Abstract
In recent years, automatic lineament extraction has gained huge popularity as it circumvents the issues such as errors and time constraints associated with manual extraction procedure. Another impediment in the lineament extraction process is that linear features existing near sub-surface or occluded due to vegetation cover cannot be identified solely by optical data. To mitigate these issues, a multi-sensor fusion-based automatic extraction process using EO-based optical and SAR data is proposed. Use of moderate resolution optical data such as ASTER minimizes erroneous identification and misclassification of anthropogenic features as geological features. In addition to this, a component loading-based band selection approach is proposed to select the most informative bands from the available optical bands for improved extraction of lineament features. Finally, a new HSV-based mapping method for visualization and directional analysis of the extracted linear features is discussed. The results are validated using the published seismo-tectonic map of the region and field investigation studies which corroborates that the proposed algorithm can successfully extract most of the geological lineaments in the study area with minimum errors.
Research highlights
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This research sheds light on the use of multi-sensor data for understanding the tectonic setup of an area.
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This research is highly useful for the practices such as geological mapping and weak zone demarcation using EO data of the denied areas
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Further, the outcome of the results can also be used in mass movement vulnerability assessment of the area for mitigation and planning purposes.
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Further, this also increases robustness in band selection procedure for lineament extraction.
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References
Abbate G, Cavalli R M, Pascucci S, Pignatti S and Poscolier M 2006 Relations between morphological settings and vegetation covers in a medium relief landscape of Central Italy; Ann. Geophys. 49(1) 153–165.
Abdi H and Williams L J 2010 Principal component analysis; Wiley Interdiscip. Rev. Comput. Stat. 2(4) 433–459, https://doi.org/10.1002/wics.101.
Aldharab H S, Ali S A, Ikbal J and Ghareb S A 2018 Spatial analysis of lineaments and their tectonic significance using landsat imagery in Alarasah area-southeastern central Yemen; J. Geogr. Environ. Earth Sci. Int., https://doi.org/10.9734/jgeesi/2018/45638.
Baisantry M and Sao A K 2019 Band selection using segmented PCA and component loadings for hyperspectral image classification; In: IGARSS 2019–2019 IEEE International Geoscience and Remote Sensing Symposium, pp. 3812–3815, https://doi.org/10.1109/IGARSS.2019.8899002.
Boyer R and McQueen J 1964 Comparison of mapped rock fractures and airphoto linear features; Photogramm. Eng. Rem. Sens. 30(4) 630–635.
Cadima J and Jolliffe I T 1995 Loading and correlations in the interpretation of principle components; J. Appl. Stat. 22(2) 203–214, https://doi.org/10.1080/757584614.
Canny J 1986 A computational approach to edge detection; IEEE Trans. Pattern Anal. Mach. Intell., PAMI 8(6) 679–698, https://doi.org/10.1109/TPAMI.1986.4767851.
Comaniciu D and Meer P 2002 Mean shift: A robust approach toward feature space analysis; IEEE Trans. Pattern Anal. Mach. Intell., https://doi.org/10.1109/34.1000236.
Cross A and Wadge G 1988 Geological lineament detection using the Hough Transform; In: International Geoscience and Remote Sensing Symposium, “Remote Sensing: Moving Toward the 21st Century”, Vol. 3, pp. 1779–1782.
Dasgupta S and Mukherjee S 2019 Remote sensing in lineament identification: Examples from western India; In: Problems and solutions in structural geology and tectonics: Development in structural geology and tectonics book series, Candice Janco, pp. 205–221.
Dey S and Sarkar P 2012 Vegetation covers as indicator of seismo-tectonic environment: An integrated geophysical study in north Baromura hill, India; Environ. Earth Sci., https://doi.org/10.1007/s12665-012-1697-9.
Dunteman G H 1989 Principal components analysis; https://doi.org/10.4135/9781412985475.
