Poverty is a socio-economic scourge raging at varying degrees throughout the Sri Lanka. Its prevalence is most pervasive in the cores of Sri Lankan traditional cities than in the urban peripheries which tend to be more modernized. Non-recognition of the heterogeneous nature of urban poverty and the many players involved in its management has only helped to aggravate the problem. Consequently, a holistic planning, implementation and control approach is imperative. This should involve all tiers of government, non-governmental bodies, and donor agencies, international Non Governmental Organizations with the research community on one hand, and a combination of historical, economical, sociological, anthropological and spatial perspectives on the other hand. The spatial perspective, which is the main focus of this paper, serves to interface with the other perspectives since people are used to space and they live in space. In this regard, Geographic Information Technology (GIT) is of utmost importance with the Spatial Database Management System (DBMS) as its heart. The essence of any DBMS is that data should be stored in an organized manner for easy retrieval to aid decision-making. Moreover, the use of Geographic Information System (GIS) for poverty-related data handling is superior not only to manual (traditional) data handling methods, but advantageous over other information systems as it admits data coming from different sources. This is because GIS derives effective results on making decisions on alleviating poverty by analysis and mapping via efficient spatial and attribute data storage and handling. This paper centres on the design of a GIS database for urban poverty assessment and inventory mapping. It is concerned with improving the effectiveness of managing urban poverty by designing a generic model showing the datasets and the relationships required for poverty appraisal application.
It defines poverty as a relationship between income and consumption, it measures it by means of poverty lines and it attempts to reduce it through macro- economic policies and specific single-line programmes designed within the areas of competence of sectoral agencies. Its applications have been particularly useful for statistical comparisons between levels of poverty in different populations. 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. A variety of urban poverty conditions, expressing more accurately the realities of city life than statistical methods. However, the importance of human settlements as one of the most significant fields for the study, comprehension of and actions against poverty cannot be ignored. The informal human settlements come closer to constitute and express the indivisible whole reality of poverty than any other manifestation of the people living in poverty. It is expected, therefore, that the qualitative definitions might show the recurrence of particular attributes in the conditions of urban poverty that justify the development of specific indicators within a common concept of poverty.
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).
Establishing a direct relationship between information and their geographical location is a unique characteristic of GIS, a versatile tool that also enables information to be displayed as maps. As a decision-support tool, GIS helps to integrate several data sets, and unravel complex relationships between phenomena within an ordered spatial framework. The former capability is of utmost importance since data sources for poverty management are multifarious as reflected in the varied poverty indicators in use. GIS has strong analytical potential for understanding the ‘where’, ‘how’ and ‘why’ of poverty as it varies from place to place, especially in an urban setting. All these capabilities coupled with the ability of GIS to quickly update information, make it much suited as a timely and reliable tool for improving data handling for urban poverty management. In particular, a municipal council stands to benefit more from spatial information since the incidence; intensity and severity of poverty are not the same all over the municipal council . Much disparity in the quality of life (welfare) occurs within and between different neighbourhoods, especially between predominantly residential and commercial neighbourhoods.
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, province, national) to non- governmental organizations and multilateral development organizations.
2. Urban Poverty in Eastern Province of Sri Lanka
Urban poverty, which is rapidly increasing, is due to receive more attention although the poor in Eastern Province of Sri Lanka are still mainly concentrated in rural areas. With the escalation in urban poverty in recent years, urban dwellers are faced with constraints quite different from that of their rural counterparts. For example, urbanites pay higher rent for accommodation and transportation, seek work where employment opportunities are scarce and deal with abysmal sanitation facilities. In addition the urban poor pay higher prices for urban land when it is available at all – even land that receives no services. The influx of rural poor people into the towns coupled with inadequate planning and provision of employment opportunities lead to increased poverty in our cities .
The poverty database captures most of the basic data of poverty. It is a simple and yet effective methodology to identify and monitor/assess poverty interventions. Poverty data is translated into easily understandable and usable information for decision-making in poverty intervention management. It allows selecting the villages for support without arguing along the perceptions of ethnic entitlements, spatial interest or political dominance. Since the data is from the smallest spatial unit, the loss of information due to generalization is also minimized.
