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Open AccessArticle

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

1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, No. 818, South Beijing Road, Urumqi 830011, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
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Institute of Geology, Earthquake Engineering and Seismology, Tajikistan Academy of Sciences, Dushanbe 735823, Tajikistan
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Research Center for Ecology and Environment of Central Asia (Dushanbe), Dushanbe 735823, Tajikistan
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Key Laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research, Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China
6
Institut für Erd-und Umweltwissenschaften, Universität Potsdam, 14476 Potsdam, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(7), 778; https://doi.org/10.3390/rs11070778
Received: 4 March 2019 / Revised: 19 March 2019 / Accepted: 20 March 2019 / Published: 1 April 2019
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively. View Full-Text
Keywords: image enhancement; automatic lineament extraction; Landsat-8; Sentinel-1; Sentinel-2; structural mapping image enhancement; automatic lineament extraction; Landsat-8; Sentinel-1; Sentinel-2; structural mapping
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MDPI and ACS Style

Javhar, A.; Chen, X.; Bao, A.; Jamshed, A.; Yunus, M.; Jovid, A.; Latipa, T. 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. 2019, 11, 778.

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