The Poverty mapping between Periatalai and Kannappapuram coast using GIS Approach: A case study southern Tamilnadu Coast

The Poverty mapping between Periatalai and Kannappapuram coast using GIS Approach: A case study southern Tamilnadu Coast

Geographically, poverty status is not only related with social-economic factors but also strongly affected by geographical environment. In the paper, GIS-based poverty and population distribution analysis method is introduced for revealing their regional differences. More than23 poor villages are chosen for the analysis. The results show that poverty distribution tends to concentrate in most of west China and mountainous rural areas of mid China. Furthermore, the fifth census data are overlaid to those poor areas in order to gain its internal diversity of social-economic characteristics. By overlaying poverty related social-economic parameters, such as sex ratio, illiteracy, education level, percentage of ethnic minorities, family composition, finding shows that poverty distribution is strongly correlated with high illiteracy rate, high percentage minorities, and larger family member.

In this research to find out the coastal poverty along the south eastern coast of Tamilnadu different methodology used. Recently, some new techniques have been developed that combine field survey data, household and census data to estimate coastal poverty for more disaggregated geographic units. In general, all these techniques involve two common steps. First, household survey data is used to estimate poverty or expenditure as a function of household characteristics such as household composition, education, occupation, housing characteristics, and asset ownership. Second, census data on those same household characteristics are inserted into the equation to generate estimates of poverty for small geographic areas poverty.

There are many potential indicators of coastal poverty. In deciding which variables to include, the desirability of including a parameter must be balanced against the availability of up-to-date data that is in a useable format. Therefore the variables chosen for inclusion in the index were those, for which data could be easily obtained,and which were also deemed to be of relevance to coastal areas. The coastal poverty variables selected for inclusion in the coastal poverty variables sub-index are listed below:

Population

Cultural heritage

Roads

Railways

Landuse

Of thesefive variables, roads and railways are the simplest environmental assets to incorporate into an index. They occupy defined space, are of defined widths and the costs of protecting, replacing or relocating them are relatively simple to evaluate. Therefore this paper concentrates on the remaining four variables and discusses the problemsEncountered in using them in a socio-economic index.

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