Early landslide mapping with slope units division and multi-scale object-based image analysis — A case study in the Xianshui River basin of Sichuan, China

Hui, Gao; He, Longzhuang; He, Zhengwei; Bai, Wenqian

doi:10.1007/s11629-022-7333-6

Cited by 6 publications

(2 citation statements)

References 45 publications

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“…Therefore, since interdisciplinary approach is recommended for landslide monitoring (Wunderlich 2006, Margottini, Bobrowsky et al 2017, Gao, He et al 2022, Saraskanrood and Piroozi 2022, and no research in documented globally on the proposed approach, the aim of this research is to Integrate lineament and strain analysis to assess landslide vulnerability along Taiping to Ipoh Highway, Malaysia by determining both the strain deformation type and pattern of rocks and the lineament intersection density of the study area and then correlating the points with both high strain deformation and high lineament intersection density as the most vulnerable zones to landslides occurrences.…”

Section: Introductionmentioning

confidence: 99%

Integration of Lineament and Strain Analysis to Assess Landslide Vulnerability Along Taiping to Ipoh Highway, Malaysia

Yamusa

Ismail²

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The overall tectonics of a terrain and landslide occurrences can be controlled using lineament analysis. In addition, understanding the deformational characteristics of the rocks in question cannot be overemphasized. The current work was carried out along Taiping to Ipoh stretch of the North – South PLUS Highway Malaysia and its environs to assess landslide vulnerability via lineaments and strain deformation analysis. Approximately 73 km stretch of the road was analysed. Classification of about 197 lineaments was done from very high to very low density classes applying class break procedures to signify their respective risk zones. Fry strain analysis method was then integrated by digitizing the centre of the grains from which reference lines angles and axial ratios of 16 photomicrographs of various lithologies obtained from field investigations were used to understand their strain deformational pattern. The lineament intersection point map shows its concordance with the strain ellipsoid. The major trend of the lineaments and fry strain ellipsoid were both found to be trending NE–SW. Congruity between the lineaments intersection density and the flattened higher degree of strain signified a risk prone zone and probable landslide trigger along the highway.

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Section: Introductionmentioning

confidence: 99%

Integration of Lineament and Strain Analysis to Assess Landslide Vulnerability Along Taiping to Ipoh Highway, Malaysia

Yamusa

Ismail²

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…As technology evolves, new methodologies for landslide recognition have been developed, including optical remote sensing imaging, InSAR technology, and airborne LiDAR. The paper by Gao et al (2022) provides new insights concerning an object-oriented image analysis method based on slope unit division and multi-scale segmentation to obtain accurate location and boundary extraction of early landslides. The results of applying this classification method in the Xianshui River Basin of Sichuan, China, indicated that landslide-susceptible areas can be defined through the rapid extraction of slope units.…”

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confidence: 99%

Disaster risk reduction in mountain areas: a research overview

2022

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This paper gives an account of the diverse dimensions of research on disaster risk reduction in mountain regions derived from an open call of the Journal of Mountain Science that brought 21 contributions. This special issue includes topics as diverse as landslide dynamics and mechanisms, landslide inventories and landslide susceptibility models, insights to landslide hazards and disasters and mitigation measures, disaster response and disaster risk reduction. The overall structure of the paper takes the form of three sections. The first part begins by laying out the significance of disaster risk reduction in mountain areas, whereas the second one looks at the research insights on disaster risk reduction in mountains provided by the contributions comprised in the special volume. The final section identifies areas for further research.

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A comparison between Pixel-based deep learning and Object-based image analysis (OBIA) for individual detection of cabbage plants based on UAV Visible-light images

Yang

Lin

et al. 2023

Computers and Electronics in Agriculture

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Early landslide mapping with slope units division and multi-scale object-based image analysis — A case study in the Xianshui River basin of Sichuan, China

Cited by 6 publications

References 45 publications

Integration of Lineament and Strain Analysis to Assess Landslide Vulnerability Along Taiping to Ipoh Highway, Malaysia

Integration of Lineament and Strain Analysis to Assess Landslide Vulnerability Along Taiping to Ipoh Highway, Malaysia

Disaster risk reduction in mountain areas: a research overview

A comparison between Pixel-based deep learning and Object-based image analysis (OBIA) for individual detection of cabbage plants based on UAV Visible-light images

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