Applying optimum fusion method to improve lithological mapping of sedimentary rocks using sentinel-2 and ASTER satellite images

Springer Science and Business Media LLC - Tập 15 - Trang 1765-1778 - 2022
Mostafa Kabolizadeh1, Kazem Rangzan1, Seyyed Sajedin Mousavi2, Ehsan Azhdari1
1Remote Sensing and GIS Department, Earth Sciences Faculty, Shahid Chamran University of Ahvaz. Ahvaz, Khouzestan, Iran
2Geology Department, Earth Sciences Faculty, Shahid Chamran University of Ahvaz. Ahvaz, Khouzestan, Iran

Tóm tắt

This study was set the yield a precise map of geological formations appliying satellite image fusion techniques. Geologic maps are one of the most valuable sources for understanding the geological conditions of a region used to show the spread of different rock and soil outcrops. In the present research, the fusion of ASTER and Sentinel-2 images were applied using Brovey Transform (BT), Gram-Schmidt (GS), Color Normalized (CN), Smoothing Filter-based Intensity Modulation (SFIM) and Discrete Wavelet Transform (DWT) methods to prepare the lithological map. Based on the results of the employed methods, DWT and BT methods are good in terms of providing spectral and spatial information, respectively. The results also showed that the SFIM method has appropriate spectral and spatial accuracy. At the classification stage, all fused images were processed through supervised classification algorithm of Support Vector Machine (SVM) to identify and separate the geological formations of the study area. The evaluation of the classifications results demonstrated that the SVM method used in the fused images by SFIM method, with 83.16 overall accuracy and 0.82 kappa coefficient has evidential results for lithological mapping.

