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  • 标题:Geological Lineament Assessment from Passive and Active Remote Sensing Imageries
  • 本地全文:下载
  • 作者:Ainyyafiatty Arifin ; Nor A.Adnan
  • 期刊名称:International Journal of Geospatial and Environmental Research
  • 印刷版ISSN:2332-2047
  • 出版年度:2021
  • 卷号:8
  • 期号:2
  • 语种:English
  • 出版社:University of Wisconsin Milwaukee
  • 摘要:Lineament is any extensive linear feature on the Earth’s surface that can be identified when there is a change in the topographical data. The advancement of technologies in remote sensing and Geographical Information Sciences (GIS) lead to the various studies and methods in mapping lineaments due to the availability of data from small to large scale areas. Lineament can be extracted from remote sensing data either with manual, semi-automatic or automatic image processing techniques that incorporate in numerous remote sensing and GIS software. Manually digitizing or tracing the aerial photograph is a subjective method as the lineament will be interpreted based on geomorphological understanding in determining the possible relationship between the linear features. Therefore, this research proposed automatic lineaments extraction techniques that less time-consuming compared to the semi-automatic and manual approaches as the algorithms for lineament detection have been integrated in the software. The aim of this study is to compare multi-sensors active and passive remote sensing technologies of Landsat 8, Sentinel 1 and Sentinel 2 satellite data in lineament mapping, based on automatic image processing tools between the state boundaries of Selangor and Pahang in Peninsular Malaysia. Overall, statistics descriptions, density, and orientations analysis indicate a correlation between the extracted lineaments and the geology of the area. Furthermore, lineaments extracted from Sentinel 1 radar images show the most significant result. Actually, the accuracy assessment of matching lineaments provides the Sentinel 1 as the best sensor compared to both the Sentinel 2 and the Landsat 8, with root mean square errors (RMSE) equal to 1.660, 1.743 and 2.757, respectively. Therefore, both remote sensing technologies and geographical information sciences can be effectively integrated within the field of structural geology, thus allowing the mapping of lineaments in a more practical, cost and time-effective way.
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