Challenges and Solutions for Exposure Estimationmddb.apec.org/Documents/2015/FMP/SEM1/15_fmp_sem1_019.pdf · Challenges and Solutions in Developing Exposure ... Philippine Business

___________________________________________________________________________

2015/FMP/SEM1/019 Session: 7

Challenges and Solutions in Developing Exposure Data: Case of Philippines

Submitted by: AIR Worldwide

Seminar on Disaster Risk Finance – APEC Roadmap for Resilient Economies

Bacolod, Philippines29-30 April 2015

1CONFIDENTIAL ©2015 AIR WORLDWIDE

Challenges and Solutions In

Developing Exposure Data:

Case of Philippines

Apoorv Dabral. Ph.D.

Manager, Research and Modelling- AIR Worldwide, Singapore


- Categorization of exposure

- Why AIR develops the exposure dataset

- AIR’s approach to developing exposure databases

- Challenges in developing exposure data for

government assets

Agenda


0

500

1000

1500

2000

2500

3000

3500

4000

20 50 100 250 500 1,000

Me

an L

oss

($

B P

HP

)

Mean Return Period (Years)

Philippines Aggregate Combined Loss Curve

Combined Peril Loss

Earthquake Loss

Tropical Cyclone Loss

NTC Precipitation Loss

NOTE:

Results shown are ground-up annual

aggregate Coverage A losses and include

both government assets and private assets.

Based on 10,000-year stochastic event

catalog

Exposure is the Main Input In a Risk Modeling

Framework

0 0.5 1 1.5

MD

R

Sa (0.3s)

Base Damage Functions

Concrete

Masonry


- Industry Exposure Database (IED)

• Database of the building stock exposed to catastrophe risk are

developed using well established methodology and data gathered from

local agencies and publicly accessible sources

• Database includes building replacement values and other primary

structural characteristics required for catastrophe risk assessment

• Database validated using previous studies conducted in the country

- Government Asset Database

• Database of national government assets which are developed using

data from government agencies and supplemented by publicly

accessible sources

• Replacement values and assets characteristics are required for

catastrophe risk assessment

Exposure For Risk Analysis Can be Divided Into

Two Main Categories


AIR Has IED’s for More Than 90 Countries as It is a

Critical Component in Model Development

- Methodology adopted for development is similar to that adopted for more than 90countries

- Robust IEDs are critical for• Sovereign (and local) level risk assessment and risk transfer

solutions• Developing and validating models• Providing confidence in loss distributions • Estimating losses for real-time events