Ehlers M, Klonusa S, Strand P J A and Rosso P 2010 Multi-sensor image fusion for pansharpening in remote sensing; Int. J. Image Data Fusion 1(1) 25–45.
Javhar A, Chen X, Bao A, Jamshed A, Yunus M, Jovid A and 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 Sens. 11(7) 778, https://doi.org/10.3390/rs11070778.
Jollife I T and Cadima J 2016 Principal component analysis: A review and recent developments; Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., https://doi.org/10.1098/rsta.2015.0202.
Karunakaran C and Rao R 1979 Status of hydrocarbon in the Himalayan regions: Contributions to stratigraphy and structure; In: Geological Survey of India, Miscellaneous Publication, pp. 1–66.
Kong H, Akakin H C and Sarma S E 2013 A generalized laplacian of gaussian filter for blob detection and its applications; IEEE Trans. Cybern., https://doi.org/10.1109/TSMCB.2012.2228639.
Kowalik W S and Glenn W E 1987 Image processing of aeromagnetic data and integration with Landsat images for improved structural interpretation; Geophysics 52 875–884.
Kumar Singh A, Parkash B, Mohindra R, Thomas J V and Singhvi A K 2001 Quaternary alluvial fan sedimentation in the Dehradun Valley Piggyback Basin, NW Himalaya: Tectonic and palaeoclimatic implications; Basin Res., https://doi.org/10.1046/j.0950-091X.2001.00160.x.
Mah A, Taylor G R, Lennox P and Balia L 1995 Lineament analysis of landsat thematic mapper images, northern-territory, Australia; Photogramm. Eng. Remote Sensing 61 761–773.
Masoud A and Koike K 2006 Tectonic architecture through Landsat-7 ETM+/SRTM DEM-derived lineaments and relationship to the hydrogeologic setting in Siwa region, NW Egypt; J. Afr. Earth Sci. 45 467–477, https://doi.org/10.1016/j.jafrearsci.2006.04.005.
Mearns B 2010 Using quantum GIS: A summary; https://www.academia.edu/689903/Using_Quantum_GIS_A_Summary
Meer P and Georgescu B 2001 Edge detection with embedded confidence; IEEE Trans. Pattern Anal. Mach. Intell. 23(12) 1351–1365, https://doi.org/10.1109/34.977560.
Mussakowski R, Trowell N F and Heather K B 1991 Digital integration of remote sensing and geosciences data for the Goudreau-Lochalsh Area, Wawa, Ontario; Can. J. Remote Sens. 17 162–173.
Mwaniki M W, Moeller M S and Schellmann G 2015 A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: A case study of central region Kenya; ISPRS – Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XL-7/W3(7W3) 897–903, https://doi.org/10.5194/isprsarchives-XL-7-W3-897-2015.
Ölgen K M 2004 Determining lineaments and geomorphic features using Landsat 5-TM data on lower Bakırçay plain, Western Turkey; Aegean Geogr. J. 13 47–57.
Prost G L 2013 Remote Sensing for Geoscientists, CRC Press, 504p.
QGIS 2014 Gentle introduction to QGIS; http://docs.qgis.org/2.0/en/docs/gentle_gis_introduction/.
Reboussin D 2005 Wind rose temperature wind rose; http://wiki.gis.com/wiki/index.php/Wind_rose.
Reinhard E, Ashikhmin M, Gooch B and Shirley P 2001 Colour transfer between images; IEEE Comput. Graph. Appl., https://doi.org/10.1109/38.946629.
Salui C L 2018 Methodological validation for automated lineament extraction by LINE method in PCI Geomatica and MATLAB based Hough transformation; J. Geol. Soc. India, https://doi.org/10.1007/s12594-018-1015-6.
Sharma S 2012 Catastrophic hydrological event of 18 and 19 September 2010 in Uttarakhand, Indian Central Himalaya: An analysis of rainfall and slope failure; Curr. Sci. 102(2) 327–331.
