تحليل مكاني آمدوشدهاي روزانه مرتبط با كار و تحصيل در مناطق روستايي پيرامون كلا نشهرها(مطالعه موردي: منطقه كلا نشهري تهران)-

Spatial Analysis of Commuting Population for Workand Education Around of Metropolis Area (CaseStudy: Tehran Metropolis Area)

سفرهاي روزانه بين مراكز روستايي و نقاط شهري پديده اي است كه در همه كشورها، با تفاوت هايي برخاسته از ساختارهاي اقتصادي و اجتماعي آن ها، مشاهده مي شود. در كشور ما نيز اين پديده، با توجه به گسترش مناطق كلان شهري و مسايل و مشكلات، از جمله گراني مسكن، رو به افزايش است. تاكنون آمار رسمي از اين تعداد جمعيت منتشر نشده است. در سرشماري سال 1385 اولين تلاش براي بررسي اين جمعيت انجام شد. در اين بررسي با استفاده از تحليل اكتشافي و به كارگيري آمارهاي فضايي سعي شد اين پديده از نظر مكاني و توزيع فضايي پيرامون كلان شهر تهران بررسي شود. رفت وآمد روزانه براي كار يا تحصيل در سطح روستاهاي كلا نشهر تهران در سه وضعيت مراجعه از روستا به شهر، از روستا به روستا، و از شهر به روستا بررسي و مشخص شد ، دو خوشه بزرگ در جنوب تهران مهم ترين مراكز فرستنده جمعيت براي كار يا تحصيل به نقاط شهر ي اند ؛ يعني بخش هايي از ري، پاكدشت، رباط كريم، و شهريار. مهم ترين قطب فرستنده جمعيت به نقاط روستايي براي كار يا تحصيل نيز شهرستان پاكدشت است. مراجعه جمعيت از نقاط شهري به نقاط روستايي نشان م يدهد اين مقادير براي كل منطقه كلان شهر تهران الگويي تصادفي دارد. به عبارت ديگر، مراكز خاصي با اين خصيصه در كلا نشهر تهران وجود ندارد؛ ولي نقاط شهري رودهن، پرديس، پيشوا، پاكدشت، بومهن، نصيرآباد ، و شاهدشهر بيشترين جمعيت را به نقاط روستايي براي كار يا تحصيل م يفرستند.

Commuting between urban centers and rural areas is a phenomenon that observed in all countries with different social and economic structure. Commuting is a new phenomenon in move of population that emerged with metropolis development. This phenomenon is different with other population movement. Because this move does not change in residential place, population work in other place. There are two reasons for commuting. First, people change their house but not change employment. Or people change their work but not change their house. Relationships between urban areas and rural areas and live in villages and work in urban areas are a dominant pattern in rural and urban integration. Research on spatial patterns of commuting to work has become an important issue in urban studies. Centralization and decentralization in the population of the metropolitan complex patterns and travel to work and residence within the metropolitan suburbs are among the most important phenomenon in the big cities. Many studies in the past decades deal with the dynamics of commuting. According to the 2006 census, commuting for metropolis of the country as one of the questions were asked from the households. This phenomenon is observed in the rural population around of metropolis areas and based on the Censusreport; this phenomenon can be seen in rural areas than in urban areas. According to the Census Bureau Report, about one-eighth of 10 years old and over of population in 2006 census had 1 Responsible Author: rajaeiabbas41@gmail.com Rural Research, Vol.4, No.2, Summer 2013 27 the commute. An attempt to study spatial clusters of this phenomenon in Tehran metropolis, what is these phenomena between surrounding rural population in metropolis and Tehran metropolis? And what is their spatial distribution? Methodology In this study to analysis of commuting in metropolis area, the analysis of spatial data exploration and spatial statistics was used. The analytical unit in this study is dehestan and data was taken from SCI that is about of place of work and education. Commuting for work and education in Tehran metropolis area investigated in three levels: 1. rural area to urban centers, 2. urban centers to rural area, and 3. rural area to rural area. For analysis of spatial data exploration and spatial statistics used of spatial autocorrelation (moran) and High/ Low cluster (Getis– ord General) methods, inverse distance entered for of distance analysis. Results Research findings show that rural area to urban centers commuting is an important pattern in Tehran Metropolis. According to results of this study parts of Rey, Pakdasht, Robatkarim and Shahriar are two important clusters that send commuters of rural area to urban centers. Morans index for this pattern is 0.1, Z value is 2.7 and significant level is 0.005. Two largest population centersin the south and southeast of Tehran Metropolis include Varamin, Pakdasht and Robat Karim are two centers that transmitter rural population to the rural areas for working or studying. The center currently has the highest population growth in the metropolis area and the largest emitters of the Tehran urban areas to rural areas are considered. Rural populations that for work or study go to other rural areas in Tehran metropolis areas how that Pakdashtand parts of Varamin region has the highest rural population characteristics within themselves. The median age is 27 years. Fern-Abad villages, Fylestan, Sharif Abad, Ghanyabad are the largest senders of population from rural to urban and urban to rural was considered. Distances from the main city showed that distance has direct impact on commuting population. For this pattern morans index equal to 0.1, Z vale is 3.08 and significant level is 0.002 that show one cluster pattern for rural area to other rural area commuting. Commuting of Urban to rural area is random and not found a pattern for it. But Rudehen, Pardis, Pishva, Pakdasht, Boomhen, Nasirabad, Shahedshahr are important centers with highest commuter in Tehran metropolis area. Conclusion In this study, we try to show commuting pattern around of Tehran metropolis. The results show there is relation between three pattern of commuting around of Tehran metropolis, due to expansion of metropolis area and the problems such as housing price and rent is growing has caused that rural area around the metropolis to become dormitory settlements. According to result of this study parts of Rey, Pakdasht, Robatkarim and Shahriarare two important clusters that send commuters of rural area to urban. Pakdast is important county in send rural commuters to other rural area. Commuting of Urban to rural area is random and not found a pattern for it.