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جلد 7 شماره 1 صفحات 121-144 برگشت به فهرست نسخه ها
رویه یادگیری برمبنای نمونه وزنی تشابه برای مدل‌سازی پتانسیل انتقال پوشش اراضی و کاربرد آن در سند طراحی پروژه REDD
کوشا پارسامهر، مهدی غلامعلی فرد*، یحیی کوچ
دانشکده منابع طبیعی، دانشگاه تربیت مدرس
چکیده:   (1295 مشاهده)
کاهش انتشارات ناشی از جنگل‌زدایی و تخریب جنگل (Reducing Emissions from Deforestation and Forest Degradation (REDD))، راهکاری برای تعدیل تغییرات اقلیمی است که به‌منظور کاهش شدت جنگل‌زدایی و انتشار گازهای گلخانه‌ای به‌کار گرفته می‌شود. در چند دهه­ی اخیر تغییرات شدید کاربری اراضی در استان مازندران باعث کاهش میزان چشمگیری از جنگل‌های هیرکانی شده است. تحقیق حاضر بر اساس اهداف پروژه‌های REDD، به بررسی تغییرات پوشش جنگل در محدوده‌ای از بخش‌های کجور و مرزن آباد در استان مازندران با استفاده از تصاویر ماهواره‌ای لندست متعلق به سال‌های 1363، 1379 و 1393 پرداخته است. در این مطالعه، برای اولین بار در ایران با استفاده از رویه یادگیری برمبنای نمونه وزنی مشابهت، مدل‌سازی تغییرات پوشش جنگل صورت گرفت و به‌منظور اعتبارسنجی از آماره­های مشخصه عملکرد نسبی، نسبت موفقیت به هشدار خطا و عدد شایستگی استفاده شد. در پایان با استفاده از روش‌شناسی استاندارد کربن اختیاری میزان انتشار گاز CO2 برای 30 سال آینده (تا سال 1423) محاسبه گردید. نتایج نشان داد که به ترتیب طی سال‌های 1379-1363 و 1393-1379 حدود 4008 و 3635 هکتار پوشش جنگل تخریب شده است. نتایج اعتبارسنجی نشان داد که میزان مشخصه عملکرد نسبی برابر با 95/0، عدد شایستگی 26 درصد و نسبت موفقیت به هشدار خطا 82 درصد بیانگر صحت بالای مدل می‌باشد. در نهایت نتایج اجرای پروژه REDD نشان داد که تحت سناریو خط‌مبنا،  tCO2e705336 طی 30 سال آینده به اتمسفر انتشار خواهد یافت که با اجرای پروژه REDD می‌توان از انتشار tCO2e 91/491697 جلوگیری نمود. با توجه به افزایش روند تخریب جنگل‌های هیرکانی و نقش مهم آنها در تعدیل تغییرات اقلیمی، با استفاده از روش‌شناسی تحقیق حاضر می‌توان تغییرات پوشش اراضی و تأثیر پروژه‌های REDD در میزان کاهش انتشار گازهای گلخانه‌ای را برآورد و پیش‌بینی نموده و در سند طراحی پروژه‌های مکانیسم توسعه پاک در کشور استفاده نمود.  .
واژه‌های کلیدی: انتشار کربن، پروژه REDD، جنگل‌زدایی، رویه یادگیری برمبنای نمونه وزنی مشابهت، استان مازندران
متن کامل [PDF 2455 kb]   (361 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: سنجش از دور
دریافت: 1396/11/2 | پذیرش: 1397/1/29 | انتشار: 1398/3/31
فهرست منابع
1. [1] A. Bahrami, I. Emadodin, M. Ranjbar Atashi, and H. R. Bork,"Land use change and soil degradation: a case study, north of Iran", Agriculture and Biology Jornal of North America, Vol. 1, pp. 600-605, 2010.
