Extracting the Low-income Characteristics ...

Due to urbanization and urban growth, the developing country also generates the major driving force of slum / low-income settlements and conditions. In particular, Principle Component Analysis (PCA) techniques are interpreted on independent variables of statistical approach. It was produced to identify source of Low-Income Settlement Characteristic (LISC) and results of different associations among the possibility of urbanization crisis in the Bangkok Metropolitan Region (BMR) of Thailand. The research result was extracted from a large data set using 22 well-known indicators under 6 components, comprising socio-economic vulnerability indexes. From the loading plots, the calculation of many indicators were indicating the strong correlation among these variables: (1) personal contribution, (2) living density, (3) expenditure estimation, (4) slum / low-income condition, (5) industrial sources, and (6) facility sources. Our finding, information indices represented a potentially useful measure for the low-income characteristic changes. Hence, the normalized indexes indicated the possible highlight sites of the vulnerability indices using spatial geographical settlements, makeing likely improvement and localization in construction of quality of life and urban planning level between similarly indices.