ارزیابی تغییرات کاربری اراضی در حوضه آب‌خیز رودخانه تجن با تکیه بر سنجه‌های سیمای سرزمین
محورهای موضوعی :
سیستم اطلاعات جغرافیایی
فاطمه رجایی
1
,
عباس اسماعیلی ساری
2
,
عبدالرسول سلمان ماهینی
3
,
مجید دلاور
4
,
علی رضا مساح بوانی
5
1 - دانش‌جوی دکتری گروه محیط‌زیست، دانشکده منابع طبیعی دانشگاه تربیت مدرس
2 - استاد گروه محیط‌زیست، دانشکده منابع طبیعی دانشگاه تربیت مدرس *(مسوول مکاتبات)
3 - دانشیار گروه محیط‌زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان
4 - استادیار گروه مهندسی منابع آب، دانشکده کشاورزی، دانشگاه تربیت مدرس
5 - دانشیار، گروه علوم و مهندسی آب، پردیس ابوریحان، دانشگاه تهران
تاریخ دریافت : 1394/02/16
تاریخ پذیرش : 1395/03/26
تاریخ انتشار : 1399/01/01
کلید واژه:
مدل‌ساز تغییر سرزمین (LCM),
سنجه‌های سیمای سرزمین,
تغییرات کاربری اراضی,
حوزه آب‌خیز تجن,
چکیده مقاله :
مقدمه: تغییرات کاربری اراضی و تخریب پوشش‌های طبیعی سبب اختلال در اکوسیستم و کاهش تنوع زیستی می‌شود. کاهش جنگل های هیرکانی ، متعلق به دوره ژوراسیک از ارزش مندترین جنگل های جهان، یکی از مهم ترین مشکلات در سال های اخیر است.روش تحقیق: در پژوهش حاضر با استفاده از تصاویر ماهواره‌ای به بررسی تغییرات کاربری اراضی و تجزیه‌وتحلیل سیمای سرزمین در دوره‌های زمانی مختلف، شامل سال‌های 1984، 2001 و 2010 پرداخته شد. جهت بررسی چگونگی روند تغییرات کاربری و سیمای سرزمین در افق زمانی آینده از مدل‌ساز تغییر سرزمین (LCM) استفاده شد. سنجه‌های سیمای سرزمین در نرم‌افزار 2/4 FRAGSTATS استخراج شدند.نتایج و بحث: نتایج نشان می‌دهد که جنگل، کاربری غالب (72 درصد از مساحت منطقه در سال 1984 و 46 درصد در سال 2040) در منطقه موردمطالعه است. در سال 1984 مساحت جنگل‌ها 4/8 برابر کاربری کشاورزی بود و این میزان به 8/1 برابر در سال 2040 خواهد رسید. شاخص بزرک ترین لکه (LPI) نشان داد اراضی جنگلی پوشش غالب در کل دوره است. هم چنین شاخص نزدیکی (PROX) در کاربری کشاورزی و مرتع در دوره 1984-2010 روند افزایشی داشته و این میزان در سال 2040 افزایش بیش تری خواهد یافت. هم چنین افزایش سنجه تراکم حاشیه (ED) در طی دوره آینده در هر سه کاربری مرتع، جنگل و کشاورزی نشان می دهد که حوضه تجن خیلی متفاوت‌تر از حال حاضر خواهد شد . این نتایج می‌توانند دیدگاه‌هایی در جهت اولویت‌بندی تصمیمات ملی و منطقه ای با هدف کاهش تخریب جنگل ها در اختیار مدیران قرار دهد.
چکیده انگلیسی:
Introduction: Land cover and its configuration in the landscape are crucial components in the provision of biodiversity and ecosystem services. Hyrcanian forests have a long history (arising in the Jurassic Period) and are among the world's most valuable forests; the decline in the Hyrcanian forests is one of the most serious problems of recent years. Material & Method: This study aims at comparing multi-temporal land use and landscape pattern analysis using satellite images from 1984, 2001 and 2010. Land use and spatial structures were predicted for future time horizons in the Tajan Watershed by land change modeler (LCM). Also, the landscape patterns were calculated by FRAGSTATS 4.2. Result & Discussion: The results show that forest was the dominant land cover (72% of area in 1984 and 46% in 2040) in the study area. The total area of forest was 8/4 times higher than the agriculture land cover in 1984 and 1.8 times in 2040. The Largest patch Index (LPI) shows forest lands as dominant cover in the whole period. Also proximity index (PROX) in agriculture and pasture land use increase during 1984 to 2040. The Edge density (ED) will increase in the future for three land uses. The edge density will increase at forest land use from 2010 to 2040. An informed vision on past, present and future forest area dynamics may help guide and prioritize international decisions aimed at reducing forest loss.