2. [2] A. M. Yanai, P. M. Fearnside, P. M. L. D. A. Graca, and E. M. Nogueira,"Avoided deforestation in Brazilian Amazonia: simulating the effect of the Juma sustainable development reserve", Forest Ecology and Management, Vol. 282, pp. 78-91, 2012. [DOI:10.1016/j.foreco.2012.06.029]
3. [3] B. Blom, T. Sunderland, and D. Murdiyarso," Getting REDD to work locally: lessons learned from integrated conservation and development projects", Journal of Environmental Science & Policy, Vol.13, pp. 164-172, 2010. [DOI:10.1016/j.envsci.2010.01.002]
4. [4] Climate Change Newsletter, provided by Iran's climate change office, No. 2, 2004.
5. [5] C. O. Wilson, and Q. Weng,"Simulating the impacts of future land use and climate changes on surface water quality in the Des Plaines River watershed, Chicago Metropolitan Statistical Area, Illinois", Science of the Total Environment, Vol. 409, pp. 4387-4405, 2011. [DOI:10.1016/j.scitotenv.2011.07.001]
6. [6] D. D. Khoi, and Y. Murayama,"Forecasting areas vulnerable to forest conversion in the Tam Dao National Park Region, Vietnam", Journal of Remote Sensing, Vol. 2, pp. 1249-1272, 2010. [DOI:10.3390/rs2051249]
7. [7] D. K. Lee, C. Park, and D. Tomlin,"Effects of land-use-change scenarios on terrestrial carbon stocks in South Korea", Landscape and Ecological Engineering, Vol. 1, pp. 1-13, 2013. [DOI:10.1007/s11355-013-0235-6]
8. [8] F. L. O Godoy, and E. H. M. Rojas,"Modeling deforestation to REDD+ project: case study in Alto Mayo protected forest, San Martin region, Peru", presented at Proceeding of simposio brasileiro de sensoriamento remoto, Brazil, 2013.
9. [9] F. Sangermano, J. R. Eastman, and, H. Zhu,"Similarity weighted instance‐based learning for the generation of transition potentials in land use change modeling", Journal of Transactions in GIS, Vol. 14, pp. 569-580, 2010. [DOI:10.1111/j.1467-9671.2010.01226.x]
10. [10] F. Sangermano, J. Toledano, and J. R. Eastman,"Land cover change in the Bolivian Amazon and its implications for REDD+ and endemic biodiversity", Journal of Landscape ecology, Vol. 27, pp. 571-584, 2012. [DOI:10.1007/s10980-012-9710-y]
11. [11] Global Land Cover facility (GLCF), http://glcf.umd.edu.
12. [12] G. R. Pontius, and L. C. Schneider,"Land-cover change model validation by an ROC method for the ipswich watershed Massachusetts, USA", Journal of Agriculture Ecosystems and Environment, Vol. 85, pp. 239-284, 2001. [DOI:10.1016/S0167-8809(01)00187-6]
13. [13] G. Vieilledent, C. Grinand, and R. Vaudry,"Forecasting deforestation and carbon emissions in tropical developing countries facing demographic expansion: a case study in Madagascar", Journal Ecology and Evolution, Vol. 3, pp. 1702-1716, 2013. [DOI:10.1002/ece3.550]
14. [14] H. G. Roy, D. M. Fox, and K. Emsellem,"Predicting Land Cover Change in a Mediterranean Catchment at Different Time Scales ", Journal of Computational Science and Its Applications, Vol. 8582, pp. 315-330, 2014. [DOI:10.1007/978-3-319-09147-1_23]
15. [15] H. J. Albers, and E. J. Z. Robinson,"Reducing emissions from deforestation and forest degradation", Encyclopedia of Energy, Natural Resource and Environmental Economics, Vol. 2, pp.78-85, 2013. [DOI:10.1016/B978-0-12-375067-9.00112-1]
16. [16] H. R. Kamyab, and A. Salmanmahiny,"Modeling Deforestation Using Logistic Regression And Artificial Neural Network in Golestan Province, Iran", International Geoinformatics Research and Development Journal, Vol.3, 2012.
17. [17] Available: http://www.aftabir.com/news/view/2007/jun/30/c4c1183190628_social_enviroment_jungle.php, 2014.
