., & Costa, L. T. D. R. (2015). Geologia e recursos minerais da folha Macapá-NA. 22-YD, estado do Amapá. GeoSGB (n.d.) Folha Macapá - NA.22-Y-D. Retrieved from: https://geosgb.cprm. gov.br/geosgb/downloads$_$en.html Horikava, É. H. (2017) & Scarpelli, W., . Gold, iron and manganese in central Amapá, Brazil. Brazilian Journal of Geology, 47, 703-721. Rajesh, H. M. (2004). Application of remote sensing and GIS in mineral resource mapping-An overview. Journal of mineralogical and Petrological Sciences, 99(3), 83- 103. Roest, W. R., Verhoef, J., Pilkington, M. (1992). Magnetic interpretation using the 3-D analytic signal. Geophysics, 57(1), 116-125. Rosa, J. W. C., Rosa, J. W. C., & Fuck, R. A. (2014). Geophysical structures and tectonic evolution of the southern Guyana shield, Brazil. Journal of South American Earth Sciences, 52, 57-71. Salem, A., Williams, S., Fairhead, J. D., Ravat, D., & Smith, R. (2007). Tilt-depth method: A simple depth estimation method using first-order magnetic derivatives. The leading edge, 26(12), 1502-1505. Sentinel-1 Toolbox, (n.d.). Available online: https://sentinels.copernicus.eu/ web/sentinel/toolboxes/sentinel-1 Vincent, R. K. (1997). Fundamentals of geological and environmental remote sensing. Prentice Hall. Schobbenhaus, C., HE, A., GR, D. (1982). Mapa geológico do Brasil e da área oceánica adjacente incluindo depósitos minerais, escala 1: 2.500.000. |
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Atribución-CompartirIgual 4.0 Internacionalhttp://creativecommons.org/licenses/by-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Nitescu, Bogdan761f5432-6ebf-4cdb-9961-ee881e0521b8600Pearse, Jillianvirtual::13379-1Bolaño De la Hoz, Juan Pablo29233c3d-556a-4acf-87ce-773fb89efecb600Tary, Jean Baptiste2022-07-29T15:00:04Z2022-07-29T15:00:04Z2022-07-06http://hdl.handle.net/1992/59346instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/The lineament analysis method consists in the mapping in the lineaments of a given area. This method can be a good alternative to the traditional exploration methods, because it is considerably cheaper than these ones, because most of the time the data sources are open to the public. The main purpose of this method is to identify the zones with the highest density of lineaments, which can be the zones hosting ore deposits. This method can be performed using optical, radar remote sensing data, but also magnetic data, which makes this method more feasible, due to it is not limited to a certain type of data. Moreover, the results from the different data can change because each one of the type of data reflects different features of the zone. This study will analyze the relation between the density of lineament and the presence of ore deposits in the northwest of the city of Macapá in Brazil. In order to achieve this, magnetic and satellite data will be use to extract the lineaments of the area using the Arcgis pro software.The lineaments extracted from the sentinel 1 VV and VH polarization images resulted to be the ones that better located the known ore deposits of the study area. Also, the directional filtered image from the S1A VH polarization images made a good localization of the ore deposits of the study area and also enhance the lineaments.GeocientíficoPregrado36 páginasapplication/pdfengUniversidad de los AndesGeocienciasFacultad de CienciasDepartamento de GeocienciasEffectiveness of lineament analysis as a method for ore deposit exploration in the Greenstone belts of the southern Guiana Shield in the Amapá Region, BrazilTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPRemote sensingLineamentOre depositsDensity mapMagnetic dataGeocienciasAlavi-Sereshki, M. M. (1972). Analytic signals and hilbert transforms (Doctoral dissertation, Texas Tech University).Balasubramanian, A. (2017). Digital elevation model (DEM) in GIS. University of Mysore.Canada Natural Resources. (2015). Passive vs. Active Sensing. Natural Resources Canada. Retrieved from https://www.nrcan.gc.ca/maps-tools-publications/satelliteimagery-air-photos/remote-sensing-tutorials/introduction/passive-vs-active-sensing/14639Carr, J. R. (1996). Numerical analysis for the geological sciences. Estudios