منابع و مأخذ:
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Wei, W., Chen, L., Fu B., Chen, J., 2010. Water Erosion Response to Rainfall and Land Use in Different Drought-Level Years in a Loess Hilly Area of China, Catena, 81 (1), 24-31.
Xiao, H., Ji, W., 2007. Relating landscape characteristics to non-point source pollution in mine Waste-located watersheds using geospatial techniques, Journal of Environmental Management, 82, 111–119.
McGarigal, K., Marks, B. J., 1995. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Port land, ORGen. Tech. Rep. PNW-GTR-351,122pp.
Congalton, R. G., 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment Journal, 37, 35–46.
Abdullah, S. A., Nakagoshi, N., 2006.Changes in landscape spatial pattern in the highly developing
Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., et al., 2005. Global consequences of land use. Science, 309 (5734), 570–574.
Saura, S., Estreguil, C., Mouton, C., & Rodríguez-Freire, M., 2011. Network analysis to assess landscape connectivity trends: Application to European forests (1990–2000). Ecological Indicators, 11(2), 407–416.
Ovalle, C., Del Pozo, A., Casado, M. A., Acosta, B., & de Miguel, J. M., 2006. Consequences of landscape heterogeneity on grassland diversity and productivity In the Espinal agroforestry system of Central Chile. Landscape Ecology, 21(4), 585–594.
state of Selangor, peninsular Malaysia. Landsc. Urban Plan, 77, 263–275.
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Turner, B. L., Lambin, E. F., Reenberg, A., 2007. The emergence of land change science for global environmental change and sustainability. Proceedings of the National Academy of Sciences of the United States of America, 104(52), 20666–20671.
Talebi SH., Azari dehkordi F., Sadeghi H., 2001. Analysis of landscape degradation Neckar watershed using landscape ecology measures. Science Environmental Journal, 6(3), 133-144.
Sheikh Goudarzi, M., Alizadeh Shabani, A., Salman Mahini, R., 2011. Survey of land cover / land use change trends in Korgarood watershed using landscape metrics. Iranian Journal of Natural Resources, 64 (4), 431-44 (In Persian).
Wu, J. G., Hobbs, R., 2002. Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landscape Ecological, 17, 355–365.
Kamyab H.R., Salman Mahini R., 2012. Temporal Spatial Patterns of Landscape Changes and Urban Development (Case Study: Gorgan). Journal of RS and GIS in Natural Resources Sciences, 2, 60-6 (In Persian)..
UN, 2012. Probabilistic Population Projections based on the World Population Prospects: The 2012 Revision. United Nations Department of Economic and Social Affairs, Population Division, Population Estimates and Projections Section.
Gutierrez-Velez, V. H., de Fries, R.S., Pinedo-Vasquez, M., Uriarte, M., Padoch, C., Baethgen, W., Fernandes, K., Lim, Y., 2011. High-yield oil palm expansion spares land at the expense of forests in the Peruvian Amazon. Environmental Research Letters. 6 (044029), 5.
Vafaee, S., Darwish sefat., M, 2013. Monitoring and Predicting Spatial Changes in Land Use Using the LCM Model (Case Study: Marivan Region). Iranian Forest Journal, Iranian Forestry Association.. 3, 323-336 (In Persian). .
Yousefi, P., Moradi, H., Hosseini, H., Mirzaei, S, 2011. Detecting land use changes using ETM + and TM images. Remote Sensing and Geographic Information Systems in Natural Resources, 2 (3), 97 – 105 (In Persian).
Shushtari., Sh., 2011. Modeling Land Use Changes in the Neka Watershed Using LCM. M.Sc., Faculty of Natural Resources, Tarbiat Modares University, 126 pages (In Persian).
Kelarestaghi, A., Jafarian Jeloudar, Z., 2011. Land use /cover change and driving force analyses in parts of northern Iran using RS and GIS techniques. Arabian Journal of Geo sciences, 4, 401–411.
Emadodin, I (2008). Human-induced soil degradation in Iran. Ecosystem services workshop, Salzau Castle, 13 – 15 May, Kiel, Northern Germany.
Paudel, S., and Yuan, F., 2012. Assessing landscape changes and dynamics using patch analysis and GIS modeling. International Journal of Applied Earth Observation and Geoinformation, 16, 66–76.
Eastman, J.R., 2006. IDRISI Andes. Guide to GIS and Image Processing, Clark Labs, Clark University, Worcester, MA, 1-327.
Verburg, P. H., Kok, K., Pontius J. r, R. Veldkamp, A., 2006. Modelling Land-Use and Land- Cover Change. In Lambin, E. F. and Geist, H., eds., Land-Use and Land-Cover Change: Local Processes, Global Impacts, Global Change - The IGBP Series, pp. 117–135, Berlin; New York (Springer).