18. [18] J. F. Mas, M. Kolb, M. Paegelow, M. T. Camacho Olmedo, and T. Houet,"Inductive pattern-based land use/cover change models: a comparison of four software packages", Journal of Environmental Modelling & Software, Vol. 51, pp. 94-111, 2014. [DOI:10.1016/j.envsoft.2013.09.010]
19. [19] J. O. Atela, C. H. Quinn, and P. A. Minang,"Are REDD projects pro-poor in their spatial targeting? evidence from kenya", Journal of Applied Geography, Vol. 52, pp. 14-24, 2014. [DOI:10.1016/j.apgeog.2014.04.009]
20. [20] J. R. Eastman, M. E. Van Fossen, and L. A. Solorzano,"Transition potential modeling for land-cover change", in GIS, spatial analysis and modeling, edited by D. J. Maguire, M. Batty, and F. Michael, Goodchild, Redlands, CA: ESRI Press, 2005.
21. [21] J. R. Eastman, IDRISI Guid to GIS and Image processing. Accessed in IDRISI Selva 17.02. Worcester, MA: Clark University, 2012.
22. [22] K. B. F. Kamelarczyk, and C. Smith-Hall,"REDD herring: epistemic community control of the production, circulation and application of deforestation knowledge in Zambia", Forest Policy and Economics, Vol. 46, pp.19-29, 2014. [DOI:10.1016/j.forpol.2014.05.006]
23. [23] K. Sagheb Talebi, Forests of Iran. Iran: Research Institute of Forest and Rangelands, 2005.
24. [24] L. Lin, E. Sills, H. Cheshire,"Targeting areas for reducing emissions from deforestation and forest degradation (REDD+) projects in Tanzania", Global Environmental Change, Vol. 24, pp. 277-286, 2014. [DOI:10.1016/j.gloenvcha.2013.12.003]
25. [25] L. Miles, and V. Kapos,"Reducing greenhouse gas emissions from deforestation and forest degradation: global land-use implications", Journal of Science, Vol. 320, pp. 1454-1455, 2008. [DOI:10.1126/science.1155358]
26. [26] L. Pedroni, A. Garcia, B. De jong, B. Schlamadinger, M. Steiniger, S. Brown, T. Pearson, K. Andrasko, and S. Scholz,"BioCF RED Mosaic Methodology-Version1 of the BioCarbon Fund's proposed Methodology for Estimating Reductions of GHG Emissions from Mosaic Deforestation", Published date: 2009/10/14, available: http://wbcarbonfi nance.org/Router.cfm? Page= Doclib&CatalogID=49189, 2014.
27. [27] M. Gholamalifard, H. Zare Maivan, S. Joorabian Shooshtari, and M. Mirzaei,"Monitoring land cover changes of forests and coastal areas of northern Iran (1988-2010), a remote sensing approach", Journal of the Persian Gulf, Vol. 3, pp. 47-56, 2012.
28. [28] M. Gholamalifard, Sh. Joorabian Shooshtari, S. H. Hosseieni Kahnuj, and M. Mirzaei,"Land cover change modeling of coastal areas of Mazandaran province using LCM in a GIS environment", Journal of Environmental Studies, Vol. 38, pp. 109-124, 2013.
29. [29] M. Kotha, and P. D. Kunte,"Land-cover change in Goa-An Integrated RS-GIS Approach", International Journal of Geoinformatics, Vol. 9, pp. 37-43, 2013.
30. [30] M. Mirzayi, A. Riyahi Bakhtiyari, A. Salman Mahini, and M. Gholamalifard,"Investigating the Land Cover Changes in Mazandaran Province Using Landscape Ecology's Metrics Between 1984-2010", Iranian journal of applied ecology, Vol. 2, pp. 37-55, 2013.
31. [31] M. Pirbavaghar, A. A. Darvishsefat, and M. Namiranian," The study of spatial distribution of changes in the northern forests of Iran", presented at the Proceeding of Map Asia, Iran, 2003.
