تحلیلی بر مهاجرفرستی شهرستان ها به مرکز استان؛ علل و روند ها (مطالعه موردی: استان آذربایجان غربی)

Introduction

Forecasts indicate a significant increase in population in urban centers. Larger urban centers and metropolitan areas, such as magnets, often attract this population in the form of various forms of migration. This growing flood of migration to large cities, which is usually faster and more intense in third world countries, creates many problems at the source and destination, including the lack of urban and public services in the destination and the shortage and loss. The workforce pointed to the origin. One of the main destinations of immigrants from villages and small towns is to move to the city center of the province, as a big city that acts as a metropolis in the region.

One of the provinces in Iran where such migration flows are observed is the province of West Azerbaijan, where research on the trends and reasons for the migration of its cities to the center of the province seems necessary. In this research, the following questions have been answered:

What has been the process of emigration to the center of the province during the period of 85-90 and 90-95?

Spatial distribution of migratory data on which of the following patterns of spatial distribution was consistent?

What factors affect the emigration of cities to the center of the province?



Methodology

The present study is a descriptive-analytical research with an applied approach. The data used from library resources such as statistical yearbooks of the province were extracted from the Statistics Center of Iran, and in their analysis, spatial statistics and inferential statistics were used. Spatial statistics analysis is performed in ArcGIS software environment. In this regard, first the immigration classification maps of the cities were drawn according to the statistics published by the National Statistics Organization in the two periods of 85-90 and 90-95.

Data analysis was performed in two parts: trends and causes of migration. Regarding the process of migration of cities to the center of the province, first by Moran spatial autocorrelation statistics, the type of spatial distribution of migration data was investigated and then by using hot spot analysis, hot spots of migration were identified. Then, the factors affecting the migration of cities to the center of the province in the form of independent variables were modeled using geographically weighted regression analysis.

Results and discussion

Salmas city with 3776 people had the highest and Takab city with 333 people had the lowest number of emigrants to the center of the province and the rate of emigration of other cities was between these two cities.

According to the value obtained for Moran index which is positive and significant, the migration data of cities have spatial autocorrelation and cluster spatial distribution pattern and are not randomized or scattered.

Hot spot analysis was used to identify places with high value clustering, or hot spots; The results showed that in the period of 90-95, high amounts of emigration in Khoy and Salmas counties have formed hot spots.

However, the results of correlated t-test showed that there were no statistically significant changes in the rate of emigration in the mentioned time period. The variables considered and related to the theoretical foundations and research background in the form of geographically weighted regression analysis have been affected on the dependent variable, the rate of migration to the center of the province. In this regard, five variables of population density, distance of origin and destination, the amount of urban services, urbanization coefficient at the origin and the number of job applicants at the origin, entered the regression model. The results of the model were evaluated with goodness –of- fit indicators; The value of R2 for the whole model is 0.773438 and the value of Local R2, for other complications (cities), varies from 0.772427 to 0.773186, which is close to the value of 1, and in general shows the goodness of the regression model.

The regression model as a whole has been able to explain about 65% of the changes in the dependent variable. In the next step, by performing Moran autocorrelation analysis on the residual values ​​of the regression model, the residual spatial distribution pattern was investigated; The value of Z obtained for the residual distribution is negative and no cluster distribution is observed in the residuals and the residues follow the pattern of random spatial distribution.

The effect of each variable on the dependent variable of the migrant was evaluated; The effect of population density variable in the northern cities of the province was more than the southern cities of the province. The effect of the variable of origin and destination distance is more evident in the south and southeast of the province than in the north of the province. Changes in the effect of the variable number of job applicants at the origin, from northwest to southeast of the province has an increasing trend. The effect of the urbanization coefficient variable at the origin from north to south of the province shows a decreasing trend. Contrary to the effect of the variable of having urban services at the origin, the trend is increasing from the north of the province to the south and southeast of the province.

Conclusions

In this section, the main research questions were answered. Migrant data has a cluster distribution pattern. The trend of migration of cities to the center of the province during the periods of 90-85 and 90-95, in general, does not show statistically significant changes.

Regarding the causes of migration to the center of the province, it can be said that the five variables of population density, distance of origin and destination, level of urban services, urbanization coefficient at the origin and number of job applicants at the origin, explain 65% of the dependent variable changes.