Valclav.k, T., Rogan, J., 2009. Identifying trends in land use/land cover changes in the context of post-socialist transformation in Central Europe: A case study of the greater Olomouc region, Czech Republic. GIScience & Remote Sensing, 46 (1), 54–76.
Schulz, J. J., Cayuela, L., Echeverria, C., Salas, J., Rey Benayas, J. M., 2010. Monitoring land cover change of the dryland forest landscape of Central Chile (1975–2008). Applied Geography, 30 (3), 436–447.
Pontius Jr., R.G., Cornell, J.D., Hall, C.A.S., 2001. Modelingthespatial pattern ofland-usechange with GEOMOD2: application and validation for Costa Rica. Agric. Agriculture, Ecosystems & Environment Journal, 85, 191–203.
Soares Filho, B. S., Goutinho Cerqueira, G., Lopes Pennachin, C., 2002. DINAMICA—a stochastic cellular automata model designed to simulate the land scape dynamics in an Amazonian colonization frontier. Ecological Modeling, 154, 217–235.
Mohammadi, J., Shataee, S., 2010. Possibility investigation of tree diversity mapping using Landsat ETMþ data in the Hyrcanian forests of Iran. Remote Sensing of Environment, 114, 1504–1512.
Masoudiyan, M., Falahiyan, F., Nejadsattari, T., Metaji, A. and Khavarinejad, R., 2010. Epilitic diatoms in Tajan River, Mazandaran province. Biological Knowledge Iran, 4, 57-66.
Rozenstein, O., Karnieli, A., 2011. Comparison of methods for land use classification incorporating remote sensing and GIS inputs. Applied Geography, 31(2), 533–544.
Salman Mahini, A., Fazli, H., Kamyab, H., Fonderski, F., et al. 2011. Zoning and Determination of Ecological Sensitivity Degree of Coastal Areas, Environmental Protection Agency, 231 p (In Persian).
Bakr, N., Weindorf, D.C., Bahnassy, M. H., Marei, S. M., El Badawi, M. M., 2010. Monitoring land cover changes in a newly reclaimed area of Egypt usingmulti-temporalLandsatdata. Applied Geography, 30, 592–605.
Eastman, J.R., 2012. IDRISI Help System. Accessed in IDRISI Selva 17.02. Worcester, MA: Clark University.
O’Neill, R.V., Krummel, J.R., Gardner, R.H., Sugihara, G., Jackson, B., DeAngelis, D.L., Graham, R. L., 1988. Indices of landscape pattern. Landscape Ecological,1 (3), 153–162.
Arkhi, s., 2015. Application of Landscape Metrics in Evaluation of Land Use Changes Using GIS Remote Sensing Case Study: Dehloran Desert Area. Geography and Development, 40, 68-59 (In Persian).
Alberti M., Booth D., Hill K., Coburn B., Avolio C., Coe S., Spirandelli D., 2007. The impact of urban patterns on aquatic ecosystems: an empiricalanalysis on Pugetlowland sub-basins, Landscape Urban Plan, 80 (4), 345–361.
Hao, F., Zhang, X., Wang X., Ouyang, W., 2012. Assesment the Relationship between Landscape Patterns and Nonpoint Source Pollution in the Danjiankou Reservoir Basin in China, Journal of the American Water Resources Association, 1, 1-16.
Wei, W., Chen, L., Fu B., Chen, J., 2010. Water Erosion Response to Rainfall and Land Use in Different Drought-Level Years in a Loess Hilly Area of China, Catena, 81 (1), 24-31.
Xiao, H., Ji, W., 2007. Relating landscape characteristics to non-point source pollution in mine Waste-located watersheds using geospatial techniques, Journal of Environmental Management, 82, 111–119.
McGarigal, K., Marks, B. J., 1995. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Port land, ORGen. Tech. Rep. PNW-GTR-351,122pp.
Congalton, R. G., 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment Journal, 37, 35–46.
Abdullah, S. A., Nakagoshi, N., 2006.Changes in landscape spatial pattern in the highly developing
Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., et al., 2005. Global consequences of land use. Science, 309 (5734), 570–574.
Saura, S., Estreguil, C., Mouton, C., & Rodríguez-Freire, M., 2011. Network analysis to assess landscape connectivity trends: Application to European forests (1990–2000). Ecological Indicators, 11(2), 407–416.
Ovalle, C., Del Pozo, A., Casado, M. A., Acosta, B., & de Miguel, J. M., 2006. Consequences of landscape heterogeneity on grassland diversity and productivity In the Espinal agroforestry system of Central Chile. Landscape Ecology, 21(4), 585–594.
state of Selangor, peninsular Malaysia. Landsc. Urban Plan, 77, 263–275.