32. [32] M. Sardarzadeh, A. A. Motakan, S. J. Sadati Nejad, and D. Ashurlu," Prediction of forests degradation using RS & GIS methods and combination of artificial neural network-markov chain", presented at the Geomatic Conference, Tehran, Iran, 2013 (Persian).
33. [33] M. S. Islam, and R. Ahmed,"Land use change prediction in Dhaka city using GIS aided markov chain modeling", Journal of Life and Earth Science, Vol. 6, pp. 81-89, 2011. [DOI:10.3329/jles.v6i0.9726]
34. [34] M. Taheri, M. Gholamalifard, A. Riahi Bakhtiari, and S. Rahimoghli,"Land cover changes modeling of Tabriz township using artificial neural network and markov chain", Journal of Physical Geography Research Quarterly, Vol. 45, pp. 97-121, 2014.
35. [35] M. Yousefi, M. R. Pourmajidian, M. Karimi, and L. Darvishi,"Quantitative and qualitative evaluation of forest plantations by four species and suggestion the appropriate species in the hyrcanian forest", Journal of Experimental Biology, Vol. 3, pp. 352-360, 2013.
36. [36] N. Haghdoost, M. Akbarinia, S. M. Hosseini, and Y. Kooch,"Conversion of hyrcanian degraded forests to plantations: effects on soil C and N stocks", Journal of Annuals of Biological Research, Vol. 2, pp. 384-399, 2011.
37. [37] N. J. S. Siles,"Spatial Modelling and prediction of tropical forest conversion in the Isiboro Secure National Park and Indigenous Territory (TIPNIS), Bolivia", Master of science , International Institute for Geoinformation Science and Earth Observation, 2009.
38. [38] N. L. Harris, S. Petrova, F. Stolle, and S. Brown,"Identifying optimal areas for REDD intervention: East Kalimantan, Indonesia as a case study", Environmental Research Letters, Vol. 3, pp. 1-11, 2008. [DOI:10.1088/1748-9326/3/3/035006]
39. [39] N. R. Virgilio, S. Marshall, O. Zerbock and C. Holmes,"Reducing Emissions from Deforestation and Degradation (REDD): A Casebook of On-the-Ground Experience", The Nature Conservancy, Conservation International and Wildlife Conservation Society. Arlington, Virginia, 2010.
40. [40] N. Rodriguez, D. Armenteras, and J. Retana,"Effectiveness of protected areas in the Colombian Andes: deforestation, fire and land-use changes", Journal of Regional Environmental Change, Vol. 13, pp. 423-435, 2013. [DOI:10.1007/s10113-012-0356-8]
41. [41] O. Rafieyan, A. A. Darvishsefat, M. Namiranian," The area change detection in the Northern forests of Iran using ETM+ data", Journal of Science and Technology of Agriculture and Natural Resources, Vol. 10, pp. 277-287, 2006 (Persian).
42. [42] O. S. Kim,"An assessment of deforestation models for reducing emissions from deforestation and forest degradation (REDD)", Journal of Transactions in GIS, Vol. 14, pp. 631-654, 2010. [DOI:10.1111/j.1467-9671.2010.01227.x]
43. [43] R. Bagheri, Sh. Shataee," Modeling forest areas decreases, using logistic regression (case study: Chehl-Chay catchment, Golestan province)", Iranian Journal of Forest, Vol. 2, pp. 243-252, 2010 (Persian).
44. [44] R. J. Culas,"REDD and forest transition: tunneling through the environmental kuznets curve", Ecological Economics, Vol. 79, pp. 44-51, 2012. [DOI:10.1016/j.ecolecon.2012.04.015]
45. [45] R. Kumar, S. Nandy, R. Agarwal, and S. P. S. Kushwaha,"Forest cover dynamics analysis and prediction modeling using logistic regression model", Journal of Ecological Indicators, Vol. 45, pp. 444-455, 2014. [DOI:10.1016/j.ecolind.2014.05.003]
46. [46] R. Mant, S. Swan, H. V. Anh, V. T. Phuong, L. V. Thanh, V. T. Son, M. Bertzky, C. Ravilious, J. Thorley, K. Trumper, L. Miles," Mapping the potential for REDD+ to deliver biodiversity conservation in Viet Nam: a preliminary analysis", Prepared by UNEP-WCMC, Cambridge, UK; and SNV, Ho Chi Minh City, Viet Nam.
