**2. Materials and methods**

#### **2.1. Study area**

**1. Introduction**

150 Multi-purposeful Application of Geospatial Data

In the modern geoscientific time frame, remote-sensing and GIS techniques have been tremendously used for obtaining reliable information from satellite imageries at macro- to microscale investigations. Studies of linear geologic features (lineaments) from macro- to microlevel have been increasing rapidly. Lineament extraction from satellite imagery either by visual or automatic interpretation has been a long interest of geologists, where the character and extent of these features have been realized and lineament analysis of remotely sensed data using automatic extraction, is a valuable source of information for studying the structural settings of an area. The term "Lineament" has been widely used in the field of geology, and literally, it expresses by different scientists through their research work in different ways. The term lineament was first described as significant line of landscape within the basement rocks [1]. The lineament defines as linear features in a landscape identified on satellite images and aerial photographs, most likely have a geological origin. Generally, lineaments are underlying by structural zone, fractured zone, a series of fault or fold aligned hills zone of localized weathering and zone of increased permeability, porosity, seismicity, landslide formation [2], active erosion, and karst development [3]. Lineament extraction and analysis have been studied by different distinguished scientists [4–11]. Besides these, lineament analysis has been used extensively for geologic interpretation, particularly from the 1930s with the advent of photogeology [12]; because satellite data provide quick and useful baseline information on the parameters controlling the occurrence and movement of groundwater like geology, lithology/structural, geomorphology, soils, land use/land cover, and lineaments. With the advancement of remote sensing techniques, identifications of lineaments for earthquake have become a rapid and cost-effective procedure. One of the main features of geological interpretation of satellite imagery has been the recognition of lineaments varying in length from a few kilometers to hundreds of kilometers [13]. The lineament is a mappable linear or curvilinear feature of a surface whose parts align in a straight or slightly curving relationship [14], which differs from the pattern of adjacent features and reflects some subsurface phenomena [15]. Moreover, lineament mapping and analyses have been gaining popularity with the increasing availability of satellite images [16]. Since satellite images are obtained from varying wavelength intervals of the electromagnetic spectrum, they are considered to be a better tool to discriminate the lineaments and to produce better information rather than conventional aerial photographs. Recently, two earthquakes were badly hit in the geologically complex regions, that is, Gorkha region of Nepal (7.8 Mw) on 25 April 2015 and Imphal region of Manipur, Eastern India (6.7 Mw) on 4 January 2016, respectively. By observing the severity of the two

earthquakes, these two study areas have been considered for our present research.

The main objective of this study is to extract lineament features through automatic approaches by using Landsat 8 Satellite imageries, which further used to calculate lineament length and directional change measurement through rose diagram and to know the pre-earthquake anomaly through lineament changes observation in the presence and the absence of an earthquake. Therefore, vector overlay technique was performed on lineament temporal data considered for the two impending earthquakes (major and strong). The earthquake occurrence signals were noticed in individual case by interpreting five satellite scenes of Landsat 8 OLI sensors.

The study area for each case covers 370 km2 in size of each single satellite scene. The first study case is Nepal, which lies toward the southern limit of the diffuse collisional boundary where the Indian plates under thrusts the Eurasian plate, occupying the central sector of the Himalayan arc [17]. In Gorkha of Nepal case, the northern part of the satellite scene is covered by parts of China. Gorkha earthquake in Nepal (7.8 Mw) is a shallow earthquake occurred on 25 April 2015 (epicenter position: 28.147° N and 84.708° E) at a depth of 15 km created massive destruction. This earthquake was caused by a sudden thrust or release of built up stress along the major fault line [18].

On the other hand, the second case study is Imphal earthquake (6.7 Mw), which occurred in northeast regions of India in the state of Manipur. This earthquake was struck on 4 January 2016 at a depth of approximate 55.0 km (measured by United States Geological Survey, USGS) and about 15 km west of the fault coinciding with the edge of the Imphal valley. The epicenter (position: 24.804° N and 93.651° E) was in Manipur's Tamenglong district, and bordering area with Myanmar is in the right section of that corresponding image. According to Gahalaut V.K., and Kundu B., this earthquake was occurred on steep plane due to typical intraslab type movement within Indian plate, which predominantly moves toward north, and developed crack which was N-S oriented along with oblique motion (1–2 cm), and it was observed during field visit [19]. The regional plate boundary in eastern India-the Indo-Burmese Arc is oriented approximately in south-southwest-north-northeast direction (see [20]). The location of study areas is shown in **Figure 1**.

**Figure 1.** Location of study area.
