# 2-D Cross-Plot Model Analysis Using Integrated Geophysical Methods for Landslides Assessment
## 5 Conclusions  
The geophysical survey was successfully applied to identify the subsurface characteristics of slope failure. Through the study, weathering and distressing have weakened the soil profiles as velocity, \(<\)1200 m/s, and resistivity, \(<\)1200 \(\Omega\)m, defined as the threshold for failure to occur. The weak zones, suspected to be landslides with sliding, were determined from the 2-D cross plot model. From the results, it reveals that the failure plane occurred at a depth of \(<\)5 m (Quadrant 1, Q1). The factor of failure in this area was suspected of loose material (sand), the existence of boulder, and accumulated saturated zone at the bottom part of the slope, and may trigger the occurrence of the landslide event. Major landslides at local slope failure occur due to water saturation exceeding a critical limit in certain parts of the slope [47]. The continuous infiltration of rainwater increases the pore-air pressure and decreases the matric suction, which compromises the slope stability [44; 45]. The process causes a change in effective stress, which produces the variations in porosity [45]. The infiltration process of near-surface flow increases the pore water pressure as created the stress path to shift horizontally to intersect at the failure envelope. The continuous infiltrated process will trigger the occurrence of slope failure. Other than that, for unsaturated/loose materials, the decreasing of suction force and collapsing of coupled volumetric may be involved in the failure process [48]. The sliding mass can also be estimated based on the integrated values from both results. The identification of the failure plane is vital in identifying the failure zone for all profiles. This survey gave valuable information regarding the slope instability \begin{table}
\begin{tabular}{c c} \hline \hline
**The Volume between Two Regions (Upper-Lower Surface), m\({}^{3}\)** \\ \hline Trapezoidal Rule: & 167,904.81 \\ Simpson’s Rule: & 167,916.12 \\ Simpson’s 3/8 Rule: & 168,070.19 \\ \hline Cut and Fill Volumes & \\ Positive Volume (Cut): & 167,904.81 \\ Negative Volume (Fill): & 0 \\ Net Volume (Cut–Fill): & 167,904.81 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the volume of sliding mass calculation. Figure 14: Volume calculation of mass sliding at landslide Hulu Yam study area: (**a**) 3-D upper surface of landslide area; (**b**) 3-D lower surface of failure plane; (**c**) 3-D illustration of a volume of mass sliding calculation between two different maps (upper–lower). investigation, and it was concluded that it was successfully integrated to evaluate the slope failure for this area. In a nutshell, the cross-plot analysis shows a qualitative method in integrating the different geophysical parameters. The geophysical approaches give comprehensive images to characterize the landslide properties, with validation from geotechnical and hydro-geological parameters providing substantiate interpretation of geophysical results. The integrated method of cross-plot analysis with the 2-D cross-plot model development shows an informative method in characterization and enhances subsurface images. [PERSON] is the first author, and he anchored the review, revisions and approved the article submission. He performed the data analysis, processed experimental data and drafted the manuscript. [PERSON] conceptualized the central research idea and provided the theoretical framework include designed the research and supervised research progress. [PERSON] aided in preliminary interpretation of the results. A.N.S., N.M., N.S., A.T.O. and F.N.R. involve in site survey planning including desk study and data acquisition. [PERSON] improvise and polished the final version of the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript. All authors have read and agreed to the published version of the manuscript. This research was funded by National and Universiti Sains Malaysia (USM), grant number \"203/PFIZIK/6711663\" and \"1001/PFIZIK/8011110\".