استفاده از سنجش از دور در ارزیابی و آشکارسازی تغییرات پوشش‌گیاهی (مطالعه موردی: منطقه حفاظت شده ماله‌گاله (مله‌گاله))

محورهای موضوعی : آمایش سرزمین

غلامرضا سبزقبائی ¹ , محمدجواد احسان دوست ² , سیده سولماز دشتی ³ , عاطفه میر ⁴ , فریبا هدایت زاده ⁵

1 - استادیار گروه محیط زیست دانشگاه صنعتی خاتم‌الانبیاء بهبهان، بهبهان، ایران.
2 - کارشناس ارشد آلودگی‌های محیط زیست دانشگاه صنعتی خاتم‌الانبیاء بهبهان، بهبهان، ایران.
3 - دانشیار گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران. *(مسوول مکاتبات)
4 - مربی گروه محیط زیست، دانشکده محیط زیست، زابل، ایران.
5 - کارشناس ارشد آلودگی‌های محیط زیست دانشگاه صنعتی خاتم‌الانبیاء بهبهان، بهبهان، ایران.

تاریخ دریافت : 1395/05/23 تاریخ پذیرش : 1395/10/15 تاریخ انتشار : 1401/10/01

کلید واژه: ماله‌گاله, سنجش از دور, TerrSet‌, پوشش جنگلی, تغییر کاربری اراضی, شاخص پوشش گیاهی,

چکیده مقاله :

زمینه و هدف: تکنیک سنجش از دور به دلیل ویژگی‌های خاص خود در ارایه سریع و ارزان اطلاعات پایه از اهمیت ویژه‌ای برخوردار است. سنجش از دور امروزه در مسایل مهمی مثل ساخت نقشه‌های مناطق و تصمیم‌گیری‌های درست کاربرد دارد. هدف از انجام این مطالعه آشکارسازی تغییرات پوشش گیاهی منطقه حفاظت شده مله گاله بوده است. روش بررسی: در پژوهش حاضر از تصاویر ماهواره‌ای لندست 7 سنجنده ETM+، سال های 2000 و 2010 استفاده شد و به بررسی تغییرات پوشش گیاهی با استفاده از نرم افزار TerrSet بدون در نظر گرفتن باغات و زمین های کشاورزی منطقه حفاظت شده ماله گاله پرداخته شده است. در این مطالعه، پس از تهیه تصاویر ماهواره ای لندست ETM+ برای دو سال 2000 و 2010 و انجام تصحیحات هندسی لازم بر روی آن ها، جهت استخراج پارامتر پوشش گیاهی، از نقشه اولیه حاصل از بارزسازی تصاویر استفاده شد. سپس با در نظر گرفتن نقشه کاربری اراضی منطقه و نقشه طبقه بندی شده حاصل از شاخص NDVI و با در نظر گرفتن پارامتر حداکثر احتمال، نقشه واقعیت زمینی مربوط به دو سال 2000 و 2010 تهیه شد. در نهایت با انجام روش تفاضل دو تصویر، میزان و چگونگی تغییرات نسبت به هم بررسی گردید. یافته ها: کمیت تغییرات در سال‌های 2000 و 2010 بررسی شد و مشخص گردید که در فاصله 10 سال، سطح پوشش گیاهی حفاظتی از 5/5278 هکتار به 25/25211 هکتار افزایش پیدا کرده و با روش تفاضل بین نقشه های نهایی، مشخص شد که تراکم پوشش گیاهی منطقه به میزان مساحت 17/181 هکتار کاسته شده، پوشش گیاهی 48/3417 هکتار از منطقه بدون تغییر بوده و در 59/21739 هکتار از منطقه پوشش گیاهی رشد داشته است. بحث و نتیجه گیری: نتایج نشان می دهد که تصاویر ماهواره ای مجهز به سنجنده ETM+ از قابلیت لازم جهت استخراج پوشش گیاهی به خصوص پوشش گیاهی مناطق جنگلی برخوردار بوده است. در بازه زمانی ده ساله تقریبا نزدیک به زمانی که منطقه حفاظت شده ماله گاله در فهرست مناطق چهارگانه حفاظت محیط زیست ایران قرار گرفته است تا سال 2010 پوشش گیاهی حفاظتی این منطقه افزایش پیدا کرده است.