3. Urban Poverty Management
Data on urban dynamics in Eastern Province of Sri Lanka is not readily available and where available, they are in a disparate form. The system was developed in a GIS environment because of its three major advantages, namely, data organization, spatial analysis, and visualization. The system involved integrating and structuring different poverty data sets from various sources in a common database. This facilitated data analysis and their integration to the geo-information of the city to provide for their spatial dimension. Furthermore a simple interactive graphic user interface was designed so as to enable users with limited knowledge of computing to operate and interact with the system. With the calculation of settlement density and growth rate as well as the qualitative settlement patterning, new informal settlements and key areas of growth Eastern Province of Sri Lanka were detected. A low-end GIS platform was used which enabled the end-user to contribute to the database building process directly.
4. Holistic Approach to Urban Poverty Management
As earlier mentioned, the heterogeneity of the urban setting does not lend itself to one approach in its management. A holistic and more generic approach to urban poverty management is most suitable. Figure 1 illustrates this approach. It is clearly shown that the local government and Provincial council play the most important role in alleviating poverty within its area of jurisdiction . Moreover, the foregoing necessitates more urgently the provision of urban mapping and land information as the spatial basis for administration and the provision of infrastructure and social services to satisfy the rising expectations of urban dwellers .
It must be noted that the adoption of the use of GIS by the council is a costly investment, since investment includes spending on hardware, software, human ware and the institutional framework. However to recover the full or partial cost of such investment, information can be sold to users especially the agencies and researchers. If the necessary policies and standards are set, then the data at the council level can be aggregated to higher regional levels such as the provincial and district level to form the National GIS (NGIS).
However laudable any urban poverty alleviation program is, its success will depend much on being able to answer these questions: ‘who are the poor? ’ and ‘where are they to be found?’ Unfortunately there are no reliable statistical records directly defining the distribution of the poor in space . This is where GIS would be of utmost usefulness since it helps to relate results of poverty measures to their actual geographic location.
Figure 1: Players and roles in urban poverty generation and management
5. Poverty Assessment Component of the GIS
Urban poverty management necessitates assessing poverty differentials occurring in different neighbourhoods making up the city. This study used GIS primarily for poverty inventory mapping in Eastern Province of Sri Lanka. Poverty inventory mapping involves assessing and mapping the various levels of poverty as it occurs in households and aggregating household poverty to derive poverty levels in neighbourhoods. Figure 2 shows the conceptual model for poverty assessment in the GIS. For the design of the conceptual model, an entity-relationship (ER) approach was adopted .
Figure 2: GIS as tool for urban poverty inventory mapping and alleviation simulation
All these datasets and the relationships between them as required for the poverty assessment application are shown in the model. The conceptual schema was then defined in the database using a relational data structure. Relational database and GIS are very effective tools supporting planners and decision makers in assessing and understanding actual situations and trends in various fields of application. In particular, the uses of geo-databases for information management nowadays provide more efficiency in handling of spatial and attribute data .
This study has demonstrated the spatial perspective to poverty management at a microeconomic urban scale. Developing an urban GIS database is of utmost importance to any local urban municipal authority in tackling the various levels of poverty occurring at the household and neighbourhood levels. Such a database should house disaggregated household data since it is best for urban poverty management. This is because as the targeting of a given poverty reduction initiative becomes more precise geographically, under-coverage and leakage rates fall and the impact on urban poverty improves . Moreover it is costly and time consuming to generate and manage such data since working at such detailed level will definitely require greater information and confidentiality.
The immense value of GIS as the singular tool for understanding human-environment interaction is resulting in its increasing use. Consequent upon these increasing uses of GIS in handling poverty and other social problems, it became necessary to examine GIS suitability, Most common GIS uses were identified as data integration, 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, visualization and presentation of the results of poverty analysis in the form of GIS and GIT Database.
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