ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 1

Early-warningRisk evaluation

Risk Data Platform

Multi-hazard data

http://www.grid.unep.ch/activities/earlywarning/preview/

Time-series at UNEP/GRID-EuropeAssessmentIntegrated environmental assessment and reporting (IEAR)

Global Environment Outlook (GEO) http://www.grid.unep.ch/geo/

GEO Data portal (> 600 variables) http://geoadata.grid.unep.ch

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 2

GEO country data

http://geodata.grid.unep.ch

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 3

GEO sub-regional data

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 4

GEO regional (continental) data

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 5

Filling data gaps for GEO

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 6

Global Assessment Report (GAR)

ISDR (2009) Global Assessment Report on Disaster Risk Reduction. United Nations, Geneva, Switzerland, http://www.preventionweb.net/english/hyogo/gar/.

Risk=

hazard frequencyx

exposure x

vulnerability

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 7

Risk = exposure x vulnerabilityIncrease in global flood risk 1990-2007

Risk is increasing globally, even at hazard assumed constant

« These increases in risk are being driven by the growing exposure of people and assets, for example through rapid economic and urban growth in cyclone prone coastal areas and earthquake prone cities. Vulnerability decreases as countries develop, but not enough to compensate for the increase in exposure » (ISDR 2009)

« More than two thirds of the mortality and economic losses from internationally reported disasters is associated with meteorological, climatological and hydrological hazard » (ISDR 2009)

Risk factors : economic strength, governance, urbanisation, …

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 8

GAR statistical analysis

Killed by event Socio-economic variables for estimating the vulnerability

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 9

Inter/extrapolation for GAR

Necessary to complete country data series for the statistical analysis of vulnerability to hazards (socio-economic factors explaining the level of losses)=> many gaps in some variables, such as governance indicators

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 10

UNEP work for ESPON Database 2013Comparison between UN and Eurostat data

Population by 3 age classes for years 2000 and 2005

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 11

0

100

200

300

400

500

600

2000 2001 2002 2003 2004 2005 2006

Year

Abso

lute

diff

eren

ce (1

.000

)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Rela

tive

diffe

renc

e (%

)

Absolute difference (1000) Relative difference (%)

Comparing UN and Eurostat dataComparison of population totals for Spain

Absolute difference = UN - EUROSTATRelative difference = (UN - EUROSTAT) / UN

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 12

0

1

2

3

4

5

6

7

0-4

5-9

10-14

15

-19

20-24

25

-29

30-34

35

-39

40-44

45

-49

50-54

55

-59

60-64

65

-69

70-74

75

-79

80-84

85

+

Age Class (years)

Diff

eren

ce: a

bs (1

.000

)

0

0.5

1

1.5

2

2.5

3

3.5

4

Diff

eren

ce: %

Diff. in Male Pop: absolute Diff. in Male Pop: %

Comparing UN and Eurostat data

Belgium 2005

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 13

Downscaling population data by UNEP

Spatial resolution : 2.5’ (≈ 5 km at the equator)Base data: transport network and cities (accessibility index)=> description of the methodology : http://na.unep.net/globalpop/africa/

ESPON Workshop « Managing time-series and estimating missing values » - 6/5/10, Luxembourg H. Dao, UNEP/GRID-Europe 14

Comparing data sources

GPW v3, pop = 484'155 GRUMP, pop = 445'711 LANDSCAN, pop = 506'178

Example of population figures extracted from three data sources for a single flood event (in light blue)

Sources: - GPW and GRUMP http://sedac.ciesin.columbia.edu/gpw/- Landscan http://www.ornl.gov/sci/landscan/