Spatial Pattern Analysis of Rural Settlements in Connection with the Earthquake Vulnerability (Case Study: Central District of Marand County)

Journal of Research and Rural Planning

مقاله 3، دوره 5، شماره 3 - شماره پیاپی 15، اسفند 2016، صفحه 61-74   

نوع مقاله: علمی

شناسه دیجیتال (DOI): 10.22067/jrrp.v5i3.46183

نویسندگان

kolsoum Zakeri-e-Miyab^* ؛ Mohsen Aghayari-e-Hir

Tabriz University

چکیده

Extended Abstract
1. INTRODUCTION
Earthquake is one of the most important factors in vulnerability of rural areas in Iran, which particularly due to shallow epicenter, causes a lot of damage. In addition to the absolute and relative position of different parts of the country, rupture of spatial organization and the lack of hierarchy based on interactive relationship among settlements, are acknowledged as the most influential factors. This condition leads to disorganization of the population, activities, services and functions, and in turn, increases the vulnerability of rural settlements against natural hazards, including earthquake. In this regard, determining appropriate pattern of settlements is seen as necessary to limit the adverse effects of earthquake.
2. THEORETICAL FRAMWORK
Distribution of settlements, with respect to the form, can be often described as; random, regular, or clustered, but are rarely seen in real conditions. Each of these patterns provides different conditions in terms of how to deal with the critical situation, if relying on inner capacities of the settlement systems, and shows different reactions against earthquake risk.
1. Dispersed pattern: is when the population in an area is uniformly distributed. According to this pattern, any of the small settlement points are developed and the further expansion of some special points are prevented. Such condition could result in dispersion of the facilities and investments.
2. Clustered pattern: is when population was concentrated in one, two, or three points. According to this pattern, rural settlements are faced with the concentration of industrial activities, services and population in those central settlements.
3. Random pattern: is when population is distributed in small and large population centers with a given order. In this pattern, although medium and larger points were developed, however, the emphasis is on the development of small points. The characteristics of each spatial patterns of the settlement system to deal with the critical situation are as follows:
 In the scattered pattern, settlements have access to the minimum services and infrastructures. This pattern causes the dispersion of facilities (such as specialized therapeutic activities) and investments, which in turn, increases the vulnerability of the settlement system in critical condition, in deferent ways.
 In the clustered pattern, from economic point of view, providing public and infrastructural services is desirable, but the relationship between rural settlements due to accessibility problems, remains unresolved. To maintain the central settlement from risk and minimizing vulnerability, heavy economic investment will be required to retrofit constructions, facilities, and buildings.
 In the random pattern, the system has the benefits of both previous patterns. Accessibility was easier and service levels were increased. In this situation, investments and resources are concentrated on the midpoints. In such circumstances, by division of labor between the central and midpoints, the volume of activities and services in central locations as well as investment needed for retrofitting the central regions, were reduced. Therefore, much of the investments goes to medium points.
3. METHODOLOGY
This study is an applied research and was performed with descriptive-analytic method. The statistical population of the study is 74 villages of Central District of Marand County, which entirely are included in the study. In this regard, Moran's I index was used to determine the distribution /concentration of spatial vulnerability of rural settlements and Kolmogorov-Smirnov test was used to analyze the differences in distribution of villages at different levels of vulnerability in the study area. Geographic Information Systems (GIS) were used for data processing, analyzing, and presentation of the results.
4. DISCUSSION
Since the rural settlements of Central District of Marand county lie in high-risk earthquake zone, investigation of the existing spatial pattern and determining the appropriate pattern of rural settlements of the area, is necessary for reducing the destructive effects of earthquake. Therefore, in this article, beside of the determining of the settlement pattern of rural points in the region, we analyzed the vulnerability of spatial patterns of rural settlements in Central District of Marand County.
5. CONCLUSION
Moran's I index indicates that the spatial correlation in the target area at the 99% confidence level is positive, and spatial distribution pattern of the villages in the region is highly centralized or clustered. Consequently, investigating of the spatial pattern of villages in the study area shows that they have not been distributed uniformly and balanced. Then, using Reclassify Function in the ArcGIS 9.3 software, the geographical space of the study area is classified into three areaswith high, medium, and low vulnerability, and based on the Moran's I spatial autocorrelation, spatial analysis between the villages was performed for each area. Results show that, the villages in high vulnerability area have more tendencies for centralization and clustering. To check significant difference between two types of distributions in the villages (the observed and expected values) at different levels of vulnerability, the Kolmogorov-Smirnov test was used. The test results showed that the statistic (value Dmax = 0.205) is larger than critical value W (1- α) at 0.95 standard confidence level. So, there are significant differences between two distributions of rural settlements in deferent levels of vulnerability with expected values. On the one hand, it is indicative of the vulnerability of the region against natural disasters, and on the other hand, clustering of villages with high vulnerability, provides an opportunity for quick and practical organization of the situation in needed times with less cost, comparing to scattered pattern.

