نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد مدیریت مناطق بیابانی دانشگاه تهران

2 استادیار دانشکده منابع طبیعی دانشگاه تهران

3 استاد دانشکده منابع طبیعی دانشگاه تهران

4 استادیار دانشکده محیط زیست کرج

چکیده

بیابانزاییپسازدوچالشتغییراقلیموکمبودآبشیرین،سومینچالشمهمجامعهجهانیدرقرنبیستویکم می‌‌باشد، کهبهعنوانیکیازبارزترینوجوهتخریبمحیط زیستوانهداممنابعطبیعیدرجهان مطرحگردیده است. این پدیدهباتأثیربرپوشش گیاهی،آبوخاک، عامل جدّی تهدید کننده پارکهای ملی در مناطق خشک و نیمهخشک از جمله ایران است.اقداماتاجرایی دررابطهباکنترلبیابانزاییبایدمتکیبرشناختوضعیتفعلیبیابانی شدنوشدتآنباشد. در این پژوهش به منظور ارزیابی و پایش بیابانزایی پارک ملی بمو- شیراز، روند تغییرات سالانه پوشش گیاهی در بازه زمانی(2014-2000) مورد بررسی قرار گرفت. فرضبرایناستکهباتحلیلسری‌‌هایزمانیبلندمدتداده‌‌هایماهوارهای و با استفاده از شاخصهای پوشش گیاهی (NDVI و (EVI، میتوان چنین تغییراتی را پایش نمود. لذا در این پژوهش، پروفیل و نقشهتغییرات سالانه مقادیر  NDVI و EVIدر طی14 سال، بااستفادهازمحصول MOD13A1  سنجندهMODISماهواره Terra سیستم Aqua،در محیط نرمافزاری IDRISI Selva تهیه و مورد تحلیل قرارگرفت. در نهایت با بهکارگیری منطق فازی، پروفیل و نقشه شدت بیابانزایی در بازه زمانی مذکور، تهیه گردید. نتایج به دست آمده نشان دهنده تخریب پوششگیاهی وافزایش شدت بیابانزایی در قسمت شمال غربی است. این تخریب شکل جدیدی از بیابانزایی به نام بیابانزایی تکنوژنیکی میباشد که دلیل آن احداث شهر جدید صدرا در قسمت شمال غربی و غرب این پارک بودهاست به طوریکه با احداث شهر صدرا در محدوده غربی این پارک، عملاً حفاظت از این قسمت نا ممکن گردیدهاست.

کلیدواژه‌ها

عنوان مقاله [English]

Monitoring and evaluation of vegetation indices based on Fuzzy Logic using MODIS satellite Imagery (Case study: Bamou National park-Shiraz)

نویسندگان [English]

  • Saharnaz Shekoohizadegan 1
  • Hassan Khosravi 2
  • Hossein Azarnivand 3
  • Gholamreza Zehtabian 3
  • Behzad Raygani 4

1 M. Sc. Expert in Desert Management Region, Faculty of Natural Resources, University of Tehran

2 Assistant Professor, Faculty of Natural Resources, University of Tehran

3 Professor, Faculty of Natural Resources, University of Tehran

4 Assistant Professor, Faculty of Environment, Alborz

چکیده [English]

