The preliminary research on the multidimensional poor information spatial processing and measuring

Poverty is an important country to solve the livelihood problems. Poverty identification is mainly based on a single income standard. Sen´s poverty thinking that poverty is determined by a number of dimensions. Main source of data in the 2000 census in the years 1949-2005 Lan national economic statistics Lan county neighborhood population, the use of multidimensional poverty theory, using the inverse distance weighted interpolation(IDW), the Multidimensional poverty spatial processing of information, research Lan county River Township, East towns and counties, the Lan towns townships multidimensional Poverty level, the weighting factors of each dimension of poverty measurement considering the three dimensions of poverty, and poverty grading classification of thematic mapping. The result shows that: single income dimension of poverty and multidimensional analysis of the extent of poverty is different, and more accurately identify the extent of poverty of the multidimensional.