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تأثیر حالت‌های احتمالی تغییر کاربری/پوشش زمین بر مؤلفه‌های سیمای سرزمین در آبخیز تالار | ||
| پژوهش های آبخیزداری | ||
| مقاله 9، دوره 32، شماره 1 - شماره پیاپی 122، فروردین 1398، صفحه 84-99 اصل مقاله (867.27 K) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2018.123624.1156 | ||
| نویسندگان | ||
| محسن ذبیحی1؛ حمیدرضا مرادی* 2؛ مهدی غلامعلی‌فرد3؛ عبدالواحد خالدی درویشان4 | ||
| 1دانشجوی دکتری علوم و مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس | ||
| 2دانشیار گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس | ||
| 3استادیار گروه محیط زیست، دانشکده‌ی منابع طبیعی، دانشگاه تربیت مدرس | ||
| 4استادیار گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس | ||
| چکیده | ||
| پژوهش حاضر با هدف بررسی و پیش‌بینی تغییرات سنجه‌های سیمای سرزمین در آبخیز تالار در استان مازندران برنامه‌ریزی شده است. نقشه‌های کاربری/پوشش زمین در سال‌های 1368، 1379 و 1393 با به‌کارگیری الگوریتم ماشین بردار پشتیبان تهیه و با استفاده از مدلساز تغییر سرزمین در حالت‌های مختلف تغییر کاربری/پوشش برای سال 1409 پیش‌بینی شد. توان انتقال و پیش‌بینی تغییرات به‌ترتیب با استفاده از روش‌های پرسپترون چندلایه و زنجیرهی مارکوف مدلسازی شد. سنجه‌های سیمای سرزمین شامل درصد پوشش سیمای سرزمین، تعداد لکه، تراکم لبه، تراکم لکه، شاخص بزرگ‌ترین لکه، شاخص شکل سیما، شاخص پراکندگی و مجاورت و نسبت چولیدگی لبه در سال‌های بررسی‌شده، وحالت‌های ممکن تغییر کاربری/پوشش زمین با استفاده از نرم‌افزار Fragstats استخراج و تغییرات آن بررسی شد. نتایج نشان داد که روند تغییرات سنجه‌های درصد پوشش سیمای سرزمین، تعداد لکه، تراکم لبه، تراکم لکه، شاخص بزرگ‌ترین لکه، و شاخص شکل سیما در سال‌های بررسی‌شده در کاربری‌های جنگل و مرتع کاهشی، و در سایر کاربری‌ها افزایشی است. مهم‌‌ترین عوامل مؤثر بر تغییر کاربری/پوشش در حالت‌های بررسی‌شده ارتفاع، فاصله از زمین‌های جنگلی و مرتعی و احتمال تجربی برای تغییر شناخته شد. میانگین افزایش تعداد لکه در حالت‌های تداوم روند فعلی تغییر کاربری، جنگل‌زدایی و توسعهی زمین‌های مسکونی به‌ترتیب 43/2، 8/9 و 7/9% بود. برای بهبود وضعیت سلامت آبخیز تالار پیشنهاد می‌شود مناطقِ مختلفِ نیازمند احیا با توجه تغییرات کاربری/پوشش ناصحیح اولویت‌بندی شوند، و در مناطقی که تغییر در حالت‌های تغییر کاربری/پوشش زمین در آن‌ها پیش‌بینی شد، با درنظرگرفتن شرایط آمایش سرزمین اقدام‌های پیش‌گیرانه و حفاظتی تعیین و انجام شود. | ||
| کلیدواژه‌ها | ||
| استان مازندران؛ پیش‌بینی کاربری/پوشش زمین؛ توسعه پایدار؛ مدل LCM؛ مدیریت سیمای سرزمین | ||
| عنوان مقاله [English] | ||
| Effects of Land Use/Land Cover Change Scenarios on Landscape Metrics on the Talar Watershed | ||
| نویسندگان [English] | ||
| Mohsen Zabihi1؛ Hamid Reza Moradi2؛ Mehdi Gholamalifard3؛ Abdulvahed Khaledi Darvishan4 | ||
| 1PhD Candidate, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Iran | ||
| 2Associate Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Iran | ||
| 3Assistant Professor, Department of the Environment Sciences, Faculty of Natural Resources, Tarbiat Modares University, Iran | ||
| 4Assistant Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Iran | ||
| چکیده [English] | ||
| The present study was planned to investigate and predict the landscape metrics on the Talar Watershed, the Province of Mazandaran. Land use/land cover (LULC) maps were produced using the support vector machine (SVM) algorithm for the years 1989, 2000, and 2014. The land change modeler (LCM) was applied for the prediction of LULC maps in different LULC change scenarios for 2030. Multi-layer Perceptron and the Markov chain methods were conducted for transition potential modelling and change prediction, respectively. Landscape metrics including the percentage of landscape (PLAND), the number of patches (NP), the edge density (ED), the patch density (PD), the largest patch index (LPI), the landscape shape index (LPI), the interspersion and juxtaposition index (IJI), and the perimeter-area fractal dimension (PAFRAC) were investigated and extracted using the Fragstats software in the studied years and the LULC change scenarios. Results demonstrated that the changes in the trend of PLAND, NP, ED, PD, LPI, and LSI were decreasing, and increasing in other land use systems during the considered years in forest, rangeland and another LULCs, respectively. Elevation, distance from forest, distance from rangeland areas, and