بررسی تغییرات کاربری اراضی با استفاده از رویکرد اکولوژی سیمای سرزمین (مطالعه موردی: حوزه‌ی سد زاگرس در گیلانغرب)
محورهای موضوعی : ارزیابی پی آمدهای محیط زیستیپریسا پیروزی نژاد 1 , مریم مروتی 2 , نوشین پیروزی نژاد 3
1 - دانشجوی کارشناسی ارشد ارزیابی و آمایش سرزمین، دانشکده کشاورزی و منابع طبیعی، دانشگاه اردکان، اردکان، ایران.
2 - دانشیار گروه علوم و مهندسی محیط زیست، دانشکده کشاورزی و منابع طبیعی، دانشگاه اردکان، اردکان، ایران. *(مسوول مکاتبات)
3 - کارشناس مسئول اداره مطالعات آبخیزداری استان کرمانشاه، کرمانشاه،ایران.
کلید واژه: توسعه کشاورزی, تغییرات کاربری اراضی, ارزیابی تغییرات, سد زاگرس, کرمانشاه.,
چکیده مقاله :
زمینه و هدف: حوزه آبخیز سد زاگرس در استان کرمانشاه در شهرستان‌های دالاهو، سرپل ذهاب، اسلام‌آباد غرب و گیلانغرب محصور است و در دهه گذشته تغییرات شدید کاربری اراضی را تجربه کرده است. هدف مطالعه، بررسی تغییرات کاربری اراضی با استفاده از سنجه¬های اکولوژی سیمای سرزمین، به علت تغییر جنگل¬های بلوط زاگرس و ارائه داده¬ها و نبود زمین کشاورزی و فرسایش خاک و سیلابی بودن منطقه بوده است. روش بررسی: در این مطالعه از تصاویر ماهواره لندست 8 در سال‌های 2010 و 2020 استفاده شد. پس از انجام پیش¬پردازش¬های لازم برای تصاویر، نمونه¬های تعلیمی به کمک تصاویر رنگی کاذب(FCC) و شاخص پوشش¬گیاهی(NDVI) شناسایی شدند. طبقه‌بندی به کمک 730 نقطه تعلیمی از طبقات کاربری کشاورزی، جنگل، مراتع و مناطق مسکونی به روش‌های شبکه عصبی -مصنوعی(ANN)، ماشین¬بردار پشتیبان(SVM) و تئوری حداکثر احتمال(Maximum Likelihood) انجام گرفت. سنجه‌های سیمای سرزمین در دو سطح کلاس و سیمای سرزمین به کار گرفته شد و تغییرات رخ‌داده در سیمای سرزمین کمی شد. پس از محاسبه تغییرات با استفاده زنجیرهMarkov پتانسیل تغییرات بین کاربری‌های مختلف برای سال 2030 به دست آمد. یافته¬ها: براساس نتایج، کاربری کشاورزی در سال 2010 مساحت 43/23933 هکتار داشت که به 09/25344 هکتار در سال 2020 افزایش پیدا کرد، که نشان‌دهنده غالبیت این کاربری در تغییرات رخ‌داده است. کاربری جنگل و مراتع روندی کاهشی داشتند. سنجه‌های سیمای سرزمین در حوزه نیز آشکارکننده تغییرات محسوس در سطح کلاس و سیمای سرزمین بود. متریک آنتروپی بی‌نظمی و آشفتگی در مرز کاربری‌های طبیعی مانند جنگل‌ها و مراتع از سال 2010 تا 2020 روندی افزایشی داشته است. سنجه تعداد لکه(NP) و سنجه پیوستگی(CONTAG) نشان دادند که تغییرات رخ‌داده در محدوده سد زاگرس به سمت تکه‌تکه-شدگی سیمای سرزمین و همچنین کاهش پیوستگی آن بوده است. بحث و نتیجه¬گیری: روند آینده تغییرات کاربری اراضی به سمت غالبیت کشاورزی و کاهش اراضی طبیعی میل خواهد کرد که لازم است دستگاه‌های اجرایی متولی کنترل بیشتری بر روی تخریب اراضی طبیعی حاشیه زمین‌های کشاورزی داشته باشند.
