# 2-D Cross-Plot Model Analysis Using Integrated Geophysical Methods for Landslides Assessment
## 1 Introduction  
Landslides are characterized by a mass movement of soil and rocks on slopes that occur across the globe due to several factors [1, 2]. Landslides, known as the most destructive types of geohazards, affect human activities, and have serious socioeconomics consequences [3]. Landslides are referred to as'mass-wasting', which occurs due to the down-slope movement of soil and rocks in a large variety of shapes and volume [3, 4]. The various types of landslides are differentiated by the kinds of material involved and the type of movement. [PERSON] (1978) classified the landslides into six different categories, namely falls, topples, slides (rotational and translational), lateral spreads, flows, and composites (acombination of types of movements) [5]. Landslides are widespread in many regions, especially under tropical or subtropical climates with prolonged and intense rainfall [6; 7]. The worldwide distribution of landslides is not uniform, with landslides occurring primarily where the requisite topographic, climatic, and environmental conditions are prevalent [8]. Landslides are often considered a secondary hazard, forming part of the problem of cascading hazards [9], as they are triggered by catastrophic events, such as storms, floods, volcanic eruptions, and earthquakes [10]. Landslides have been found to have size-frequency distributions that follow a power function for both area and volume of large events [11; 12; 13; 14; 15]. The above-referenced landslide studies have been conducted in different locations and are associated with different triggering mechanisms [16]. This phenomenon may occur in natural slopes in a variety of materials, including residual and colluvial soils [17]. Although the impact of this geohazard is inevitable, it can be significantly reduced by increasing the capacity to assess and predict the risks using different mitigation methods [3]. In past decades, numerous modeling methods have been designed to assess slope stability, predict slope response to various triggers and evaluate slope deformation [3]. Investigation of subsurface landslide features are necessary to provide preliminary input for forwarding modeling and subsequent predictions of potential failure events [18; 19]. However, such models still require access to detailed information of geological, mechanical, and hydrological properties, as well as conditions surrounding boundaries. Therefore, integrated multidisciplinary approaches are essential to being implemented in landslide investigations to improve the reliability of the deterministic model. The increase in geophysical methods has become more widespread. The comprehensive result with proper numerical modeling helps to develop the predictive model, especially for complex landslides event. Due to complexity, classic geotechnical problem for stability assessment give verifiable information on the mechanical and hydraulic characteristics of the landslides, but in a discrete point of the subsurface [20]. Satellite and airborne methods provide useful information regarding the surface characteristics of the slope, such as geomorphological features, areas of extension of the landslide body, superficial displacement, and velocity [21; 22]. However, all of this information has not included subsurface features, which plays a vital role in landslide characteristics. In-situ geophysical methods, such as resistivity and seismic refraction, are capable of evaluating physical parameters, directly or indirectly, such as lithology of the subsurface, hydrology, and geotechnical characteristics [23]. The 2-D resistivity is widely used in evaluating slope deformations and in predicting the surface movements [24; 25; 26; 27]. The information obtained is useful to define the geological setting of the investigated subsoil, reconstruct the landslide body, and volume of the slide material [23; 28]. Seismic refraction has been proven in detecting the landslide extent and material velocity of the subsurface [29; 30].