Abstract
Desertification means land degradation in arid, semi-arid and dry sub-humid regions in result of climate variability and human-activity. Desertification is the third major challenge for international community in twenty-first century after the two challenges of climate change and scarcity of fresh water.This phenomenon has been raised as one of the most striking aspect of environmental degradation and destruction of natural resources in the world.Desertification, byaffecting vegetation cover, water and soil, is a serious factor threatening national parks in arid and semi-arid regions including Iran.Executive actions related to desertification control must be based on the recognition of the current state of desertification and its intensity.The aim of this study was to evaluate and monitor desertification by usingvegetation indices (NDVI and EVI) extracted from MODIS satellite imagery and classification of desertification by using fuzzy logic.
Materials and Methods
The study area covers an area with about 47,244 hectares, which has been named as Bamou National Park.The height distribution of Bamou National Park shows that most of the area is locatedbetween 1700 and 1900 meters altitude and a maximum height of the study area is 2700 meters above the sea level.The average annual rainfall in the main station area representing the Shiraz station is 392.9 mm with a mean annual temperature of 17.9°C.Based on Domarten developed method, Bamou National Park has a semi-arid climate and is cold with winter rains.
In this research, to monitor and evaluate desertification in Shiraz Bamou national park, the annual changes in vegetation cover were studied during the period of 2000 - 2014. On the other hand, this paper tries to monitor desertification changes using long term-time series analysis of satellite data and vegetationcover indices (EVI & NDVI).Therefore, in this study, profile and map of annual changes were prepared on IDRISI Selva and then analyzed using the MOD13A1product, MODIS sensor, Terra satellite and Aqua system. Finally, using fuzzy logic, profile and desertification intensity map were prepared for 2000-2014. According to the climatic conditions of the region and based on expert opinion, the value of fuzzy classes index changes, the software IDRIDIselva and Arc GIS 10.2 severity of desertification on each indicator based on fuzzy logic was prepared.
 Discussion and results
 Based on the results of EVI & NDVI, vegetation destruction and desertification intensity have been more in the north west of the study area. The reason for this destruction and desertification is the construction of the new city of Sadra in part of the North West and the west of this park. It can be said that, this degradation is a new form of desertification entitled anthropogenic desertification.As a result of the construction of Sadra city in the western area of the park, it is practically impossible to protect this area.The results show that EVI is more sensitive than NDVI for monitoring parameters such as canopy cover, leaf area index, canopy structure, phenology, and stress plants. The EVI index due to greater sensitivity to changes in areas with high biomass (vegetation growth season) and mitigating the effects of atmospheric conditions on vegetation index values is more applicable to monitor vegetation changes than NDVI.This paper introduces fuzzy logicas one of the methods for classifying the severity of desertification. Fuzzy logic can be used to determine the boundaries of class and privilege of desertification indicators and explain the process. Fuzzy sets, or classes of fuzzy are no sharply defined boundaries and membership or non- membership of a place in particular.The severity of desertification in the form of fuzzy maps based on each available indicator provided the values between 0 and 1 as the classes of desertificationon the map.It can be concluded that for better management of desertification it is necessary to prioritize areas affected by desertification according to its severity.As a result, we can say that accurate desertification classification can be helped to manage this phenomenon. In fact, it is a set of unpleasant consequences that human environment brings. Hence, monitoring and evaluation of the severity of desertification and mapping always isone of the most important management andplanning tools to achieve sustainable development in the field of natural resources.

کلیدواژه‌ها [English]