the empirical likelihood of change were identified as the most important factors influencing the LULC change in the studied scenarios. Also, the average increase of NP was calculated at 43.2, 8.9, and 7.9 percent in continuing the current LULC change, deforestation, and residential area development scenarios, respectively. Prioritization of different areas that require restoration with respect to the incorrect LULC changes, and determination and implementation of the precautionary and protective measures in the areas with change prediction based on the studied LULC change scenarios, as well as considering land use planning conditions to improve the health of Talar Watershed by managers and planners are recommended. | ||
| کلیدواژه‌ها [English] | ||
| Land use/land cover prediction, landscape management, LCM, sustainable development, the Province of Mazandaran | ||
| مراجع | ||
|
Aguilera F, Valenzuela LM, Botequilha-Leitão A. 2011. Landscape metrics in the analysis of urban land use patterns: A case study in a Spanish metropolitan area. Landscape and Urban Planning. 99(3–4):226–238. Apan AA, Raine SR, Paterson MS. 2002. Mapping and analysis of changes in the riparian landscape structure of the Lockyer Valley catchment, Queensland, Australia. Landscape and Urban Planning. 59(1):43–57. Arekhi S, Fathizad H. 2014. Analyzing landscape degradation using landscape ecological metrics, remote sensing and GIS (Case study: Doiraj watershed, Ilam province. Iranian Journal of Rangeland and Desert Research. 21(3): 466–481. (In Persian). Asgarian A, Jabbarian Amiri B, Alizadeh Shabani A, Feghhi J. 2015. Assessing urban growth patterns in Sari using landscape ecology approach. Journal of Natural Environment (Iranian Journal of Natural Resources). 68(1(: 95–107. (In Persian). Boongaling CGK, Faustino-Eslava DV, Lansigan FP. 2018. Modeling land use change impacts on hydrology and the use of landscape metrics as tools for watershed management: The case of an ungauged catchment in the Philippines. Land Use Policy. 72: 116–128. Braimoh AK. 2006. Random and systematic land-cover transitions in northern Ghana. Agriculture, ecosystems and environment. 113(1–4): 254–263. Chen Y, Yu S. 2017. Impacts of urban landscape patterns on urban thermal variations in Guangzhou, China. International Journal of Applied Earth Observation and Geoinformation, 54: 65–71. Fathizad H, Safari A, Bazgir M, Khosravi GH. 2017. Evaluation of SVM with Kernel method (linear, polynomial, and radial basis) and neural network for land use classification. Iranian Journal of Rangeland and Desert Research. 23(4): 729–743. (In Persian). Feizizadeh B, Didehban Kh, Gholamnia Kh. 2016. Extraction of land surface temperature (LST) based on Landsat satellite images and split window algorithm (Study area: Mahabad catchment). Scientific-Research Quarterly of Geographical Data (SEPEHR). 25(98):171–181. (In Persian). Fiener P, Auerswald K, Van Oost K. 2011. Spatio-temporal patterns in land use and management affecting surface runoff response of agricultural catchments-A review. Earth-Science Reviews. 106(1–2): 92–104. Golshan M, Pirneia A, Ebrahimi P, Esmali Ouri A. 2014. Analysis of the effect of precipitation type on flow simulation in Talar and Khoramabad watershed. Geography and sustainability of Environment. 9: 51–64. (In Persian). Hassan MM. 2017. Monitoring land use/land cover change, urban growth dynamics and landscape pattern analysis in five fastest urbanized cities in Bangladesh. Remote Sensing Applications: Society and Environment.7: 69–83. Hosseini Vardei M,Salman Mahini A, Monavari SM,Kheirkhah Zarkesh MM. 2012. Using landscape metrics in cumulative effects assessment of road network on tree cover. Journal of Natural Environment (Iranian Journal of Natural Resources). 65(2): 139–152. (In Persian). Inkoom JN, Frank S, Greve K, Walz U, Fürst C. 2018. Suitability of different landscape metrics for the assessments of patchy landscapes in west Africa. Ecological Indicators. 85:117–127. Jiang W, Chen Z, Lei X, Jia K, Wu Y. 2015. Simulating urban land use change by incorporating an autologistic regression model into a CLUE-S model. Journal of Geographical Sciences. 