Land use Changes Scenarios for Rural Areas (Case study: Bash Qaleh Dehestan –Urmia County)

Journal of Research and Rural Planning

مقاله 4، دوره 7، شماره 3 - شماره پیاپی 23، اسفند 2018، صفحه 29-44   

نوع مقاله: علمی

شناسه دیجیتال (DOI): 10.22067/jrrp.v7i3.67080

نویسنده

Aliakbar Taghilou^*

Urmia University

چکیده

Purpose- The purpose of the study is to determine the land use change scenarios in Bash Qaleh dehestan.
Design/methodology/approach- Research methodology is based on futures studies and scenario studies. First, a list of drivers using documents 34 domestic and foreign research in the field of land use was prepared and then through the view of villagers and farmers (318) (Using Likert scale) and experts (22) the importance and their impact on land use were studied. For development scenarios, a team of five experts (2 rural planners, 2 regional planners, one natural resource expert) was used. Mick Mac software and Wizard scenario were also used for data analysis.
Findings- The results showed that people's income, production level, return on investment in activity, industrial agriculture and agricultural margin were the most effective and uncertain drivers of land use change. For these drivers, eight scenarios were developed and developed.
Practical implications- Food security, encouragement of conservation of resources, encouraging policies for population growth, increasing community well-being, droughts, climate change, soil erosion, the emphasis of civil society on the rights of citizens and protection of the rights of the next generation, the emphasis of governments on economic self-sufficiency is only part of the opposite trends which has faced land use challenges. It is suggested that specific programs be developed and monitored to avoid them for any scenario.

کلیدواژه‌ها

land use؛ scenario؛ future studies؛ Bash Qaleh Dehestan؛ Urmia

مراجع

1. Alexander, P., Rounsevell, M. D., Dislich, C., Dodson, J. R., Engström, K., & Moran, D. (2015). Drivers for global agricultural land use change: the nexus of diet, population, yield and bioenergy. Global Environmental Change, 35, 138-147.

2. Boroumand. A. Abbasi A.A. & Bahrami. M. (1394/2015). Probabilistic Tree scenario-writing, Third National Conference on Future Studies. Yadeghar Derakhshan Aria, Tehran, [in Persian].

3. Bozorgi, M. (1388/2009). Research Methods in Future Thesis. Social Sciences Month Book, 14. [In Persian]

4. Bradfield, R., Derbyshire, J., & Wright, G. (2016). The critical role of history in scenario thinking: Augmenting causal analysis within the intuitive logics scenario development methodology. Futures, 77, 56-66.

5. MacNulty, C. A. R. (1977). Scenario development for corporate planning. Futures, 9(2), 128-138.

6. Van Dijk, T. (2003). Scenarios of Central European land fragmentation. Land use policy, 20(2), 149-158.

7. Ding, D., Bennett, D., & Secchi, S. (2015). Investigating impacts of alternative crop market scenarios on land use change with an agent-based model. Land, 4(4), 1110-1137.

8. Dong, C., Schoups, G., & van de Giesen, N. (2013). Scenario development for water resource planning and management: a review. Technological forecasting and Social change, 80(4), 749-761.

9. Rodriguez Eraso, N., Armenteras-Pascual, D., & Alumbreros, J. R. (2013). Land use and land cover change in the Colombian Andes: dynamics and future scenarios. Journal of Land Use Science, 8(2), 154-174.

10. Fox, T. A., Rhemtulla, J. M., Ramankutty, N., Lesk, C., Coyle, T., & Kunhamu, T. K. (2017). Agricultural land-use change in Kerala, India: Perspectives from above and below the canopy. Agriculture, Ecosystems & Environment, 245, 1-10. ‏

11. Freeman, O., & Pattinson, H. M. (2010). Exploring client scenarios associated with scenario planning. Futures, 42(4), 304-312. ‏

12. Gollnow, F., Göpel, J., Schaldach, R., & Lakes, T. (2018). Scenarios of land-use change in a deforestation corridor in the Brazilian Amazon: combining two scales of analysis. Regional Environmental Change, 18(1), 143-159. ‏

13. Shao, J. A., Wei, C. F., & Xie, D. T. (2006). An insight on drivers of land use change at regional scale. Chinese Geographical Science, 16(2), 176-182. ‏

14. Johnson, M. L., Bell, K. P., & Teisl, M. F. (2016). Does reading scenarios of future land use changes affect willingness to participate in land use planning? Land Use Policy, 57, 44-52. ‏

15. Kristensen, S. B. P. (2016). Agriculture and landscape interaction—landowners’ decision-making and drivers of land use change in rural Europe. Land use policy, 57, 759-763. ‏

