# Integration of Geoscience Information for Disaster Resilience in Kuala Lumpur, Malaysia
## 2 Materials and Methods
### Assessment of Geoscience Information  
The GIS software ArcGIS 10.5 was used to conduct spatial data acquisition, processing and visualisation due to its accessibility and prevalent use across the field. The data analysis was completed in MS Excel and ArcGIS before reinterpretation was carried out and presented as various maps. The urban development suitability analysis was completed using a computer-assisted overlay approach to evaluate the selected factors in raster format [22]. It enables the combination and transformation of spatial input data into a resultant decision. Subsequently, the overlay technique involves applying a common measurement scale of values to the input to indicate the influence of the factors towards the urban development suitability prior to zonation of the prevalent suitability classes [26]. The overview of the general workflow is shown in Figure 2 and described as follows. * Assessment of engineering geology condition  
The engineering properties acquired from previous research and borehole logs of past site investigation reports were digitised and organised in an inventory for analysis to determine the engineering characteristics of each formation. The engineering ground classification (EGC) map was established based on expert judgement using five criteria. A similar expert judgement overlay method has been used to assess engineering geological for development suitability [28; 53]. The five criteria are the ground stability, aggregate potential, engineered fill, foundation and excavatability of the ground materials in the study area. Values of 1, 2, 3 and 4 are given to the engineering performance for groundwork indicating ranks of very poor, poor, moderate and good, respectively. The classification of the EGC map into five classes (namely, Class I--Excellent, Class II--Good, Class III--Fair, Class IV--Poor and Class V--Unpredictable) is based on the scoring matrix, where the suitability increases with score (figure in Section 3.1). Consideration of the external factors on ground constraint contributes to the evaluation of the material and the ranking process. This included the surrounding geomorphology and past mining activities, which had modified the condition of the surfi  
Figure 2: General workflow commencing with analysis of geoscience and related information and GIS modelling, followed by spatial integration, and zonation of contiguous areas. * Assessment of geohazard susceptibility Susceptibility assessment of landslides was conducted using ArcGIS to process the landslide-controlling factors derived from the input base maps. The landslide susceptibility modelling in this study adopted a bivariate statistical approach which involves the selection of landslide-controlling factors and the respective classes of a feature to be compared with a reliable past landslide occurrences map [54; 55]. Seven landslide-controlling factors were selected using expert judgement which included slope gradient, surface material, distance to lineament, distance to road, elevation, roughness and topographic position index (TPI). The surface geology is determined by referring to the geological map, aerial photographs, topographic map and field mapping. DTM is used to derive most of the landslide conditioning factors using geoprocessing in ArcGIS 10.5. The slope gradient factor map shows the degree of inclination of the slope, while the elevation factor map represents the height above sea level. Surface roughness indicates the degree of variation of surface elevation derived from the average standard deviation calculated from a 10 m by 10 m moving window. The distance to lineament shows the distance to fault and lineament in metres, which was interpreted from DTM and aerial photographs. The distance to road factor map was produced from the DBKL road map, which shows the distance to roads in metres. TPI was calculated as the difference between the elevation at a point, and the mean elevation within a 250 m radius circular window actually indicates the relative slope position [18].