The Philippine archipalego is tectonically complex and seismically hazardous, yet few seismic hazard assessments have provided national coverage. This paper presents an updated probabilistic seismic hazard analysis for the nation. Active shallow crustal seismicity is modeled by faults and gridded point sources accounting for spatially variable occurrence rates. Subduction interfaces are modelled with faults of complex geometry. Intraslab seismicity is modeled by ruptures filling the slab volume. Source geometries and earthquake rates are derived from seismicity catalogs, geophysical datasets, and historic-to-paleoseismic constraints on fault slip rates. The ground motion characterization includes models designed for global use, with partial constraint by residual analysis. Shallow crustal faulting near metropolitan Manila, Davao, and Cebu dominates shaking hazard. In a few places, peak ground acceleration with 10% probability of exceedance in 50 years on rock reaches 1.0 g. The results of this study may assist in calculating the design base shear in the National Structural Code of the Philippines.

The Greater Metro Manila Area is one of the world's megacities and is home to about 12 million people. It is located in a region at risk from earthquakes, volcanic eruptions, tropical cyclones, riverine flooding, landslides and other natural hazards. Major flooding affected the Greater Metro Manila Area in September 2009 following the passage of Typhoon Ketsana (known locally as Typhoon Ondoy). Following this event, the Australian Aid Program supported Geoscience Australia to undertake a capacity building project with its partner agencies in the Government of the Philippines. The output of this project has been a series of risk information products developed by agencies in the Collective Strengthening of Community Awareness for Natural Disasters (CSCAND) group. These products quantify the expected physical damage and economic loss to buildings caused by earthquakes, tropical cyclone severe wind and riverine flooding across the Greater Metro Manila Area. Spatial data is a key input to the development of hazard models and information on exposure, or the 'elements at risk'. The development of a spatially enabled exposure database was a crucial element in the construction of risk information products for the Greater Metro Manila Area. The database provides one central repository to host consistent information about the location, size, type, age, residential population and structural characteristics of buildings within the area of interest. Unique spatial analysis techniques were employed to quantify and record important aspects of the built environment, for inclusion in the database. The process of exposure data development within the Greater Metro Manila Area, including a new application developed by Geoscience Australia for estimating the geometric characteristics of buildings from high resolution elevation data and multi-spectral imagery, will be presented.

The Philippine Institute of Volcanology and Seismology (PHIVOLCS) and Geoscience Australia (GA) have developed a long-term partnership in order to better understand and reduce the risks associated with earthquake hazards in the Philippines. The Project discussed herein was supported by the Australian Agency for International Development (AusAID). Specifically, this partnership was designed to enhance the exposure and damage estimation capabilities of the Rapid Earthquake Damage Assessment System (REDAS), which has been designed and built by PHIVOLCS. Prior to the commencement of this Project, REDAS had the capability to model a range of potential earthquake hazards including ground shaking, tsunami inundation, liquefaction and landslides, as well as providing information about elements at risk (e.g., schools, bridges, etc.) from the aforementioned hazards. The current Project enhances the exposure and vulnerability modules in REDAS and enable it to estimate building damage and fatalities resulting from scenario earthquakes, and to provide critical information to first-responders on the likely impacts of an earthquake in near real-time. To investigate this emergent capability within PHIVOLCS, we have chosen the pilot community of Iloilo City, Western Visayas. A large component of this project has been the compilation of datasets to develop building exposure models, and subsequently, developing methodologies to make these datasets useful for natural hazard impact assessments. Collection of the exposure data was undertaken at two levels: national and local. The national exposure dataset was gathered from the Philippines National Statistics Office (NSO) and comprises basic information on wall type, roof type, and floor area for residential buildings. The NSO census dataset also comprises crucial information on the population distribution throughout the Philippines. The local exposure dataset gathered from the Iloilo City Assessors Office includes slightly more detailed information on the building type for all buildings (residential, commercial, government, etc.) and appears to provide more accurate information on the floor area. However, the local Iloilo City dataset does not provide any information on the number of people that occupy these buildings. Consequently, in order for the local data to be useful for our purposes, we must merge the population data from the NSO with the local Assessors Office data. Subsequent validation if the Iloilo City exposure database has been conducted through targeted foot-based building inventory surveys and has allowed us to generate statistical models to approximate the distribution of engineering structural systems aggregated at a barangay level using simple wall and roof-type information from the NSO census data. We present a comparison of the national and local exposure data and discuss how information assembled from the Iloilo City pilot study - and future study areas where detailed exposure assessments are conducted - could be extended to describe the distribution of building stock in other regions of the Philippines using only the first-order national-scale NSO data. We present exposure information gathered for Iloilo City at barangay level in a format that can be readily imported to REDAS for estimating earthquake impact.