Background and Objective: The Zagros Dam watershed in Kermanshah Province is enclosed by the cities of Dalaho, Sarpol Zahab, Islamabad Gharb and Gilan Gharb and has experienced drastic land use changes in the last decade. The aim of the study was to investigate the changes in land use using land surface ecology measures, due to the change in Zagros oak forests and data provision, lack of agricultural land, soil erosion and flooding in the area. Material and Methodology: Landsat 8 satellite images from 2010 and 2020 were used in this study. After the necessary image pre-processing, educational patterns were identified using false-colour imagery (FCC) and vegetation index (NDVI). Classification was done using 730 training points from agricultural, forest, pasture and residential areas using Artificial Neural Network (ANN), Support Vector Machine (SVM) and Maximum Likelihood Theory. Land surface measurements were used at two levels of class and landscape, and the changes that occurred in the landscape were quantified. After calculating the changes using the Markov chain, the potential of changes between different land uses was obtained for the year 2030. Findings: ¬ According to the results, the area of agricultural land use in 2010 was 23,933.43 hectares, which increased to 25,344.09 hectares in 2020, indicating the dominance of this land use in the changes that occurred. Forest and pasture land use showed a decreasing trend. Field measurements of the land surface also revealed significant changes in the class level and the landscape. The entropy metric of disorder and disturbance at the boundary of natural land uses such as forest and pasture showed an increasing trend from 2010 to 2020. The measure of the number of patches (NP) and the measure of continuity (CONTAG) showed that the changes that occurred in the area of the Zagros Dam were towards the fragmentation of the landscape and also towards the reduction of its continuity. Discussion and Conclusion: The future trend of land use change will be towards the predominance of agricultural land use and the reduction of natural land use, so it is necessary for the relevant executive bodies to have more control over the destruction of natural land at the edge of agricultural land.
1. Darvish Sefat, A., Bagheri, M., Ghorbani, M., Zahedi Amiri, G. (2018). 'Spatial forest disturbance modeling using landscape metrics in Sarvelat protected area of Iran', Forest and Wood Products, 71(1), pp. 23-33. doi: 10.22059/jfwp.2018.232486.847. (In Persian)
2. Yousefi, S., Mirzaee, S., Zeini Vand, H. (2013). Investigation deforestation trends in Zagros mountain with using GIS and RS (Case study: Marivan). Journal of Applied RS & GIS Techniques in Natural Resource Science, Vol.4, Issue.2: 15- 23. (In Persian)
3. Ahmadi, A., javanshir, K., Ahmadi, H., Mozaffarian, V. (2003). Investigating vegetation in relation to geomorphological units in Barun region of West Azerbaijan. Iranian Journal of Range and Desert Research, Vol. 10, No. 2, pp. 169- 192. (In Persian)
4. Alimohammadi, A., Matkan, A., Ziaeean, P., Tabatabaii, H. (2009). Comparison of methods based pixel classification, object-based and decision tree in forest type mapping using remote sensing data (Case study: Forest Astara). Journal of Applied Researches in Geographical Sciences, Vol.9, Issue. 13, pp. 7- 26. (In Persian)
5. Hasanzad Navrodi, I., Seyyedi, N., Seifolahian, H. (2009). Evaluation of quantitative and qualitative forest stands changes during a Period of forest management Plan (case study: Janbe sara district-Guilan). Iranian Journal of Forest, Vol.1, Issue.4: 301- 311. (In Persian)
6. Ghanbari, F., Shataee, Sh. (2011). Investigation on Forest Extend Changes Using Aerial Photos and ASTER Imagery (Case Study: Border Forests in South and Southwest of Gorgan City). Wood & Forest Science and Technology, Vol.17, Issue.4: 1- 18. (In Persian)
7. Abdolahi, H., Shataee Joybari, Sh. (2012). Comparative evaluation of IRS-P6-LISS-III and LISS IV images for canopy cover mapping of Zagros forests (Case Study: Javanroud Forests). Wood & Forest Science and Technology, Vol.19, Issue. 1, pp. 43- 60. (In Persian)
8. Shayesteh, A., Karimzadeh, H., Soltani, S., Sarhadi, A. (2008). Investigating the relationship between land use change and sediment production in the Manderjan watershed of Isfahan. Geomatic conference, May 2008. (In Persian)
9. Hassanpour, P., Sayyahnia, R., Esmaeilzadeh, H. (2020). Ecological structure assessment of urban green space using the landscape approach(case study: Tehran’s 22nd district). Environmental Sciences, Vol. 18, Issue. 1, pp. 187- 202. (In Persian)
10. Hosseine, M., Mostafazadeh, R., Nazarnejad, H. (2019). Analysis of Land Use Change in Balanjchai Watershed (Urmia) Using Landscape Metrics. Geography and Development Iranian Journal, Vol.17, Issue. 54, pp. 75- 89. (In Persian)
11. Castillo, E.M., García-Martin, A., Aladrén, L.A.L., de Luis, M. (2015). Evaluation of forest cover change using remote sensing techniques and landscape metrics in Moncayo Natural Park (Spain). Applied Geography, Vol.62, pp. 247- 255.