چکیده انگلیسی:

Background and Objective: Remote sensing techniques due to their specific features in providing rapid and inexpensive basic information is very important. Remote sensing is used these days in the important issues like making maps of the regions and the right decision making. The aim of this study was to changes detection in vegetation of Maleh Galle protected area. Material and Methodology: In this study, satellite images of Landsat 7 ETM+, 2000 and 2010 were used and the vegetation changes using TerrSet software were considered regardless of the gardens and agricultural lands of the of, Maleh Galle protected area. In this study, after the preparation of Landsat ETM+ images for years 2000 and 2010 and necessary geometric corrections on them, for extract the parameters of vegetation cover, the original map was derived from processing images. Then, taking into account the classified land use map and map of NDVI index and keeping in mind the maximum likelihood parameter, ground truth map was prepared for the two years 2000 and 2010. Finally with two images difference method, the rate and the changes relation to each other investigated.     Findings: The quantity changes between the years of 2000 and 2010 were examined and it was found that within 10 years, the level of protective vegetation cover has been increased from 5278/5 hectares to 2521/25 hectares. With the Difference method between final maps, it was found that the density of vegetation area has been reduced to 181/17 hectares. 3417/48 hectares of Vegetation area remained unchanged and 21739/59 hectares of vegetation area has been grown. Discussion and Conclusion: Results showed that satellite images equipped with Landsat ETM+ has sufficient capabilities to extract vegetation cover, particularly vegetation of forest areas. In this nearly ten-year period, when the area was included in the list of protected areas in Iran, by 2010, the protected vegetation of region has been increased.                         

منابع و مأخذ:

1. Makhdoum, M. et al. 2001. Environmental evaluation and planning by geographic information system, first edition, publication of Tehran University. (In Persian)


2. Zebardast. L. et al. 2010. Assessment of the Trend of Changes in Land Cover of Arasbaran Protected Area Using Satellite Images of 2002, 2006 and 2008. Environmental researches, No. 1. (In Persian)


3. Sanchez, W. 2004. Land use and Growth Impacts from Highway Capacity Increases. ASC-Journal of Urban and Development, 130: pp. 75-82.


4. Rajitha, K., Mukherjee, C., and Vinu Chandran R. 2007. Applications of Remote Sensing and GIS for Sustainable Management of Shrimp Culture in India. Journal of Aquaculture Engineering, 36: P 17.


5. Sultana, Q., Sultana, A. and Ara, Z. 2023. “Assessment of the land use and landcover changes using remote sensing and GIS techniques,” Water, Land, For. Susceptibility Sustain. pp. 267–297, doi: 10.1016/B978-0-323-91880-0.00022-2.


6. Helming, K. 2008. Sustainability Impact Assessment of Landuse Changes. Springer. Berlin, Heidelberg, New York. P 507.


7. Akinyemi, F. O., Ghazaryan, G. and Dubovyk, O. 2021. “Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics,” L. Degrad. Dev., Vol. 32, no. 1, pp. 158–172, doi: 10.1002/LDR.3695.


8. Lausch, A. and Herzog, F. 2002. Applicability of Landscape Metrics for the Monitoring of Landscape Change: Issues of Scale, Resolution and Interpretability. Ecological Indicator: 3- 15.


9. Shikhar Deep, Akansha Saklani, 2014.” Urban Sprawl modeling using cellular automata”, The Egyptian Journal of Remote Sensing and Space Sciences, 17, pp. 179–18.


10. Rashid, M. B., Sheik, M. R. Haque, A. J. M. E.  Siddique, M. A. B. Habib, M. A. and Patwary, M. A. A. 2023.“Salinity-induced change in green vegetation and land use patterns using remote sensing, NDVI, and GIS techniques: A case study on the southwestern coast of Bangladesh,” Case Stud. Chem. Environ. Eng., Vol. 7, p. 100314, doi: 10.1016/J.CSCEE.2023.1003


11. Meera Gandhi, G.  Parthiban, S.  Thummalu, Nagaraj. and Christy, A. 2015, NDVI: Vegetation Change Detection Using Remote Sensing and GIS – A Case Study of Vellore District, Procedia Computer Science, Vol. 57, pp. 1199-1210.


12. Bhandari. K.  Kumar, A.  2012. “Feature Extraction using Normalized Difference Vegetation Index (NDVI): A Case Study of Jabalpur City”, Proceedings of Communication, Computing & Security. Procedia Technology Vol. 6, pp 612– 621.


13. Peyman, A. 2010. Soil Salinity in Irrigated Area under Qazvin Plain Network Using Satellite Imagery. Presented in the 9th International Drainage Symposium held jointly with CIGR and CSBE/SCGAB Proceedings, Published by the journal of American Society of Agricultural and Biological Engineers IDS-CSBE-100164, June 13th to June 16th, 2010.