Tài liệu tham khảo

Acerbi-Junior F, Clevers J, Schaepman M (2006) The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna. Int J Appl Earth Obs Geoinf 8(4):278–288 Al-Nahmi F, Saddiqia O, Hilali A, Rhinane H, Baidder L, El arabi H, Khanbari K (2017) Application of remote sensing in geological mapping, case study Al-Maghrabaharea – Hajjah region, Yemen. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. https://doi.org/10.5194/isprs-annals-IV-4-W4-63-2017 An Z, Shi Z (2014) An improved-SFIM fusion method based on the calibration process. Optik 125(14):3764–3769 Bachri I, Hakdaoui M, Raji M, Teodoro AC, Benbouziane A (2019) Machine learning algorithms for automatic lithological mapping using remote sensing data: a case study from Souk Arbaa Sahel, Sidi Ifni Inlier, western anti-Atlas. Morocco Int J Geoinf 8(248):1–20 Bashirpour M, Valadan ZM, J, Maghsoudi Y, (2017) Effect of different SRFs on time series of spectral indices, between sentinel-2 and other sensors for the purpose of vegetation land cover monitoring. J Geomat Sci Tech 5:122–140 Beiranvand pour AB, Hashim M, Hong JK, Park Y, (2019) Lithological and alteration mineral mapping in poorly exposed lithologies using Landsat-8 and ASTER satellite data: North-eastern Graham Land, Antarctic Peninsula. Ore Geol Rev 118:112–133 Bhan SK, Krishnanunni K (1983) Applications of remote sensing techniques to geology. Procceding Indian Acad Sci (Engg Sei) 6(4):297–311 Black M, Riley TR, Ferrier G, Fleming AH, Fretwell PT (2016) Automated lithological mapping using airborne hyperspectral thermal infrared data: A case study from Anchorage Island, Antarctica. Remote Sens Environ 176:225–241 Chen X, Warner TA, Campagna DJ (2010) Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada: A rule-based system. Int J Remote Sen 31:1733–1752 Chisense C, Engels J, Hahn M, Gulch E (2012) Pansharpening of hyperspectral images in urban areas, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. ISPRS International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences. https://doi.org/10.5194/isprsarchives-XXXIX-B7-387-2012 Coluzzi R, Imbrenda V, Lanfredi M, Simoniello T (2018) A first assessment of the Sentinel-2 Level 1-C cloud mask product to support informed surface analyses. Remote Sens Environ 217:426–443 Diaz D, Molina A, Hahn WD (2018) Effect of laser irradiance and wavelength on the analysis of gold- and silverbearing minerals with laser-induced breakdown spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy 145:86–95 Dhruval L, Richard S (2015) Advance SFIM technique for image fusion in remote sensing domain. Int J Innov Res Sci Eng Technol 2(1):148–161 Fal S, Maanan M, Baidder L, Rhinane H (2018) The contribution of Sentinel-2 satellite images for geological mapping in the south of Tafilalet basin (Eastern Anti-Atlas, Morocco). 5th International Conference on Geoinformation Science – Geoadvances. https://doi.org/10.5194/isprs-archives-XLII-4-W12-75-2019 Ge W, Cheng Q, Ging L, Armenakis C, Ding H (2018) Lithological discrimination using ASTER and Sentinel-2A in the Shibanjing ophiolite complex of Beishan orogenic in Inner Mongolia. China Adv Space Res 62(7):1702–1716 Ghaedrahmati R, Fathian N, Amiri H (2008) Discrimination of rock units of Isfahan’s Irankoh region using image classification algorithm on satellite data. J Eng Geol 2(2):395–413 Hedley J, Roelfsema C, Koetz B, Phinn S (2012) Capability of the Sentinel 2 mission for tropical coral reefmapping and coral bleaching detection. Remote Sens Environ 120:145–155 Hou Z, Li W, Li L, Tao R, Du Q (2021) Hyperspectral change detection based on multiple morphological profiles. IEEE Trans Geosci Remote Sens 60:1–12 Hsu C, Chang C, Lin C (2003) A practical guide to support vector classification. https://www.csie.ntu.edu.tw/~cjlin/talks/freiburg.pdf Hsu C, Chang C, Lin C (2010) A practical guide to support vector classification. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.224.4115 Jagruti V (2014) Implementation of discrete wavelet transform based image fusion. IOSR J Electron Commun Eng 9:107–109 James GA, Wynd JG (1965) Stratigraphic nomenclature of the Iranian oil consortium agreement Area. Bull AAPG 49(12):2182–2245 Karatzoglou A, Meyer D, Hornik K (2006) Support vector machines in R. J Stat Software 15(9):1–8 Lakshmi Ram Prasath H, Kusuma KN (2018) Lithological mapping using Landsat 8 OLI and ASTER TIR multispectral data: a comparative study. Int J Adv Remote Sens GIS7 1:2728–2745 Leverington DW, Moon WM, Leverington DW, Moon WM (2012) Landsat-TM-based discrimination of lithological units associated with the purtuniq ophiolite, Quebec, Canada. Remote Sens 4:1208–1231 Masoumi F, Ranjbar H (2012) Mapping of hydrothermally