POVERTY and FOOD INSECURITY MAPPING

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POVERTY and FOOD INSECURITY MAPPING
CSI/CGIAR
Project Funding Government of Norway
(GCP/INT/761/NOR)
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The overall objectives of the project

• To enhance scientific understanding of poverty
  and its relationship to food insecurity and
  vulnerability by placing these issues in a
  spatial context
• Making linkages between the environment and
  poverty and food insecurity

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1. TO APPLY GIS AND SPATIAL ANALYSIS TECHNIQUES
TO FOOD INSECURITY AND POVERTY REDUCTION
The main outputs of the Project
2. TO CARRY OUT CASE STUDIES IN EIGHT COUNTRIES
3. TO GATHER AND DISSEMINATE THE BEST SCIENCE ON
THE SUBJECT
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CIAT/CG Centres part in the Project

• COUNTRY CASE STUDIES
• CIAT ECUADOR
• CIMMYT MEXICO
• IITA NIGERIA
• ICARDA SYRIA
• IFPRI MALAWI
• ILRI KENYA
• IRRI BANGLADESH
• IWMI SRI LANKA

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FAOs part in the Project

• Development of the FIVIMS Global GIS Database
  (FGGD)
• The main Purpose of FGGD is to create a global
  environmental database and a modelling/analysis
  infrastructure for assisting in the
  implementation and monitoring WFS plans of action

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UNEP-GRID-Arendals part in the Project

• NETWORKING AND DISSEMINATION OF THE RESULTS

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Expert Workshop Recommendations, Washington,
D.C. (April 2001)

• Where are the poor, in particular the rural poor,
  located in relation to
• Agroecological zones
• Marginal or productive lands
• Major foodcrop and/or livestock production
  systems.
• Market access
• Livelihood systems

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What can we find out using Global environmental
maps?

• Using LandScan2001 population data, we have
  determined that
• About 620 million people live in agroecological
  zones (AEZ) where moisture and temperature allow
  crop growth for less than 120 days.
• ...incomes of these people have to come mainly
  from sources other than rainfed cropping.

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Population density in areas where LGP lt60
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Length of Growing Period (LGP) variability
(Standard Deviation of LGP in days)
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Population density (rural/urban) projection maps
for 2015 Why do we need them?

• We need to know how many people live where and
  under what environmental conditions in 2015, the
  target date of WFS, MDGs and the Johannesburg
  Summit.
• .

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One of the main challenges in poverty mapping
COMBINING SOCIO-ECONOMIC DATA AGGREGATED BY ADMIN
BOUNDARIES WITH ENVIRONMENTAL DATA BASED ON
NATURAL BOUNDARIES BUT, DESPITE THESE
DIFFICULTIES, COMBINING THESE TWO KINDS OF DATA
IS IMPORTANT
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For linking socio-economic and environmental data

• We need GIS models to pixelize the socio-economic
  data (spatial disaggregation or rasterization by
  modelling )

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Ghana first and second level admin units
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Pixelization of socio-economic data Population
density
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Input maps to the pixelization model
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Input maps to the pixelization model
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Pixelization of socio-economic data Population
density
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Thank you.
ergin.ataman_at_fao.org