- IEDs are independently developed using data from

government and private vendors

AIR’s IEDs Are Built from the Ground Up to Provide

a Comprehensive Database of All Properties

- Client exposure data

used to validate, rather

than build, the IED

- AIR creates multiple

views of the IED for each

country


Industry

Exposure

Database

AIR Employs a Robust Approach for Building

Industry Exposure Databases

Rebuild Cost Approach

Replacement

Values

Benchmarking

• National Economic Data

• Insurance PublicationsConstruction

Distribution

Assignment of

construction types to

risks

Disaggregation

High-resolution

spatial mapping of

risks

Spatial Cost

Index

National costs

adjusted for regional

variation

AIR High-Resolution

Attribute Modeling

• Population &

economic censuses

• Housing surveys

Risk Counts

• Occupancy

• Construction & Height

• Floor Area

Risk Attributes

• Costing Manuals

• Construction Indexes

Construction Costs

Data Collection


Primary Data Sources Used to Develop Risk Counts

Variable Vintage Nationwide Region Municipality

Census of Population

and Housing 2010 X

2007 X

2000 X

Annual Survey of

Philippine Business

and Industry

2012 X

2010 X

2000 X


Data Disaggregation Improves Spatial Accuracy of

Exposures

Data typically available at low

geographic resolutionActual risk distributions reflect

human settlement patterns


Various Types of Data Used to Develop

Construction Distributions

GIS Layers

Urbanicity, Hazard

and Location

Census and

Surveys

Height, Wall, Frame

and Year Built

Distributions

Engineering

and Risk

Assessment

Studies

Structural Types

Handbook On Good

Building Design And

Construction In The

Philippines

200720052001

Philippines Wind Zone Philippines Hazard MapPhilippines Seismic Zone

Concrete/Brick/

Stone Wall Type

Distribution from

Census

Wood Wall Type

Distribution from

Census

0-20%

21-40%

41-60%

61-80%

81-100%


Structural Types Included in the Industry Exposure

Database

Non-engineered

& Wood

• Reinforced Concrete

Shear Wall(With MRF)


Shear Wall(Without

MRF)


MRF

• Light Metal

• Steel MRF

• Steel Reinforced

Concrete

• Non-engineered

• Wood Frame

Masonry

• Unreinforced

• Reinforced

• Confined

Concrete Steel


- Spon’s Asia-Pacific Construction Handbook (Davis

Langdon & Seah International)

- Philippines Report, Rider Levett Bucknall

- International Report, Rider Levett Bucknall

- Construction Statistics from Approved Building Permits

(Philippines National Statistics Office)

- Strengthening Natural Hazard Risk in the Philippines

(World Bank)

Replacement Costs Developed From a Variety of

Sources

Wood URM RM Concrete Light Metal Steel

Un

it C

ost

(P

HP

/sq

m) Single Family

Commercial


Commercial Exposures are Concentrated in Urban

Areas


Residential Exposures Reflect Population Centers


National Government Asset

Database


- Data can be incomplete and inaccurate

- Same data from two sources are sometimes contradicting

- Data often not in a format for use with catastrophe models

- Data sometimes come as a hard copy requiring significant

effort to turn them into a usable electronic database

- Delays in response from some agencies

- General difficulty in acquiring certain exposure datasets

- While it was perceived that a lot of data was available and

easily accessible in the Philippines, the data in general was

difficult to obtain, incomplete, and not at the level that can be

directly or easily used for an exposure database

Data Collection Challenges (from a Catastrophe

Modeling Perspective)


Different Local Agencies Provides Different Dataset

Abbreviation Agency

BOC Bureau of Corrections

CAAP Civil Aviation Authority of the Philippines

CHED Commission of Higher Education

DepEd Department of Education

DILG Department of Interior and Local Government

DOH Department of Health

DPWH Department of Public Works and Highways

GSIS Government Service Insurance System

LRTA Light Rail Transit Authority

NPC National Power Corporation

NSO National Statistics Office

PNR Philippine National Railway

PPA Philippine Ports Authority

TransCo National Transmission Corporation


Final Government Asset Database Statistics and

Cost Map

0%

2%

4%

6%

8%

10%

12%

14%

16%

Nation

al C

apita

l…

Cala

ba

razon

Centr

al L

uzo

n

We

ste

rn V

isa

yas

Easte

rn V

isaya

s

Centr

al V

isayas

Nort

hern

Min

dan

ao

Bic

ol

Ilo

cos

Ca

ga

ya

n V

alle

y

Davao

Mim

aro

pa

Soccsksa

rge

n

Za

mb

oa

nga

Pe

nin

su

la

Cara

ga

AR

MM

Cord

illera

…

Pe

rce

nt

To

tal V

alu

e

Government Asset Database


Spatial Distribution of Some Assets: Ports, Rail, Public Universities,

Public Administration Buildings, Airports, Prisons, Bridges, Etc.


- AIR has IEDs for the over 90+ countries it models• All IEDs developed from ground up

• IEDs provide comprehensive view of risks and values

- The IED development process leverages the latest technologies and state of the art techniques• Multiple data sources, including remote-sensed data

• Sophisticated algorithms

- A host of data sources coupled with rigorous methodology result in robust high resolution IEDs

- There are several challenges in building a robust national assets exposure database

- There is a need for Government agencies to collect , process and share the data for a more accurate disaster risk assessment.

Summary