IN SUPPORT OF THE MILLENNIUM DEVELOPMENT GOALS: GIS USE FOR 
POVERTY REDUCTION TASKS 
Felicia O. Akinyemi 
GIS and Remote Sensing Research and Training Centre, National University of Rwanda 
P.O. Box 212, Butare, RWANDA 
- felicia.akinyemi@cgisnur.org - fakinyemi@yahoo.com 
WG V1I/7 
KEY WORDS: Geographic Information System, Poverty Management, Spatial analysis, Visualization, Overlay analysis, Digital 
mapping 
ABSTRACT: 
To achieve the goal of poverty reduction, as encapsulated within the Millennium Development Goals, the collection, analysis, and 
use of geographic information as it relates to the multidimensionality of poverty offers a starting point. The spatial handling of 
poverty is an emerging paradigm for which researches on the spatial modelling of poverty are required. Attempting to contribute to a 
better understanding of poverty mapping, this paper examines GIS suitability for use in poverty application areas. GIS analysis 
functions most appropriate for use in specific poverty mapping tasks are examined. The uses are identified as data integration of 
socio-economic, environmental, cultural data, etc.; delineation of areas lying within a specified threshold distance from selected 
features or places; deriving further data from spatial analysis for multivariate analysis of poverty; deriving straight-line and network 
distances; visualisation and presentation of the results of poverty analysis. Special emphasis is placed on ways in which GIS is being 
used and its suitability for poverty reduction tasks to help draw out some relevant methodological and policy lessons. 
1. INTRODUCTION 
Halving world extreme poverty (1.2 billion people) by year 
2015 has been made the first and most prominent of the 8 
United Nations' Millennium Development Goals (MDG) thus 
making the issue of poverty reduction a global challenge. 
Harnessing the potential of GIS-based ICTs (Information and 
Communication Technology) for poverty reduction is 
imperative. Poverty is a multidimensional problem which is 
best tackled using a multidisciplinary approach. It includes low 
income, low food consumption, ill-health, reduced life 
expectation, poor education, lack of assets, limited access to 
natural resources, low social status, lack of political voice, poor 
access to ICT, social services and welfare facilities. With 
poverty levels varying within and between countries or regions 
of the world, the fact remains that the different manifestations 
of poverty are as a result of the interplay of myriads of factors 
over time (such as geography, history, ethnicity, access to 
markets and public services and public policy (See Figure 1). 
Figure 1 reveals that poverty is multidimensional and the 
indicators are numerous. With these dimensions closely related 
one to another, indicators rarely occur alone as the presence of 
one form of poverty appreciably increases the probability of 
occurrence of all others (Akinyemi 2007a). 
The multidimensional nature of poverty itself adds to the 
complexity of its handling because actors in poverty reduction 
often see poverty differently, both in their perception and 
approaches. How poverty is handled very much depends on how 
the problem is perceived and understood. Generally, poverty 
measures can be broadly categorized as income (monetary) 
based or non-monetary measures of poverty. The data 
requirements and implementation costs differ for each method. 
While monetary measures no longer have exclusive hold on our 
attention, they remain central to analysis. The past two decades 
of experience, though, reinforce the value of collecting health 
and education data, as well as other social indicators that 
describe broader conditions of poverty. Increasingly, 
researchers also find value in asking about subjective views of 
poverty and in seeking input on poverty through participatory 
exercises that involve participants from local communities. 
Direct measures of access to basic services and infrastructure 
also provide important inputs in the policy making process 
(United Nations Forthcoming). 
Recent studies showing the importance of spatial variables in 
tackling poverty have promoted the use of poverty maps made 
within a Geographic Information System (GIS) environment to 
better understand who the poor are, where the poor are found 
and to some extent, why and how long they have been poor. 
Consequently, decision makers can better identify and 
understand from maps, the socio-economic and development 
variations among regions for planning purposes. This makes 
poverty maps invaluable tools for poverty reduction especially 
in their use for targeting poverty alleviation programmes (PAPs). 
With appropriate scale and robust poverty indicators, poverty 
maps can assist in the implementation of PAPs, making for 
efficient allocation of resources. Using geographic targeting 
techniques, as opposed to across the board subsidies, has been 
shown to be effective at maximizing the coverage of the poor 
while minimizing leakage to the non-poor (Baker and Grosh 
1995 in Henninger 1998). 
Spatial analysis of poverty has been utilized in a number of 
policy and research applications ranging from targeting 
emergency food aid and anti-poverty programmes to 
assessments of the determinants of poverty and food insecurity, 
in addition to providing visual representations of spatial 
relationships between variables. Poverty mapping applications 
have been used by organizations ranging from governments 
(municipality, state/province, national) to non-governmental 
organizations and multilateral development organizations.