Geomatics and Environmental Engineering, vol. 14, no. 3

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Vol. 14 No. 3 (2020): Geomatics and Environmental Engineering

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Submitted
Jan 22, 2020
Accepted
Apr 20, 2020
Published
Sep 21, 2020
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This work is licensed under a Creative Commons Attribution 4.0 International License.

Processing and Analysis of ASTER and Landsat 8 Scenes to Aid in Geological Mapping: A Case Study of Murchison Greenstone Belt Area, South Africa

https://doi.org/10.7494/geom.2020.14.3.107
Abraham Thomas
Geophysics and Remote Sensing Unit, Council for Geoscience, Pretoria
https://orcid.org/0000-0003-4412-3152

Corresponding Author(s) : Abraham Thomas

athomas1965@gmail.com

Geomatics and Environmental Engineering, Vol. 14 No. 3 (2020): Geomatics and Environmental Engineering

Abstract

This paper presents processing and analysis results of ASTER and Landsat 8 scenes to aid in geological mapping of Murchison Greenstone Belt region of Limpopo Province, South Africa. Images of ASTER acquired in 2005 and 2006 and Landsat 8 acquired in 2019 were downloaded and subset covering 5 mapping sheets was extracted. Images of different band ratios and band combinations were experimented using ENVI and SNAP software to identify suitable band/band ratio combinations to produce FCCs that enabled discrimination of lithology, structural features, lineaments, alteration and iron oxides, land/water, surface features, vegetation cover and healthy vegetation etc. Using DEM data, slope and shaded relief were also prepared that enabled the identification of the extent of protruded outcrops, some structural features and lineaments using different FCC displays. These datasets prepared in ENVI file format were later exported to GeoTiff/Imagine file for display in ArcMap by the mapping geologists. FCCs made in various band combinations, ratio combination and also with slope are useful in discriminating geology, structural features and protruded outcrops including dykes that are not so visible in a true colour image of the same resolution. This study could illustrate the usefulness of remote sensing analysis to aid in geological mapping using freely available ASTER and Landsat 8 data.