12. Plexidaa, S.G., Sfougaris, A.I., Ispikoudis, I.P., Papanastasis, V.P. (2014). Selecting Landscape metrics as indicators of spatial heterogeneity- A Comparison among Greek Landscapes. International Journal of Applied Earth observation and Geoinformation, Vol.26, pp. 26- 35.
13. Karami, A. (2012). Preparation of water erosion map using object-oriented techniques in remote sensing (case study: Lamard region of Fars province). Master's Thesis of Watershed Engineering Sciences, Faculty of Agriculture and Natural Resources, Hormozgan University. 98pp. (In Persian)
14. Arekhi, S., Momeni Taramsari, M. (2015). Envi 5 software video tutorial. First edition, Golestan University Press. 526 pp. (In Persian)
15. Saedpanah, M., Amanoallahi, J., Ghorbani, F. (2021). Investigating the effect of land use changes on land surface temperature in cold and semi-arid areas (Case study: Central Zone of Sanandaj City). Journal of Natural Environment, Vol.74, Issue. 1, pp. 69- 82. (In Persian)
16. Ahmad, A., Quegan, Sh. (2012). Analysis of maximum likelihood classification on multispectral data. Applied Mathematical Sciences, Vol.6, No.129, pp. 6425- 6436.
17. Sisodia, P.S., Tiwari, V., Kumar, A. (2014). Analysis of supervised maximum likelihood classification for remote sensing image. Recent Advances and Innovations in Engineering (ICRAIE): IEEE, pp. 1- 4.
18. Vapnik, V.N. (1995). The Nature of Statistical Learning Theory (New York :Springer Verlag ).
19. Karami, A., Feghhi, J. (2012). Investigation of Quantitative metrics to protect the landscape in land use by sustainable pattern (Case study: Kohgiluyeh and Boyer Ahmad). Journal of Environmental Studies, Vol.37, Issue. 4, pp. 79- 88. (In Persian)
20. Shayesteh, K., Mohammadyary, F. (2018). Evaluation and Prediction of Changes in Vegetation Using Landscape Metrics and Markov Model (Case Study: Hamadan). Geography and Development Iranian Journal, Vol.16, Issue. 53, pp. 85- 104. (In Persian)
21. Kakehmami, A., Moameri, M., Ghorbani, A., Ghafari, S. (2020). Analysis of land use/ cover changes in Ardabil province using landscape metrics. Journal of Rs and Gis for natural Resources, Vol.11, Issue. 3, pp. 68- 86. (In Persian)
22. Zhang, L., Wu, J., Zhen, Y., Shu, J. (2004). A GIS-based Gradient Analysis of Urban Landscape Pattern of Shanghai Metropolitan Area, China. Journal of Landscape and Urban Planning, Vol.69, Issue. 1, pp. 1- 16.
23. Herold, M., Couclelis, H., Clarke, K. C. (2005). The role of spatial metrics in the analysis and modeling of urban land use change. Journal of Computers, Environment and Urban Systems, Vol.29, Issue. 4, pp. 369– 399.
24. Azimi Najarkolaei, A., Jamali, A., Hosseini, Z. (2017). Comparing the accuracy of time series classification of Landsat images in monitoring land use change. Journal of Rs and Gis for natural Resources, Vol.8, Issue. 2, pp. 33- 47. (In Persian)
25. Ahmadpour, A., Solaimani, K., Shokri, M., Ghorbani, J. (2011). Comparison of three common methods in supervised classification of satellite data for vegetation studies. Journal of RS and GIS for Natural Resources, Vol.2, No.2, pp. 69- 81. (In Persian)
26. Niyazi, Y., Ekhtesasi, M., Maleki Nejad, H., Morshedi, J., Hoseyni, Z. (2011). Comparibson Between two Classification Methods of Maximum likelihood and Artificial Neural Network for Providing Land use Maps Case Study: Ilam Dam Area. Geography and Development Iranian Journal, Vol.8, Issue. 20, pp. 119- 132. (In Persian)
27. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Bray, M. and Islam, T. (2012). Selection of classification techniques for land use/land cover change investigation. Advances in Space Research, Vol.50, Issue.9, pp. 1250- 1265.
28. Fathi Zad, H., Fallah Shamsi, R., Mahdavi, A., Arekhi, S. (2015). Comparison of two classification methods of maximum probability and artificial neural network of fuzzy Art map in making Range land cover maps (case study: Range land area of Doviraj area, Dehloran). Iranian Journal of Range and Desert Research, Vol.22, Issue. 1, pp. 59- 72. (In Persian)
29. Bolstad, P.V., Lillesand, T.M. (1991). Rapid maximum likelihood classification Photogram. Engineering Remote Sensing. Vol.57, Issue. 1, pp. 67- 74.
