Development of the Global Exposure Database (GED)
-
Upload
global-earthquake-model-foundation -
Category
Presentations & Public Speaking
-
view
133 -
download
3
description
Transcript of Development of the Global Exposure Database (GED)
Development of the Global Exposure Database (GED)
Kishor Jaiswal, Synergetics Inc./USGS Golden COwith contributions from: P. Gamba, University of Pavia, Italy, C. Huyck and Z. Hu, ImageCat Inc.S. Vinay, R. Chen, and M. Becker, CIESINO. Odhiambo, G. Mboup UN-Habitat, Nairobi KenyaS. Ferri, E. Goldoni, D. Ehrlich JRC ItalyP. Henshaw, GEM FoundationD. Wald, USGS Golden CO
10NCEE, Anchorage Alaska
July 23rd, 2014
@GEMwrld #10NCEE
Objectives
• The aim of GED4GEM is to build a comprehensive, multi-scale andstatistically accurate database of population and buildings, to asses thephysical and economic exposure of a given area to earthquakes.
• The database had therefore to be:– state-of-the-art, i.e. including all existing (and freely available) data sets;– global, i.e. valid all for each country;– consistent, i.e. capable in providing statistical and spatial consistency (in
a region or a country);– easily upgradable through ad-hoc scripts.
• Including more information than just the building structural data, the GlobalExposure Database (or GED for short) could eventually be useful inmulti-hazard applications, e.g., earthquakes, floods, landslides,hurricanes and other disasters.
Consortium
Partners• University of Pavia (UNIPV)• The Center for International Earth Science Information Network (CIESIN)• Global Urban Observatory (GUO) of UN-HABITAT• ImageCat Inc.• The Joint Research Centre of the European Union (JRC)
Advisory Partners• US Geological Survey (USGS)• EUCENTRE• Geoscience Australia (GA)
Source Taxonomy Grid/Vector
Statistics Validation
Level 0 GPW, PAGER,GRUMP, UN-HABITAT, NERA
PAGERGEM
30” Country Internal:consistency with PAGER
Level 1 Sub-country db(Census, DHS, MICS, HAZUS, regional programmes)
GEMHAZUS
30” Region (Admin 1 & Admin 2)
Internal: test site informationat aggregated levels
Internal: quality of input data
Level 2 National/regional/local database(s)
GEM 30” Ad hoc
Level 3 Ground surveyBuilding database(s)
GEM vector Single building
External:regional and selected users
Global Exposure Database: levels
GED Level 0: data from PAGER
IMPROVED Level 0
• Additional information available from UN-Habitat to improve GED has been processed and sample results checked before ingestion into GED.
Census records
• Sample design– Systematic sample of every twentieth household.
• Sampling unit: Households• Sample fraction: 5%• Sample size (person records): 1,407,547• Sample weights: Self-weighting.
Expansion factor = 20.
Demographics and Health Survey records
• The Demographics and Health Survey (DHS) sample is designed torepresent each of the country’s administrative regions. In each region, astratified sample design was employed. Primary sampling units (PSUs) areselected with probability proportional to the estimated number of householdsfrom the Census.
Level 1: for the first time sub-national information
struct_code struct_ratio
W+WLI//R99 0.026
CR+CT99//RC+RC99 0.001
MUR+STRUB+MOM//R99 0.370
MUR+CL99//R99 0.043
MUR+CL99//RO 0.558
MUR+ADO//R99 0.002
struct_code struct_ratio
W+WLI//R99 0.020
CR+CT99//RC+RC99 0.00
MUR+STRUB+MOM//R99 0.375
MUR+CL99//R99 0.040
MUR+CL99//RO 0.558
Level 1: less coverage
• Check for region matching included (issues with GADM versus the population model versus national databases)
• GADM v.2 compliant
Level 2 data: room for detailed databases
struct_id struct_code struct_ratio
1 W+WLI//R99 0.026
9CR+CT99//RC+RC
99 0.001
12MUR+STRUB+MO
M//R99 0.370
19 MUR+CL99//R99 0.043
31 MUR+CL99//RO 0.558
102 MUR+ADO//R99 0.002
103MATO//RME+RM
E99 0.000
Stone 4.3%Cane/palm 0.7%Adobe / "tapial" 37.0%"Tabique, quinche" 0.1%Wood 1.9%Bricks 55.8%OTHER 0.2%
Level 2: aggregated data from existing GIS files
Guadeloupe: density of buildings + dwelling fractions from Level 0 (JRC + UNIPV)
Replacement cost data sources
• Published construction cost guides– Common in countries like
Europe, North America, Australia, et
– Available for a selection of countries in Africa, South America, Asia
• Purpose commissioned reports from local quantity surveyors
Example: Malaysia
Procedure
• It is proposed that the global range of GDPpc is subdivided into five bins and an index country (together with a full range of factors) is provided for each bin.
• Then, a factor for replacement rate is computed.
Current Replacement Cost Coverage
• A few countries with detailed information by expert opinion• Rest of the world (almost) with “default” values
A few examples of data in GED
A few question we can answer with GED 1.0
Level 0 (national) questions• Estimate of the total residential exposure of Russia
– X billions USD (computed using level 0 dwelling fractions from PAGER, average floor per capita, default replacement cost)
Level 1 (subnational) questions• Estimate of total wooden buildings that are present in the Saravan region of
Laos– Y (computed using level 1 dwelling fractions from 2006 MICS survey, the
average number of people per dwelling, default numbers for the numbers of dwelling per building)
Level 2 (local) questions• Estimate of total masonry buildings in a radius of 3 km around the center of
Brisbane – Lat. 153.03, Lon. -27.44, – or how much would cost to rebuild 60% of them?– Z and XX billion AUS (computed using level 2 data from NEXIS)
GEM Data and Models on the Platform
Thank you !
Except where otherwise noted, this work is licensed under: creativecommons.org/licenses/by-nc-nd/4.0/
Please attribute to the GEM Foundation with a link to -www.globalearthquakemodel.org
Questions?
• Just to help understanding the answers …