47. [47] S. Arekhi,"Modeling spatial pattern of deforestation using GIS and logistic regression: a case study of northern Ilam forests, Ilam province, Iran", African Journal of Biotechnology, Vol. 10, pp. 16236-16249, 2011. [DOI:10.5897/AJB11.1122]
48. [48] S. Arekhi, A. A. Jafarzadeh, and S. Yousefi,"Modeling deforestation using logistic regression, GIS and RS case study: Northern forests of the Ilam province", Journal of Geography and Development, V. 10, pp. 31-42, 2012. [DOI:10.5897/AJB11.1122]
49. [49] S. Eckert, H. R. Ratsimba, L. O. Rakotondrasoa, L. G. Rajoelison, and A. Ehrensperger,"Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region Madagascar", Journal of Forest Ecology and Management, Vol. 262, pp. 1996-2007, 2011. [DOI:10.1016/j.foreco.2011.08.041]
50. [50] S. Joorabian Shooshtari, S. M. Hosseini, A. Esmaili-Sari, and M. Gholamalifard,"Application logistic regression and Markov Chain in land cover change prediction in east of Mazandaran province", Iranian journal of Natural Environment, Vol. 66, pp. 351-363, 2014.
51. [51] S. Pagiola,"Payments for environmental services in Costa Rica", Journal of Ecological Economics, Vol. 65, pp. 712-724, 2008. [DOI:10.1016/j.ecolecon.2007.07.033]
52. [52] S. Ty, N. Sasaki, A. H. Ahmad, and A. Z. Zainal,"REDD development in Cambodia-potential carbon emission reductions in a REDD project", Formath, Vol. 10, pp. 1-23, 2011. [DOI:10.15684/formath.10.1]
53. [53] S. Vafaei, A. A. Darvishsefat, and M. Pir Bavaghar,"Monitoring and predicting land use change using LCM module (Case study: Marivan region)", Iranian Journal of Forest, Vol. 5, pp. 323-336, 2013.
54. [54] T. Wünscher, S. Engel, and S. Wunder,"Spatial targeting of payments for environmental services: a tool for boosting conservation benefits", Journal of Ecological economics, Vol. 65, pp. 822-833, 2008. [DOI:10.1016/j.ecolecon.2007.11.014]
55. [55] V. Kapos, C. Ravilious, A. Campbell, B. Dickson, H. Gibbs, M. Hansen, I. Lysenko, L. Miles, J. Price, J. P. W. Scharlemann, and K. Trumper,"Carbon and biodiversity", UNEP-WCMC, Cambridge, UK, 2008.
56. [56] Y. Haibo, D. Longjiang, G. Hengliang, and Z. Jie,"Tai'an Land Use Analysis and Prediction Based on RS and Markov Mode", Procedia Environmental Sciences, Vol. 10, pp. 2625-2630, 2011. [DOI:10.1016/j.proenv.2011.09.408]
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Parsamehr K, Gholamalifard M, Kooch Y. Transition Potential Modeling of Land-Cover based on Similarity Weighted Instance-based Learning Procedure and Its Implication in the REDD Project Design Document. jgit. 2019; 7 (1) :121-144
URL: http://jgit.kntu.ac.ir/article-1-683-fa.html

پارسامهر کوشا، غلامعلی فرد مهدی، کوچ یحیی. رویه یادگیری برمبنای نمونه وزنی تشابه برای مدل‌سازی پتانسیل انتقال پوشش اراضی و کاربرد آن در سند طراحی پروژه REDD. مهندسی فناوری اطلاعات مکانی. 1398; 7 (1) :121-144

URL: http://jgit.kntu.ac.ir/article-1-683-fa.html



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