کلیدواژه‌ها

Earthquake؛ rural settlements؛ disaster management؛ Spatial Analysis؛ Distribution pattern

مراجع

1. Afrakhteh, H. (1387/2008). Introduction to the planning of rural settlements. Tehran: Ganj Honar Publication. [In Persian].

2. Ahadnejad Roshti, M., Movlaei Ghelichi, M., Javadzadeh Aghdam, H., & Hatemi, A. (1391/2012). Analysis of the spatial distribution pattern educational centers and suitable physical organize by using GIS (Case Study: Area 8 Tabriz). Journal of Research & Urban Planning, 3(8), 1-18. [In Persian]

3. Bahraini, H. (1375/1996). Research project space-spatial analysis and planning of settlements to reduce the risk of earthquake. Tehran: Islamic Revolution Housing Foundation Publication. [In Persian].

4. Bahrami, R. (1390/2011). Environmental limitations and their impact on instability in rural settlements (Case study: Sanandaj county). Journal of Rural Studies, 2(3), 145-167. [In Persian]

5. Beladpas, A. (1390/2011). Analysis of environmental hazards and geomorphologic rural settlements in the north Marand (plain Halakow). Journal of Geographic Space, 11(36), 1-23. [In Persian]

6. Bevan, A. & Conolly, J. (2006), Multiscalar approaches to settlement pattern analysis. In Confronting Scale in Archaeology: Issues of Theory and Practice (Pp. 218-234). New York, Springer US.

7. Cho, S. H. & Newman, D. H. (2005). Spatial analysis of rural land development. Journal of Forest Policy and Economics 7(5), 732– 744.

8. Dolfos, A. (1374/1995). Geographical space (2st Ed., S. Sahami, Trans.). Tehran: Nika publication. [In Persian]

9. Faraji, A., & Gharakhlou, M. (1389/2010). Earthquake and Disaster Management (Case Study: Babel City). Iranian Geographical Association, 8 (25), 143-163. [In Persian]

10. Hodder, I. R., & Orton, C. (1979). Spatial Analysis in Archaeology (2st Ed.). Cambridge: Cambridge University publication.

11. Holdaway, S. J. & Wandsnider, L. (2006). Temporal scales and archaeological landscapes from the Eastern Desert of Australia and Intermontane North America. In Confronting Scale in Archaeology, Issues of Theory and Practice, (pp 194-199), Springer US.

12. Illian, J., Penttinen, A., Stoyan, H., & Stoyan, D. (2008). Statistical Analysis and Modelling of Spatial Point Patterns. British Library Cataloguing in Publication Data, John Wiley & Sons Ltd.

13. Kazemnejhad, A., Khalkhali, H. R., & Kazempour Dizaji, M. (1380/2011). 100 statistical test to guide spss software. Tehran: Institute of Culture and Arts Dibagaran publication. [In Persian]

14. Lee, J., & Wong, D. W. (2001). Statistical Analysis with Arcview GIS. Canada: John Wiley & Sons publication.‏.

15. Liu, Y., Lu, Sh., & Chen, Y. (2013). Spatio-termporal change of urban-rural equalized development patterns in china and its driving factors. Journal of Rural Studies, 32,320-330.

16. Long, H., Liu, Y., Wu, X., & Dong, G. (2009). Spatio-temporal dynamic patterns of farmland and rural settlements in Su–Xi–Chang region: Implications for building a new countryside in coastal China. Journal of Land Use Policy, 26(2), 322-333.

