# Integration of Geoscience Information for Disaster Resilience in Kuala Lumpur, Malaysia
## 1 Introduction  
The concept of resilience refers to the ability of a system to \"bounce back\" or reorganise and return to its original condition after encountering a sudden shock [1; 2; 3]. A widely accepted definition for disaster resilience is \"the ability of a system, community or society exposed to hazards to resist, absorb, accommodate and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions\" [4]. Resilience is closely linked to disaster risk response and capacity to recover [5; 6]. Actions on disaster prevention, mitigation, preparedness, response and recovery collectively contribute to building resilience. This is important for cities where climate change is expected to increase impacts on communities and infrastructure and disrupt essential amenities [7]. Cities are complex and interdependent systems, requiring effective mechanisms to cope with climate hazards as the expected impacts are greater due to high population density, extensive infrastructure and limited resources [5; 8; 9]. The global agenda to \"make cities inclusive, safe, resilient and sustainable\" is embedded in the national policies of many countries [10]. Initiatives for strengthening disaster resilience in cities include reducing the vulnerability and exposure of communities, their assets and surrounding areas to hazards [3; 11]. Risk reduction to climate hazards including the forecasting of disruptiveevents in cities is increasingly important to reduce losses [8; 12; 13; 14; 15]. Building city resilience requires a holistic approach that can be measured by four main aspects comprising economy, organisation, environment and society [1]. With respect to the physical environment, the potential of geoscience information, which includes data and knowledge about the Earth and its systems, is becoming increasingly recognised [16; 17; 18; 19; 20]. Local-level geoscience information can be obtained from multiple agencies and site investigations conducted for ongoing development projects, which are an added source for cities with limited records. Very often, such information has to be digitised and geo-referenced into geospatial data before being used in geographic information system (GIS) software. The incorporation of geoscience perspectives using GIS is common in the development planning process, and it allows stakeholders to take into account engineering geology conditions and susceptibility to geohazards [18; 21]. Land evaluation through land-use suitability modelling is a common practice prior to development [22; 23; 24; 25]. The process involves a scientific method for assessing ground conditions using geoscience information, which is critical to achieving an optimum utilisation of available land resources by recognising the potential and limitation of the area for a defined use [26; 27; 28]. Susceptibility modelling draws on local geoscience information to delineate areas with potential for geohazards to occur based on local geological, geomorphological and other physical conditions, which are mapped through field observation or remote sensing. Rainfall is not often used as a parameter for susceptibility modelling for landslides [29]. However, it is commonly used as a parameter for floods [30]. In this study, rainfall is considered as a trigger factor, and it is not used as a parameter for susceptibility modelling [18; 29; 31; 32]. While the zoning of an area using suitability modelling is not new [22; 23; 24; 25], many studies do not use information on hazard susceptibility, and if they do so, the focus is on a single geohazard such as seismicity, flooding and groundwater pollution [34; 35; 36; 37]. The combination of both engineering geology conditions and susceptibility to multiple geohazards facilitates risk reduction and helps in achieving a better understanding of the current challenges in cities for building resilience to disasters influenced by climate change [38; 39; 37].