Task 3.2 – (Land Use)/Spatial Indicators of Vulnerable communities

Friday 27th April 2012

Patrik Karlsson Nyed GIS analyst, KU

Case cities

St Louis Dar Es Salaam

Main objectives

• Reveal spatial indicators which are relating to the vulnerability of communities.

• Map vulnerable communities and high risk areas.

Indicators

• What are they?Quantitative entities that provide information of wider significance than is actually measured

TIME-EFFICIENT decision-making and planning (instead of qualitative methods)

Comparisons across SPACE and over TIME

# Pinpoint most vulnerable communities – Space# Development between years – Time

• Why do we need them?

Task 3.2 – Workflow indicatorsInventory

First selectionHazard-type relevant

Second selectionSite-specific

Check data availability

Geodata processingAnalysis/Validation

Map making

Sharing with stakeholders

Expert surveyLiterature study

Local expert surveyRanking/Weighting?

African partnersOther sources (e.g. WWW)OOA (Digitizing/Segmentation)

Field surveysPurchase Decide MMU

Reduction indicatorsVulnerability Index

1

2a

2b

3

Workflow – step 1

• Expert survey/Literature study Long list of potential indicators

Less long list of potential indicators

• Exclude indicators less relevant to hazard type

InventoryFirst selection

Hazard-type relevant

Workflow – step 2a Second selectionSite-specific

• Local expert survey

Less long list of potential indicators

Short list of potential indicators

Municipality officials and University staff Community representatives

Workflow – step 2b Check data availability

• African partners

• Other sources (e.g. WWW)

• OOA (Digitizing/Segmentation)

• Field surveys

• Purchase

Task 2.2 – UMT (Urban Morphology Types)

Task 2.1 – Construction material buildings

Task 1.3 – DEM (Digital Elevation Models)

Workflow – step 3

• Geodata processing – Quantification of indicators using GIS

Geodata processingAnalysis/Validation

Map making

Short list of potential indicators

Mobility/Accessibility-Network Analysis

Proportion green areas

• Analysis/Validation – Stepwise regression analysis using vulnerability data from national census as validation

A few indicators (explaining most of the variation in vulnerability)

• Map making (overlay)

Create Vulnerability Index (using the final set of indicators)

Vulnerability of communities High risk areas

Spatial Indicator

• Preconditions (some necessary, others desired)

- Quantifiable in space

- Express variation

- Comprehensible

- Valid (measure what it is intended to)

- Achievable?

‘Short-cut proxy’

Mobility/Accessibility-Network Analysis

Proportion paved roads

- Field survey (doorway threshold) Official records of previous flood areas

Previous Hazard Experience

Sex ratio

Pop. size ???

Maps – Comparison across SPACERepeatable – Comparison over TIME

Constraints: Data accessBudgetKnow-how Future accessibility

Thanks for the attention