Keywords

ASTER Landsat 8 Murchison Greenstone Belt geological mapping
Thomas, A. (2020). Processing and Analysis of ASTER and Landsat 8 Scenes to Aid in Geological Mapping: A Case Study of Murchison Greenstone Belt Area, South Africa. Geomatics and Environmental Engineering, 14(3), 107–123. https://doi.org/10.7494/geom.2020.14.3.107
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References
  1. Pournamdari M., Hashim M., Pour A.: Application of ASTER and Landsat TM Data for Geological Mapping of Esfandagheh Ophiolite Complex, Southern Iran. Resource Geology, vol. 64, 2014, pp. 233–246. https://doi.org/10.1111/rge.12038.
  2. Amer R., Kusky T., Ghulam A.: Lithological mapping in the Central Eastern Desert of Egypt using ASTER data. Journal of African Earth Sciences, vol. 56(2–3), 2010, pp. 75–82. https://doi.org/10.1016/j.jafrearsci.2009.06.004.
  3. Gannouni S., Gabtni H.: Structural Interpretation of Lineaments by Satellite Image Processing (Landsat TM) in the Region of Zahret Medien (Northern Tunisia). Journal of Geographic Information System, vol. 7(2), 2015, pp. 119–127. https://doi.org/10.4236/jgis.2015.72011.
  4. Mohammadizad R., Arfania R.: Advanced investigation of remote sensing to geological mapping of Zefreh region in central Iran. Open Journal of Geology, vol. 7(10), 2017, pp. 1509–1529. https://doi.org/10.4236/ojg.2017.710101.
  5. Mwaniki M.W., Moeller M.S., Schellmann G.: A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: A case study of central region Kenya. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XL-7/W3, 2015, pp. 897–903. https://doi.org/10.5194/isprsarchives-XL-7-W3-897-2015.
  6. Abdelaziz R., El Rahman Y.A., Wilhelm S.: Landsat 8 data for chromite prospecting in the Logar Massif, Afghanistan. Heliyon, vol. 4(2), 2018, pp. 1–18. https://doi.org/10.1016/j.heliyon.2018.e00542.
  7. Amusuk D.J., Hashim M., Pour A.B., Musa S.I.: Utilization of Landsat 8 data for lithological mapping of basement rocks of Plateau State North Central Nigeria. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-4/W1, 2016, pp. 335–337. https://doi.org/10.5194/isprs-archives-XLII-4-W1-335-2016.
  8. Ourhzif Z., Algouti A., Algouti A., Hadach F.: Lithological mapping using Landsat8 OLI and ASTER multispectral data in Imini Ounilla district South High Atlas of Marrakech. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W132019, pp. 1255–1262. https://doi.org/10.5194/isprs-archives-XLII-2-W13-1255-2019.
  9. Banerjee K., Jain M.K., Panda S., Jeyaseelan A.T.: Landsat 8 OLI data for identification of hydrothermal alteration zone in Singhbhum Shear Zone using successive band depth difference technique – a new image processing approach. Current Science, vol. 116(10), 2019, pp. 1639–1647. https://www.currentscience.ac.in/Volumes/116/10/1639.pdf [access: 12.06.2020].
  10. Prasath L.R., Kusuma K.N.: Lithological mapping using Landsat 8 OLI and ASTER TIR multispectral data: A comparative study. International Journal of Advanced Remote Sensing and GIS, vol. 7(1), 2018, pp. 2728–2745. https://doi.org/10.23953/cloud.ijarsg.369.
  11. Shimoda H., Kimura T.: Missions and Sensors. [in:] Shunlin Liang (ed.), Comprehensive Remote Sensing, Elsevier, 2018, p. 3134.
  12. Westen C.J. van: Geo information tools for landslide risk assessment: an overview of recent developments. [in:] Lacerda W., Erlich M., Fontoura S.A.B., Sayao A.S.F. (eds.), Landslides: Evaluation and Stabilization, CRC Press, 2004, pp. 39–56.
  13. Buis A.: NASA, Japan Make ASTER Earth Data Available at No Cost. NASA Jet Propulsion Laboratory, April 1, 2016. https://www.jpl.nasa.gov/news/news.php?feature=6253 [access: 26.02.2020].
  14. USGS (no date): USGS EROS Archive – Landsat Archives – Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) Level 1 Data Products. https://doi.org/10.5066/F71835S6.
  15. ESA-STEP: ESA SNAP Toolbox surpasses 300000 downloads. 2018. http://step.esa.int/main/esa-snap-toolbox-surpasses-300000-downloads/ [access: 10.09.2019].
  16. ESA-STEP: SNAP. 2018. http://step.esa.int/main/toolboxes/snap/ [access: 10.09.2019].
  17. Data.Gov: ASTER L2 Surface Reflectance VNIR and Crosstalk Corrected SWIR V003. NASA LP DAAC, 2019. https://catalog.data.gov/dataset/aster-l2-surface-reflectance-vnir-and-crosstalk-corrected-swir-v003 [access: 29.02.2020].
  18. NASA EarthData: AST_07XT v003 – ASTER L2 Surface Reflectance VNIR and Crosstalk Corrected SWIR. USGS, 2004. https://lpdaac.usgs.gov/products/ast_07xtv003/ [access: 2.03.2020].
  19. Kalinowski A., Oliver S.: ASTER Mineral Index Processing Manual, Geoscience Australia. 2004. https://www.ga.gov.au/webtemp/image_cache/GA7833.pdf [access: 2.03.2020].
  20. van der Werff H., van der Meer F.: Sentinel 2A MSI and Landsat 8 OLI Provide Data Continuity for Geological Remote Sensing. Remote Sensing, vol. 8(11), 2016, pp. 883 (1–16). https://doi.org/10.3390/rs8110883.
  21. NASA-JPL: ASTER Instrument Characteristics. Jet Propulsion Laboratory, 2004. https://asterweb.jpl.nasa.gov/characteristics.asp [access: 4.03.2020].
  22. Loyd C.: Landsat 8 Bands. NASA Landsat Science, 2013. https://landsat.gsfc.nasa.gov/landsat-8/landsat-8-bands/ [access: 4.03.2020].
  23. Garzelli A., Aiazzi B., Alparone L., Lolli S., Vivone G.: Multispectral Pansharpening with Radiative Transfer Based Detail Injection Modeling for Preserving Changes in Vegetation Cover. Remote Sensing, vol. 10(8), 2018, pp. 1308 (1–18). https://doi.org/10.3390/rs10081308.
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