Determination of the Stability of a High and Steep Highway Slope in a Basalt Area Based on Iron Staining Anomalies

Lihui Qian; Shuying Zang; Haoran Man; Li Sun; Xiangwen Wu

doi:10.3390/rs15123021

Remote Sensing (Jun 2023)

Determination of the Stability of a High and Steep Highway Slope in a Basalt Area Based on Iron Staining Anomalies

Lihui Qian,
Shuying Zang,
Haoran Man,
Li Sun,
Xiangwen Wu

Affiliations

Lihui Qian: Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
Shuying Zang: Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
Haoran Man: Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
Li Sun: Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
Xiangwen Wu: Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China

DOI: https://doi.org/10.3390/rs15123021
Journal volume & issue: Vol. 15, no. 12
p. 3021

Abstract

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In recent years, geological disasters have frequently occurred on basarlt highway slopes. Studying the stability of highway slopes in this type of area is of great significance for traffic safety. However, due to the high cost and low efficiency of traditional monitoring and experimental methods for slope engineering, these methods are not conducive to the quick and comprehensive identification of regional slope stability. Due to the high iron content of basalt, iron staining anomalies in the ore prospecting field are reinterpreted from an engineering perspective in this study. Taking the S3K section of a highway in Changbai County, China, as an example, Landsat8 remote sensing (RS) images from 2014, 2016, 2018, 2020, and 2021 are selected, and principal component analysis is used to extract iron staining anomalies in the region. Combined with field investigation and evidence collection, the corresponding rock mass fragmentation is distinguished via iron staining anomalies. Then, according to previous research results, eight indexes including annual rainfall, slope, topographic relief, surface roughness, vegetation index, leaf area index (LAI), root depth of vegetation, and human activity intensity are selected for investigation. The artificial neural network–cellular automata (ANN-CA) model is established, and the rock fragmentation classification data obtained based on iron staining anomalies are used to simulate the area. Next, the calculation formula of slope stability is determined based on the simulation results, and the stability of a high and steep slope in the area is calculated and analyzed. Finally, a comparison with an actual field investigation shows that the effect of the proposed method is good. The research findings reveal that it is feasible to judge the stability of a high and steep slope in a basalt area via the use of iron staining anomalies as an indicator. The findings are tantamount to expanding the application scope of RS in practical engineering.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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