altered areas using ASTER and ETM+ data in northern half of Baftgeological map. Q J Geosci 20(79):121–128 Melgani F, Bruzzone L (2004) Classification of hyperspectral remote sensing images with support vector machines. IEEE Trans Geosci Remote Sens 42(8):1778–1790 Mohebi A, Mirnejad H, Lentz D, Behzadi M, Dolati A, Kani A, Taghizadeh H (2015) Controls on porphyry Cu mineralization around Hanza Mountain, south-east of Iran: an analysis of structural evolution from remote sensing, geophysical, geochemical and geological data. Ore Geol Rev 69:187–198 Nex F, Duarte D, Steenbeek A, Kerle N (2019) Towards real-time building damage mapping with low-cost UAV solutions. Remote Sensing 11(3):287 Nikolakopoulos KG, Tsombos IP, Photiades A, Psonis K, Zervakou A (2013) Using remote sensing multispectral data and GIS technique s for the geological mapping of Halki Island. International Congress of Exploration and Exploitation of Mineral Resources. https://doi.org/10.12681/bgsg.10988 Nikolakopoulos KG, Vaiopoulos DA, Skianis GA (2007) Use of multitemporal remote sensing data for mapping the Alfios river network changes from 1977 to 2000. Geocarto Int 22(4):251–271 Ninomiya Y, Fu B, Cudahy TJ (2005) Detecting lithology with advanced apaceborne thermal emission and reflection radiometer (ASTER) multispectral thermal infrared radiance-at-sensor data. Remote Sens Environ 99(1–2):127–139 Pohl C, Van Genderen J (2016) Remote sensing image fusion: apractical guide, 1st edn. CRC Press, Boca Raton, p 288 Pour AB, Hashim M (2015) Integrating PALSAR and ASTER data for mineral deposits exploration in tropical environments: a case study from Central Belt, Peninsular Malaysia. Int J Image Data Fusion 6(2):170–188 Qasim M, Khan SD, Haider R (2022) Integration of multispectral and hyperspectral remote sensing data for lithological mapping in Zhob Ophiolite. Western Pakistan Arabian Journal of Geosciences 15(7):1–19 Ranchin T, Wald L (2000) Fusion of high spatial and spectral resolution images: the ARSIS concept and its implementation. Photogramm Eng Remote Sens 66(1):49–61 Raharimahefa T, Kusky TM (2009) Structural and remote sensing analysis of the Betsimisaraka suture in northeastern Madagascar. Gondwana Res 15:14–27 Salehi S, Mielke C, Pedersen CB, Olsen SD (2019) Comparison of ASTER and Sentinel-2 spaceborne datasets for geological mapping: a case study from North-East Greenland. Geol Surv Den Greenl Bull 43:1–6 Sekandari M, Masoumi I, Beiranvand Pour A, Muslim MA, Rahmani O, Hashim M, Aminpour SM (2020) Application of Landsat-8, Sentinel-2, ASTER and WorldView-3 spectral imagery for exploration of carbonate-hosted Pb-Zn deposits in the Central Iranian Terrane (CIT). Remote Sensing 12(8):1239 Serbouti I, Raji M, Hakdaoui M (2022) Lithological mapping for a semiarid area using GEOBIA and PBIA machine learning approaches with sentinel-2 imagery: case study of Skhour Rehamna, Morocco. In: Barramou F, El Brirchi EH, Mansouri K, Dehbi, Y. (eds) Geospatial Intelligence. Advances in Science, Technology and Innovation. Springer, Cham, pp 143–153 Tangestani MH, Shayeganpour S (2020) Mapping a lithologically complex terrain using Sentinel-2A data: a case study of Suriyan area, southwestern Iran. Int J Remote Sens 41(9):3558–3574 Testa F, Villanueva C, Cooke D, Zhang L (2018) Lithological and hydrothermal alteration mapping of epithermal, porphyry and tourmaline Breccia districts in the Argentine Andes using ASTER imagery. Remote Sens 10:203 Van der Meer FD, Van der Werff HMA, Van Ruitenbeek FJA (2014) Potential of ESA’s Sentinel-2 for geological applications. Remote Sens Environ 148:124–133 Van der Werff H, Van der Meer F (2015) Sentinel-2 for mapping iron absorption feature parameters. Remote Sens 7:12635–12653 Vapnik V (1998) Statistical learning theory. Wiley, New York Ye B, Tian S, Cheng Q, Ge Y (2020) Application of lithological mapping based on advanced hyperspectral imager (AHSI) imagery onboard Gaofen-5 (GF-5) satellite. Remote Sensing 12(23):3990 Yu CNJ, Joachims T (2009) Learning structural SVM with latent variables. Proceedings of the 26th Annual International Conference on Machine Learning. https://doi.org/10.1145/1553374.1553523 Zhang X, Pazner M, Duke N (2007) Lithologic and mineral information extraction for gold exploration using ASTER data in the south Chocolate Mountains (California). ISPRS J Photogramm Remote Sens 62:271–282 Zheng Q, Lyu HM, Zhou A, Shen SL (2021) Risk assessment of geohazards along Cheng-Kun railway using fuzzy AHP incorporated into GIS. Geomat Nat Haz Risk 12(1):1508–1531 Zheng Q, Huang W, Cui X, Shi Y, Liu L (2018) New spectral index for detecting wheat yellow rust using sentinel-2 multispectral imagery. Sensors 18(3):868