25(7):836–850. Joorabian Shooshtari SH, Shayesteh K, Gholamalifard M, Azari M, López-Moreno JI. 2017. The role of landscape metrics and spatial processes in performance evaluation of GEOMOD (Case Study: Neka River Basin). Geography and sustainability of Environment. 7(24):63–80. (In Persian). Kang N, Sakamoto T, Imanishi J, Fukamachi K, Shibata S, Morimoto Y. 2013. Characterizing the historical changes in land use and landscape spatial pattern on the oguraike floodplain after the Meiji Period. Intercultural Understanding. 1: 11–16. Karami P, Mirsanjari M. 2018. Analysis of landscape degradation in the Hawizeh wetland by using remote sensing. Wetland Ecobiology. 10(1): 39–54. (In Persian). Kiyani V, Feghhi J. 2015. Investigation of Land Cover/Land Use Structure of Sefidrod watershed by landscape ecology metrics. Journal of Environmental Sciences and Technology. 17(65): 131–141. (In Persian). Leh MD, Matlock MD, Cummings EC, Nalley LL. 2013. Quantifying and mapping multiple ecosystem services change in West Africa. Agriculture, ecosystems & environment. 165: 6–18. McGarigal K, Cushman SA, Neel MC, Ene E. 2002. FRAGSTATS: spatial pattern analysis program for categorical maps. Megahed Y, Cabral P, Silva J, Caetano M. 2015. Land cover mapping analysis and urban growth modelling using remote sensing techniques in greater Cairo region-Egypt. ISPRS International Journal of Geo-Information. 4(3): 1750–1769. Mirzayi M, Riyahi Bakhtiyari A, Salman Mahini A, Gholamalifard M. 2013. Investigating the land cover changes in Mazandaran Province using landscape ecology’s metrics between 1984 – 2010. Iranian Journal of Applied Ecology. 2(4): 37–55. (In Persian). Munsi M, Areendran G, Joshi PK. 2012. Modeling spatio-temporal change patterns of forest cover: a case study from the Himalayan foothills (India). Regional environmental change. 12(3): 619–632. Nazarnezhad H, Hoseini M, Irani T. 2018. The use of landscape metrics in the evaluation of landscape structure changes in Gharesou watershed, Kermanshah. Journal of Geography and Environmental Hazards. 7(2), Doi:10.22067/geo.v7i2.66958. (In Persian). Nor ANM, Corstanje R, Harris JA, Brewer T. 2017. Impact of rapid urban expansion on green space structure. Ecological Indicators. 81: 274–284. Peng Y, Mi K, Qing F, Xue D. 2016. Identification of the main factors determining landscape metrics in semi-arid agro-pastoral ecotone. Journal of Arid Environments. 124: 249–256. Reddy CS, Singh S, Dadhwal VK, Jha CS, Rao NR, Diwakar PG. 2017. Predictive modelling of the spatial pattern of past and future forest cover changes in India. Journal of Earth System Science. 126(1): 8. Shi Y, Xiao J, Shen Y. 2008. Landscape pattern change and associated environmental implications in the Haihe River Basin, China. ISPRS J. Photogramm. Remote Sens. 37:569–574. Shooshtari, SJ, Gholamalifard M. 2015. Scenario-based land cover change modeling and its implications for landscape pattern analysis in the Neka Watershed, Iran. Remote Sensing Applications: Society and Environment. 1:1–19. Shooshtari, SJ, Shayesteh K, Gholamalifard M, Azari M, López-Moreno JI. 2018. Land cover change modelling in Hyrcanian forests, Northern Iran: a landscape pattern and transformation analysis perspective. Cuadernos de Investigación Geográfica. 44(2):743–761. Su S, Ma X, Xiao R. 2014. Agricultural landscape pattern changes in response to urbanization at ecoregional scale. Ecological indicators. 40:10–18. Sun B, Zhou Q. 2016. Expressing the spatio-temporal pattern of farmland change in arid lands using landscape metrics. Journal of Arid Environments. 124: 118–127. (In Persian). Talebi Amiri SH, Azari Dehkordi F, Sadeghi SH, Soofbaf SR. 2009. Study on landscape degradation in Neka Watershed using landscape metrics. Environmental Sciences. 23: 133–144. (In Persian). Tlapáková L, Stejskalová D, Karásek P, Podhrázská J. 2013. Landscape metrics as a tool for evaluation landscape structure–Case Study Hustopeče. European countryside. 5(1): 52–70. Yousefi S, Tazeh M, Mirzaee S, Moradi HR, Tavangar SH. 2014. Comparison of different classification algorithms in satellite imagery to produce land use maps (Case study: Noor city). Journal of RS and GIS for Natural Resources. 5(3):67–76. (In Persian). | ||
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