  • Bamou National Park
  • EVI
  • Monitoring of Desertification
  • MODIS
  • NDVI
  • Shiraz
1- احمدی، ح، (1377)، ژئومورفولوژی کاربردی، جلد2، بیابان- فرسایش بادی، انتشارات دانشگاه تهران.
2- رحیمی، م.، دماوندی، ع.، جعفریان، و. (1392)، کاربردهایسنجشازدوردرارزیابیوپایشتخریبسرزمین وبیابانزایی. فصلنامه علمی-پژوهشی اطلاعات جغرافیایی(سپهر) 20،‌ 115-128.
3- سپهر، ع.،   اختصاصی، م. ر.،  المدرسی،‌ س. ع. (1391)، ایجادسامانهشاخص‌هایبیابان‌زاییبراساس DPSIR (بهره‌گیریازروشفازی-تاپسیس) .جغرافیا و برنامه ریزی محیطی،23(1)،   33 -50 .
4- صادقیروش، م. ح.،  زهتابیان، غ. (1390)،بررسیآسیب پذیریزیستمحیطی EVI،  منطقهخضرآبادیزدنسبتبهخطربیابان‌زایی،دومینهمایشملیمقابلهبا بیابان‌زاییوتوسعهپایدارتالاب‌هایکویریایران.
5- علوی پناه، س. ک. ( 1382) ، کاربرد سنجش از دور در علوم زمین، انتشارات دانشگاه تهران، صفحه 478
6- Babaev, G. A., (1999). Desert Problems and Desertification in Central ASIA. The researches of the Desert institute springer - velag berlin, Heidelberg New York, 293p.
7- Binh, T.N.K.D., Vromant, N., Hung, N.T., Hens, L., Boon, E.K., (2005). Land cover changes between 1968 and 2003 in Cai Nuoc, Ca Mau Peninsula, Vietnam. Environment Development and Sustainability. 519-536, (4)7
8- Depew, J. J., (2004). Habitat Selection and Movement Patterns of Cattle and White-Tailed Deer in a Temperate Savanna. Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of Master of Science. 71 p.
9-Hill, J., Megier, J., Mehl, W., (1995). Land degradation, soil erosion and desertification monitoring in Mediterranean ecosystems. Remote Sensing Reviews, 12(12), 107-130.
10-Hoersch, B., Braun, G., Schmidt. U., (2002). Relation between landform and vegetation in alpine regions of Wallis, Switzerland. A multiscale remote sensing and GIS approach. Computers, Environment & Urban Systems, 26, 113-139.
11-http://www.irandeserts.com/content
12- http://zistboom.com/fa/news
13-Huete, A.R., Liu, H., Batchily, K., Leeuwen, W., . (1997) A Comparison of Vegetation Indices over a Global Set of TM Images for EOS-MODIS. Remote Sensing of Environment. 440-451, (3)59
14- Koh, C.N., Lee, P.F., Lin, R.S., (2006). Bird species richness patterns of northern Taiwan: primary productivity, human population density, and habitat heterogeneity. Diversity & Distributions12 (5), 546-554.
15-Lawley, M. Lewis, K. Clarke, B., (2016). Site-based and remote sensing methods for monitoring indicators of vegetation condition: An Australian review. Ecological Indicators, 71, 1273-1283.
16- Magee, T. K., Ringold, P. L., Bollman, M. A. (2008). Alien species importance in native vegetation along wade able streams, John Day River basin, Oregon, USA. Plant Ecology, 195, 287-307.     
17- Matsushita, B., Yang, W., Chen, J., Onda, Y., Qiu, G., (2007). Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to topographic effects: A case study in high-density cypress forest. Sensors, 7(11), 2636-2651.
18- Morawitz, D., Blewett, T., Cohen, A., Alberti, M. (2006). Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound. Environmental Monitoring and Assessment, 114(1), 85-106
19- Pettorelli, N., Vik, O., Mysterud. A., Gaillard. J.M., Tucker. C.J., Stenseth, N.C., (2005). Using the satellite derived NDVI to assess ecological responses to environmental change. Journal Trends in ecology and evolution.  9(20), 503-510.
20- Reynolds, J.F., (2001). Desertification. In: Levin, S. (2 Ed.), Encyclopedia of Biodiversity. Academic Press, San Diego, CA, USA, 61-78p.
21-  Reynolds, J.F., Smith, D.M.S., Lambin, E.F., Turner II, B.L., Mortimore, M., Batterbury, S.P.J., et al., (2007). Global desertification: building a science for dryland development. Science, 316, 847-851.
22- Sadeghi Ravesh, M. H., Khosravi, H., Ghasemian, S., (2015). Application of fuzzy analytical hierarchy process for Assessment of combating-desertification alternatives in the central Iran. Journal of Natural Hazard, 75: 653-667.
23- Sadeghi Ravesh, M. H., Zehtabian. G., Khosravi. H., (2014). Application of AHP and ELECTRE models for Assessment of de-desertification alternatives, Desert, 19(2), 141-153.
24- UN (United Nations), (1994). United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/ or Desertification, Particularly in Africa, UNEP/IPA, Nairobi.
25- UNCCD, (1994). United Nations Convention to Combat Desertification in Countries Experiencing Serious Drought and/or Desertification, Particularly in Africa. A/AC.241/27, Paris.
26- UNCCD, (2012). United Nations Convention to Combat Desertification.Www.unccd.int(accessed 16.05.2013)
27- UNEP (United Nations Environmental Program) (1992). Word atlas of desertification, editorial commentary by N. J. Middleton and D. S. G. Thomas Arnold: London.
28- Xie, Z., (2014). Research Advance in Remote Sensing to Land Desertification Monitoring, School of Surveying and Prospecting Engineering, Jilin Jianzhun University, Changchun, China.