30. Meng, Q., Fu, B., Tang, X., Ren, H. (2008). Effect of land use on phosphorus loss in the hilly area of the Loess Plateau, China. Environmental Monitoring and Assessment, Vol. 139, pp.195-204
31. Bazgir, M., Hydari, M., Zeynali, N., Kohzadean, M. (2020). Effect of Land Use Change from Forest to Agriculture and Abounded of Agriculture on Soil Physical and Chemical Properties in Zagros Forest Ecosystem. Journal of Environmental Sciences and Technology, Vol. 22, Issue. 1, pp. 201- 214. (In Persian)
32. Mardani Yaghouti, F., Khanmohammadi, M., Karami, P. (2019). Investigating the Quantitative Trend of Land Changes in Kermanshah Province(Case Study: Gharesou and Mereg Watershed (in years 1984, 2000, and 2016)). Journal of Environmental Sciences and Technology, Vol.21, Issue. 7, pp. 161- 176. (In Persian)
33. Rahimi Dehcheraghi, M., Erfanzadeh, R., Joneidi Jafari, H. (2014). Impact of land use changes from rangeland to rain-fed land on soil organic matter and nitrogen in Kermanshah and Kordestan provinces (Case study: Lille, Ravansar and Razavr watersheds). Journal of Rangeland, Vol.7, Issue. 2, pp. 167- 158. (In Persian)
34. Karami, P. (2021). Identifying and Analyzing Distribution of Habitat's Hotspots of Salient Vertebrates from Landscape Perspective in Kermanshah Province. PhD in environmental studies. Faculty of Natural Resources and Environment, Malayer University. Hamedan. Iran. 421pp. (In Persian)
35. Heshmati, M., Gheitouri, M. (2018). Land-use Change; Achilles heel to Overcoming the Environmental Crisis, Process and Impacts. Geography and Sustainability of Environment, Vol. 8 Issue. 26, pp. 89- 105. (In Persian)
36. Salarian, F., Tatian, M., Ghanghermeh, A., Tamartash, R. (2021). Modeling land cover changes in Golestan province using land change modeler (LCM). Journal of Rs and Gis for natural Resources, Vol.12, Issue. 4, pp. 47- 70. (In Persian)
37. Newton, A. C. (2007) Biodiversity and Conservation in Fragmented Forest Landscapes. CABI Press.
38. Mirakhorlou, Kh., Akhavan, R. (2008). Investigation on boundary changes of northern forests of Iran using remotely sensed data. Iranian Journal of Forest and Poplar Research, Vol.16, No.1, pp. 139- 148. (In Persian)
39. Ahmadi, M., Narangifard, M. (2015). Quality assessment and detection of forest area changes using satellite images (Case study: Rustam, Fars). Journal of Rs and Gis for natural Resources, Vol.6, Issue. 3, pp. 87- 100. (In Persian)
40. Mirzaei Mossivand, A., Ghorbani, A., Keivan Behjou, F. (2018). Land use/cover change detection using Landsat and IRS imagery: A case study, Khalkhal County. Geographic Space, Vol.17, Issue. 60, pp. 101- 116. (In Persian)
41. Ramezanpour, H., Rasooli, N. (2015). Effects of Land Use Changes and Parent Materials on Some Soil Properties in Guilan Province. Iranian Journal of Soil Research, Vol.29, No.2, pp. 221- 231. doi: 10.22092/ijsr.2015.102215. (In Persian)
42. Jafari, M., Sarmadian, F. (2002). Soil science and soil taxonomy. Tehran University Press. Tehran, Iran.
43. Khosravian, M., Entezari, A., Rahmani, A., Baaghide, M. (2018). Monitoring the Disturbance of Lake District Water Level Changes Using Remote Sensing Indices. Hydrogeomorphology, Vol.4, Issue. 13, pp. 99- 120. (In Persian)
44. Mijani, N., Hamzeh, S., Karimi Firozjaei, M. (2019). Quantifying the effect of surface parameters and climatic conditions on land surface temperature using reflective and thermal remote sensing data. Journal of Rs and Gis for natural Resources, Vol.10, Issue. 1, pp. 36- 59. (In Persian)
45. Georgescu, M., Moustaoui, M., Mahalov, A., Dudhia, J. (2011). An alternative explanation of the semiarid urban area “oasis effect”. Journal of Geophysical Research: Atmospheres, Vol.116, pp. 1- 13.
