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Climate change and Urban Vulnerability in Africa. Assessing vulnerability of urban systems , population and goods in relation to natural and man-made disasters in Africa. “Training on the job” Course on Hazards, Risk and (Bayesian) multi-risk assessement

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Climate change and urban vulnerability in africa

Climate change and Urban Vulnerability in Africa

Assessingvulnerability of urbansystems, population and goods in relation to natural and man-made disasters in Africa

“Training on the job” Course on Hazards, Risk and

(Bayesian) multi-risk assessement

Napoli, 24.10.2011 – 11.11.2011

Module 3.5: Desertification, Case Studies

Iavazzo, Topa, Terracciano

04/11/2011



DESERTIFICATION

In africa

Source: UN - United Nations


DESERTIFICATION

In WEStafrica

St. Louis

Ouagadougou

Douala

Source: UN - United Nations


DESERTIFICATION

In EAST africa

Addis Ababa

Dar EsSalaam

Source: UN - United Nations


MEDALUS METHODOLOGY

ESAs model was developed in Mediterranean habitat. The application of this methodology in west Africa sub-Saharan areas needs a readjustment for some parameters to adapt the classes and weigh of indices to different habitat conditions.

  • The readjustment of vegetation index was made starting from classification of the dominant natural vegetation and agricultural crops in sub-Saharan west Africa, and subsequently weighing indices in relation to the four sub-indices.

  • Mediterranenan area Sub-Saharan west Africa

ClassVegetation

1 MixedMediterranean macchia/evergreen forest

2 Mediterranean macchia

3 Permanentgrassland

4 Annualgrassland

5 Deciduousforest

6 Pine forest

7 Evergreen forestexcept pine forest

8 Evergreen perennialagriculturalcrops

9 Deciduousperennialagriculturalcrops

10 Annualwinteragriculturalcrops

11 Annualsummeragriculturalcrops

12 Bare land

ClassVegetation

1 Tropicalrainforest

2 Woodlandsavanna

3 Grasslandsavanna

4 Steppe

5 Semidesert

6 Annualagricolturalcrops

7 Perennialagricolturalcrops

8 Bare areas


MEDALUS METHODOLOGY

Fire Risk

Erosion Protection

Drought Resistance

Plant Cover

VQI

Vegetation Quality Index

Mean Annual Rainfall

Aspect

Aridity Index

CQI

Climate Quality Index

ESAI

Soil Texture

Rock Fragment

Slope Gradient

Soil Depth

Parent Material

Drainage

SQI

Soil Quality Index

MQI

Management Quality Index

Land Use Type

Land Use Intensity

Policy

(Kosmas et al., 1999)


Case study burkina faso
CASE STUDY: BURKINA FASO

STUDY AREA:

OUAGADOUGOU REGION

100 km

50 km


VQI

REFERENCE DATA

LAND COVER MAP

FAO, 2009


VQI

VEGETATION QUALITY INDEX

FIRE RISK

100 km


VQI

VEGETATION QUALITY INDEX

EROSION PROTECTION

100 km


VQI

VEGETATION QUALITY INDEX

DROUGHT RESISTANCE

100 km


VQI

VEGETATION QUALITY INDEX

PLANT COVER

100 km


VQI

VEGETATION QUALITY INDEX

Urban area

Non affected

Potential

Fragile 1

Fragile 2

Fragile 3

Critical 1

Critical 2

Critical 3

100 km


CQI

Climate QUALITY INDEX

AI = P/ETP = 0.5

P: meanannualrainfall

ETP: potential evapotranspiration (calculated by method of Thornthwaite)

100 km


SQI

REFERENCE DATA

PEDOLOGICAL MAP

PEDOLOGICAL MAP

PEDOLOGICAL MAP

O.R.S.T.O.M., 1973 – 1/500000

I.R.A.T., 1985 – 1/1000000

O.R.S.T.O.M., 1976 – 1/500000

GEOLOGICAL MAP

DOMINANT SOILS

D.G.M., 1976 – 1/1000000

FAO, 2001


SQI

SOIL QUALITY INDEX

TEXTURE

100 km


SQI

SOIL QUALITY INDEX

ROCK

FRAGMENTS

100 km


SQI

SOIL QUALITY INDEX

SLOPE

100 km


SQI

SOIL QUALITY INDEX

SOIL

DEPTH

100 km


SQI

SOIL QUALITY INDEX

PARENT

MATERIAL

100 km


SQI

SOIL QUALITY INDEX

DRAINAGE

100 km


SQI

SOIL QUALITY INDEX

Urban area

Non affected

Potential

Fragile 1

Fragile 2

Fragile 3

Critical 1

Critical 2

Critical 3

100 km


MQI

MANAGEMENT QUALITY INDEX

LAND USE

CROPLAND AREAS

100 km


MQI

MANAGEMENT QUALITY INDEX

LAND USE

PASTURE AREAS

100 km


MQI

MANAGEMENT QUALITY INDEX

POLICY

100 km


MQI

MANAGEMENT QUALITY INDEX

Urban area

Non affected

Potential

Fragile 1

Fragile 2

Fragile 3

Critical 1

Critical 2

Critical 3

100 km


MEDALUS METHODOLOGY

Urban area

Non affected

Potential

Fragile 1

Fragile 2

Fragile 3

Critical 1

Critical 2

Critical 3

100 km


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