Geogr´aficos, 57, 166.Dasgupta, S., & Mukherjee, S. (2019). Remote sensing in lineament identification: Examples from western India. In Developments in Structural geology and Tectonics (Vol. 5, pp. 205-221). Elsevier.ESA. (n.d.). Snap. SNAP - Earth Online. Retrieved from:https://earth.esa.int/ eogateway/tools/snapESA. (n.d.). Sentinel-1. Sentinels. Retrieved March 17, 2022. Retrieved from: https: //sentinels.copernicus.eu/web/sentinel/missions/sentinel-1Filipponi, F. (2019). Sentinel-1 GRD preprocessing workflow. In Multidisciplinary digital publishing institute proceedings (Vol. 18, No. 1, p. 11).Guth, P. L., Van Niekerk, A., Grohmann, C. H., Muller, J. P., Hawker, L., Florinsky, I. V., ... & Strobl, P. (2021). Digital elevation models: Terminology and definitions. Remote Sensing, 13(18), 3581.Han, L., Liu, Z., Ning, Y., & Zhao, Z. (2018). Extraction and analysis of geological lineaments combining a DEM and remote sensing images from the northern Baoji loess area. Advances in Space Research, 62(9), 2480-2493Javhar, A., Chen, X., Bao, A., Jamshed, A., Yunus, M., Jovid, A., & Latipa, T. (2019). Comparison of multi-resolution optical Landsat-8, Sentinel-2 and radar Sentinel-1 data for automatic lineament extraction: A case study of Alichur area, SE Pamir. Remote Sensing, 11(7), 778.Jong, S. M. D., Meer, F. D., & Clevers, J. G. (2004). Basics of remote sensing. In Remote sensing image analysis: Including the spatial domain (pp. 1-15). Springer, Dordrecht.Li, X. (2006). Understanding 3D analytic signal amplitude. Geophysics, 71(2), L13- L16.Lowrie, W., & Fichtner, A. (2020). Fundamentals of geophysics. Cambridge university press.Manuel, R., Brito, M. D. G., Chichorro, M., & Rosa, C. (2017). Remote sensing for mineral exploration in central Portugal. Minerals, 7(10), 184.Marston, B. E., Jenny, B. (2015). Improving the representation of major landforms in analytical relief shading. International Journal of Geographical Information Science, 29(7), 1144-1165.Mårtensson, U. (2011). Introduction to Remote Sensing and Geographical Information Systems.Middleton, M., Schnur, T., Sorjonen-Ward, P., & Hyv¨onen, E. (2015). Geological lineament interpretation using the object-based image analysis approach: results of semi-automated analyses versus visual interpretation. Geological Survey of Finland, Special Paper, 57, 135-154.Mostafa, M. E., Qari, M. Y. H. (1995). An exact technique of counting lineaments. Engineering Geology, 39(1-2), 5-15.NASA. (2021). Landsat 8. NASA. Retrieved from https://landsat.gsfc.nasa.gov/satellites/landsat8/Pour, A. B., Hashim, M. (2015). Structural mapping using PALSAR data in the Central Gold Belt, Peninsular Malaysia. Ore Geology Reviews, 64, 13-22.Prost, G. L. (2013). Remote sensing for geoscientists (pp. 309-310). New York: CRC Press.Barbosa, J. D. P. D. O., Chaves, C. L., Costa Neto, M. C. D., Anjos, G. C. D., & Costa, L. T. D. R. (2015). Geologia e recursos minerais da folha Macapá-NA. 22-YD, estado do Amapá.GeoSGB (n.d.) Folha Macapá - NA.22-Y-D. Retrieved from: https://geosgb.cprm. gov.br/geosgb/downloads$_$en.htmlHorikava, É. H. (2017) & Scarpelli, W., . Gold, iron and manganese in central Amapá, Brazil. Brazilian Journal of Geology, 47, 703-721.Rajesh, H. M. (2004). Application of remote sensing and GIS in mineral resource mapping-An overview. Journal of mineralogical and Petrological Sciences, 99(3), 83- 103.Roest, W. R., Verhoef, J., Pilkington, M. (1992). Magnetic interpretation using the 3-D analytic signal. Geophysics, 57(1), 116-125.Rosa, J. W. C., Rosa, J. W. C., & Fuck, R. A. (2014). Geophysical structures and tectonic evolution of the southern Guyana shield, Brazil. Journal of South American Earth Sciences, 52, 57-71.Salem, A., Williams, S., Fairhead, J. D., Ravat, D., & Smith, R. (2007). Tilt-depth method: A simple depth estimation method using first-order magnetic derivatives. The leading edge, 26(12), 1502-1505.Sentinel-1 Toolbox, (n.d.). Available online: https://sentinels.copernicus.eu/ web/sentinel/toolboxes/sentinel-1Vincent, R. K. (1997). Fundamentals of geological and environmental remote sensing. Prentice Hall.Schobbenhaus, C., HE, A., GR, D. (1982). 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