17. Ma, X., Qiu, F., Li, Q., Shan, Y., & Cao, Y. (2013). Spatial pattern and aregional types of rural settlements in Xuzhou City, Jiangsu province, China. Journal of Chinese Geographical Science, 23(4), 482-491.

18. Mokhtari, D. (1383/2004). Evaluation of geomorphologic path of Tabriz-Marand in Payam cervix on the northwest of Iran. Journal of Teacher Humanities, 9(4), 87-111. [In Persian]

19. Pelling, M. (2007). Learning from others: the scope and challenges for participatory disaster risk assessment. Disasters Journal, 31(4), 373–385.

20. Peng, Y., Shen, L., Tan, C., Tan, D., & Wang, H. (2013). Critical determinant factors (CDFs) for developing concentrated rural settlement in post-disaster reconstruction: a China study. Journal of Natural Hazards, 66(2), 355-373.

21. Perles, C. (2001). The Early Neolithic in Greece: the first farming communities in Europe. Cambridge: Cambridge University publication.

22. Pourahmad, A., Lotfi, S., Faraji, A., & Azimi, A. (1388/2009). Assessment of dimensions of the prevention of earthquake cricis (Case study: Babylon county). Journal of Urban and Regional Studies and Research, 1(1), 1-24. [In Persian]

23. Purtaheri, M., Parishan, M., Rokneddin Eftekhari, A., & Asgari, A. (1390/2011). Measurement and evaluation of the basic elements of earthquake risk management (Case study: rural areas of Qazvin county). Journal of Rural Studies, 2(1), 115-150. [In Persian]

24. Qadeer, M. A. (2004). Urbanization by implosion. Habitat International, 28(1), 1-12. ‏

25. Roberts, B. k. (2003). Landscapes of settlement prehistory to the present (2st Ed.). USA and Canada: Routledge publication.

26. Sadeghi Nia, A., Alijani, B., Ziaeian, P., & Khaledi, sh. (1391/2012). The Use of Space auto-correlation techniques to analyze the thermal island of Tehran. Journal of Applied Researches in Geographical Sciences, 13(30), 67-90. [In Persian]

27. Saeedi, A. (1389/2010). Recognition of rural settlements. Tehran: Mehr Mino publication. [In Persian]

28. Seifolddini, F., & Mansourian, H. (1390/2011). Pattern of Urban Services Concentration and Its Environmental Impacts on Tehran City. Journal of Environmental studies, 37(60), 53-64. [In Persian]

29. Statistical Center of Iran. (1392/2013). Birth certificate villages of East Azarbaijan province in 2011. Tehran: Statistical Center of Iran. [In Persian]

30. Tian, G., Qiao, Z., & Zhang, Y. (2012). The investigation of relationship between rural settlement density, size, spatial distribution and its geophysical parameters of china using landsat TM images. Journal of Ecological Modelling, 231, 25-36. ‏

31. Torres, M., Vosti, S. A., Bassoi, L. H., Howitt, R., Maneta, M. P., Rodrigues, L. N., & Young, J. A. (2007). Spatial Patterns of Rural Poverty in the São Francisco River Basin, Brazil. Selected Paper prepared for the American Agricultural Economics Association annual meeting, Portland, Oregon.

32. Waller, L. A. & Gotway C. A. (2004). Applied Spatial Statistics for Public Health Data. Hoboken, New Jersey in Canada: John Wiley & Sons publication.

33. Waller, L. A., & Gotway, C. A. (2004). Applied spatial statistics for public health data (Vol. 368). John Wiley & Sons. ‏

34. Wang L., & Wu R. (2013). Form the tribe to the settlement- human mechanism of Tibetan colony formation-In Case Luqu Gannan. Proceeding of the International conference on Advances in Social Science, Humanities and Management (ASSHM 2013). Atlantis Press. ‏

35. Williams, M. (1977). Settlements in rural: Planned landscapes and unplanned changes in South Australia. Journal of Landscape Planning, 4, 29-51.

36. Zakeri Miab, K. (1392/2013). Spatial Analysis of Rural Settlement System with emphasis on disaster risk reduction (Case study: the central District of Marand county). Unpublished master’s thesis. Tabriz University, Tabriz. Iran.