16. Levers, C., Butsic, V., Verburg, P. H., Müller, D., & Kuemmerle, T. (2016). Drivers of changes in agricultural intensity in Europe. Land Use Policy, 58, 380-393. ‏

17. Lin, Y. P., Hong, N. M., Wu, P. J., & Lin, C. J. (2007). Modeling and assessing land-use and hydrological processes to future land-use and climate change scenarios in watershed land-use planning. Environmental Geology, 53(3), 623-634. ‏

18. Lu, Q., Liang, F., Bi, X., Duffy, R., & Zhao, Z. (2011). Effects of urbanization and industrialization on agricultural land use in Shandong Peninsula of China. Ecological Indicators, 11(6), 1710-1714. ‏

19. Maimaitijiang, M., Ghulam, A., Sandoval, J. O., & Maimaitiyiming, M. (2015). Drivers of land cover and land use changes in St. Louis metropolitan area over the past 40 years characterized by remote sensing and census population data. International Journal of Applied Earth Observation and Geoinformation, 35, 161-174. ‏

20. Mancosu, E., Gago-Silva, A., Barbosa, A., De Bono, A., Ivanov, E., Lehmann, A., & Fons, J. (2015). Future land-use change scenarios for the Black Sea catchment. Environmental Science & Policy, 46, 26-36.

21. Mottet, A., Sylvie, L., Nathalie, C., & Annick, G. (2006). Agricultural land-use change and its drivers in mountain landscapes: A case study in the Pyrenees. Agriculture, Ecosystems and Environment 114, 296–310.

22. Newman, M. E., McLaren, K. P., & Wilson, B. S. (2014). Long-term socio-economic and spatial pattern drivers of land cover change in a Caribbean tropical moist forest, the Cockpit Country, Jamaica. Agriculture, Ecosystems & Environment, 186, 185-200.

23. Nguyen, H. H., Dargusch, P., Moss, P., & Aziz, A. A. (2017). Land-use change and socio-ecological drivers of wetland conversion in Ha Tien Plain, Mekong Delta, Vietnam. Land Use Policy, 64, 101-113.

24. Pratt, A. C. (2009). Social and economic drivers of land use change in the British space economy. Land Use Policy, 26, S109-S114.

25. Provo, J., Ruona, W. E., Lynham, S. A., & Miller, R. F. (1998). Scenario building: An integral methodology for learning, decision-making, and human resource development. Human Resource Development International, 1(3), 327-340.

26. Da Silva, R. F., Batistella, M., & Moran, E. F. (2016). Drivers of land change: Human-environment interactions and the Atlantic forest transition in the Paraiba Valley, Brazil. Land Use Policy, 58, 133-144.

27. Snoek, M. (2003). The use and methodology of scenario making. European Journal of Teacher Education, 26(1), 9-19.

28. Swart, R. J., Raskin, P., & Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global environmental change, 14(2), 137-146.

29. Taghilou, A.A. (1394/2015). Future Scenarios of Rural Settlements in Iran, Rural Journalism Research and Program. Third Year, (5), 96-83. [In Persian]

30. Taghilou, A.A. (1396/2017). Drivers of Development of Iranian Villages. Journals of Spatial Planning, 20(4), 281. [In Persian]

31. Ustaoglu, E., Williams, B., & Murphy, E. (2016). Integrating CBA and land-use development scenarios: Evaluation of planned rail investments in the Greater Dublin Area, Ireland. Case Studies on Transport Policy, 4(2), 104-121.

32. Van Vliet, J., de Groot, H. L., Rietveld, P., & Verburg, P. H. (2015). Manifestations and underlying drivers of agricultural land use change in Europe. Landscape and Urban Planning, 133, 24-36.

33. Wang, Q., Ren, Q., & Liu, J. (2016). Identification and apportionment of the drivers of land use change on a regional scale: Unbiased recursive partitioning-based stochastic model application. Agriculture, Ecosystems & Environment, 217, 99-110.

34. Weimer-Jehle W. (2016). Constructing consistent scenarios using cross-impact balance analysis. Stuttgart Research Center for Interdisciplinary Risk and Innovation Studies University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany.

35. Xystrakis, F., Psarras, T., & Koutsias, N. (2017). A process-based land use/land cover change assessment on a mountainous area of Greece during 1945–2009: signs of socio-economic drivers. Science of the Total Environment, 587, 360-370.

36. Zhang, Y., Wang, C., Xie, H., Zhang, J., & Wu, J. (2017). Analyzing spatial variations in land use/cover distributions: A case study of Nanchang area, China. Ecological Indicators, 76, 52-63.