Welcome to visit Geoscience!

Geoscience ›› 2014, Vol. 28 ›› Issue (5): 1068-1076.

• Engineering Geology and Environmental Geology • Previous Articles     Next Articles

Ancient Landslide Identification and Characteristics Using Remote Sensing along Eastern Edge of the Heqing Basin

GUO Zhao-cheng1, NIE Hong-feng1,YANG Liang2,TU Jie-nan1,HE Peng1,TONG Li-qiang1   

  1. (1.China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing100083, China; 2.Geological and Mineral Survey Institute of Inner Mongolia, Hohhot, Inner Mongolia010010,China)
  • Online:2014-10-25 Published:2014-12-29

Abstract:

Large ancient landslides offer clues to the regional tectonics, climate change and paleoenvironment evolution that would be able to influence the development of human society in the future. It is difficult to identify ancient landslides, but with the development of remote sensing technology, it can be used to effectively recognize ancient landslides. Based on the image texture, tone characteristics, two ancient landslides have been identified by using the digital landslide technical method along the eastern margin of the Heqing Basin. The information of these ancient landslides- features, such as the location, extent and elevation was extracted. The calculation results show that the two ancient landslides- scales reached 130 million and 564 million m3, respectively. The lithology, geological structure, stratigraphy covering relation and ancient seismic activity of the study area were analyzed in detail, suggesting that the two ancient landslides were triggered by powerful earthquakes. By comparative analyzing the relative position of the two ancient landslides with the Dali-Lijiang railway and the Heqing railway station, it was concluded that the construction of large linear projects should not only focus on the current regional stability evaluation, but also consider the ancient seismic activity, especially avoiding steep fault along basin edges.

Key words: Heqing Basin, rift basin margin, ancient landslide, remote sensing interpretation

CLC Number: