XU Qiang. Understanding and Consideration of Related Issues in Early Identification of Potential Geohazards[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11): 1651-1659. DOI: 10.13203/j.whugis20200043
Citation: XU Qiang. Understanding and Consideration of Related Issues in Early Identification of Potential Geohazards[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11): 1651-1659. DOI: 10.13203/j.whugis20200043

Understanding and Consideration of Related Issues in Early Identification of Potential Geohazards

Funds: 

the National Natural Science Foundation of China 41521002

Sichuan Science and Technology Program 2018SZ0339

Land and Resources Research Program of Sichuan Province KJ-2018-21

More Information
  • Author Bio:

    XU Qiang, PhD, professor, specializes in geological disaster prevention. E-mail: xq@cdut.edu.cn

  • Received Date: February 17, 2020
  • Published Date: November 18, 2020
  •   Objectives  In China, geohazards are wide-ranging. Traditional artificial investigations have found nearly three hundred thousand locations of potential geohazards. However, the recent occurred catastrophic geohazards are not within these determined locations. Widely identification of potential geohazards become one of the most important jobs for geohazard prevention and mitigation.
      Methods  We propose some suggestions to promote early identification for potential geohazards.
      Results  (1) Recently, various remote sensing techniques play an significant role in geohazard identification, but each technique has its limitation to recognize geohazards with different types and characteristics. Only integrated technologies, mutual complementation and verification, can effectively solve the problem. (2) Combination between traditional geological surveys and modern technologies (LiDAR, aerial and semi-aerial geophysical exploration, etc.) can improve the efficiency and accuracy for identification of the most difficult and unstable slops.(3) The deep machine learning is expected to realize the intelligent automatic identification of geohazards. Currently, it shows good performance in new geohazards with significant spectral and texture characteristics, while the accuracy of automatic identification for other types, such as ancient landslides and normal potential geohazards, is still not enough.
      Conclusions  More efforts are in urgent need for further research in related fields.
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