Sidiropoulou Velidou D, Tolpekin V A, Stein A and Woldai T 2015 Use of Gestalt theory and random sets for automatic detection of linear geological features; Math. Geosci. 47(3) 249–276, https://doi.org/10.1007/s11004-015-9584-z.
Singh A K, Parkash B and Choudhury P R 2007 Integrated use of SRM, Landsat ETM+ data and 3D perspective views to identify the tectonic geomorphology of Dehradun valley, India; Int. J. Remote Sens., https://doi.org/10.1080/01431160600993397.
Sinha S and Sinha R 2016 Geomorphic evolution of Dehra Dun, NW Himalaya: Tectonics and climatic coupling; Geomorphology, https://doi.org/10.1016/j.geomorph.2016.05.002.
Srivastava V, Mukul M and Barnes J B 2016 Main Frontal thrust deformation and topographic growth of the Mohand Range, northwest Himalaya; J. Struct. Geol., https://doi.org/10.1016/j.jsg.2016.10.009.
Sumaryono, Triana Y D, Hidayati S, Wahyudi D R, Muslim D and Sulaksana N 2015 Control morphology to the landslide Induced Earthquake: Case study Padang Pariaman, Sumatra; In: 10th Asian Regional Conference of IAEG, pp. 1–6.
Thakur V and Pandey A 2004a Late Quaternary tectonic evolution of Dun in fault bend/propagated fold system, Garhwal Sub-Himalaya; Curr. Sci. 87.
Thakur V C and Pandey A 2004b Active deformation of Himalayan Frontal Thrust and piedmont zone south of Dehradun in respect of seismotectonics of Garhwal Himalaya; Him. Geol. 25 23–31.
Thakur V C, Pandey A K and Suresh N 2007 Late Quaternary-Holocene evolution of Dun structure and the Himalayan Frontal Fault zone of the Garhwal Sub-Himalaya, NW India; J. Asian Earth Sci., https://doi.org/10.1016/j.jseaes.2006.02.002.
Theodoridis S and Koutroumbas K 2009 Feature generation I: Data transformation and dimensionality reduction; In: Pattern recognition, https://doi.org/10.1016/B978-1-59749-272-0.50008-6.
Thomas C, Ranchin T, Wald L and Chanussot J 2008 Synthesis of multispectral images to high spatial resolution: A critical review of fusion methods based on remote sensing physics; IEEE Trans. Geosci. Remote Sens. 46(5) 1301–1312, https://doi.org/10.1109/TGRS.2007.912448.
Weeks A R 1996 Colour Image processing; In: Fundamentals of Electronic Image Processing, pp. 228–288.
Zhang J 2010 Multi-source remote sensing data fusion: Status and trends; Int. J. Image Data Fusion 1(1) 5–24.
Zhang N and Zhou K 2017 Identification of hydrothermal alteration zones of the Baogutu porphyry copper deposits in northwest China using ASTER data; J. Appl. Remote Sens. 11(1) 1–19, https://doi.org/10.1117/1.JRS.11.015016.
Zou H and Xue L 2018 A selective overview of sparse principal component analysis; Proc. IEEE, https://doi.org/10.1109/JPROC.2018.2846588.
Acknowledgement
The authors wish to express their sincere gratitude to Dr L K Sinha (Retd.), Director, DTRL (Now DGRE) for providing the necessary support to carry out the research work in the laboratory and to publish the work.
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The first two authors of the manuscript have almost equally contributed to the article in both processing and analysis of the data. The third author has placed the idea of the work in front of the first two authors and guided along the way. Also, all the three authors have equally contributed to the completion of the manuscript.
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Communicated by Munukutla Radhakrishna
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Dhara, M., Baisantry, M. & Prusty, G. Automatic extraction and analysis of lineament features using ASTER and Sentinel 1 SAR data. J Earth Syst Sci 131, 111 (2022). https://doi.org/10.1007/s12040-022-01851-y
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DOI: https://doi.org/10.1007/s12040-022-01851-y