14. Rahman, M. Hedayutul, I., and Shareful, M. 2005. Change Detection of Winter Crop Coverage and the Use of Landsat Data with GIS. The Journal of Geo-Environment, 4: pp. 1-13.


15. Lo, L. and Yang, X. 2002. Drivers of Land Use/Land –Cover Changes and Dynamic Modeling for Atlanta, George Metropolitan Area. Journal of Photogrammetric Engineering and Remote Sensing, 68: pp. 1073-1082.


16. Website of the Environmental Protection Agency of Fars province. 2014. (http://fars.doe.ir/Portal/home). (In Persian)


17. Mohammad. 2015, GIRS website (http://girs.ir). (In Persian)


18. Paul M. Mather, 1990, Computer processing of remotely - sensed images, translated by Mohammad-Ali Najafi Disfani, .1998, Semat Publishing, First Printing, Tehran. (In Persian)


19. Khodakarami, L., Soffianian, A. 2012. Application of Multi Temporal Remote Sensing for Precision Farming. JWSS. 2012; 16 (59):215-231. (In Persian)


20. Zobeiry, M., Majd, A. R. 2004. An introduction to remote sensing technology and its application in natural resources. Tehran University Press, 5th edition, Tehran. (In Persian)


21. Kassa, A., 1990. Drought risk monitoring for Sudan using NDVI, 1982-1993. A Dissertation submitted to the University College London.


22. Kogan, F.N., 1993. United States droughts of late 1980’s as seen by NOAA polar orbiting satellites. International Geoscience and remote Sensing Symposiom, 1: pp. 197-199.


23. Halounov, L., 2008. Reclamation areas and their development studied by vegetation indices, International Journal of Digital Earth, Vol. 1, No. 1, pp.155-164.


24. Thenkabail, P.S., Gamage, M.S.D.N., Smakhtin, V.U., 2004. The use of remote sensing deta for drought assessment and monitoring in Southwest Asia. Report 85. Coiombo, Srilanka: International Water Management Institute.


25. Allison, E. W., 1989. Monitoring drought affected vegetation with AVHRR Digest International Geoscience and Remote Sensing Symposium, 4: pp. 1965-1967.


26. Baghideh, M., Alijani, B., Ziaeian, P. 2011. Evaluating the possibility of using the NDVI index to analyze and monitor droughts in Esfahan Province. Arid Regions Geographic Studies, 1 (4):1-16. (In Persian)


27. Akbari, M. 2003. Assessment and Classification of Desertification Using RS Technique in the Dry Area of the North of Isfahan". Master's Degree in Environmental Sciences, Isfahan University of Technology. (In Persian)


28. Matsushita. B., Wei. Y., Jin. C., Yuyichi. O. and Guoyn. Q., 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. www.mdpi.org/sensors.


29. Pettorelli.N, Vik. J.O., Mysterud. A., Gaillard. J.M., Tucker. C.J. and Stenseth. N.C., 2005. Using the satellite –derived NDVI to assess ecological responses to environmental change. Journal Trends in ecology and evolution. Vol. 20, No. 9.


30. Snaeenejad, S. H., et al. 2008. Using Satellite Images for Vegetation Studies (Comparison of Various Plant Indicators-Case Study of Neyshabour Region). (Article 438). Proceedings of the 5th National Congress of Agricultural Machinery and Mechanization, Mashhad, Ferdowsi University of Mashhad. (In Persian)


31. Sousani, J, et al.,.2008. Application of ETM satellite imagery for forest coverage mapping in the middle Zagros area (Case study of Lorestan forests), Geomatics conference, Tehran, Mapping Organization of Iran. (In Persian)


32. Land use map of Iran Forest and Rangeland Organization, 2013. (http://geographybank.blogfa.com/post-66.aspx). (In Persian)


33. Pakniat, D, et al. 2014. Using remote sensing in evaluating and Detection of vegetation changes and soil salinity: Case Study of Mezayjan Hunting Region, The second National Conference on wilderness with the approach of the management of arid and desert, Semnan, School of Desertification, Semnan University, International Center for Desertification, University of Tehran. (In Persian)


34. Ahmadi, H. and Nusrath, A. 2012. “Vegetation change Detection of Neka river in Iran by using remote sensing and GIS”, Journal of geography and Geology, Vol. 2 No. 1, pp. 58-67.


35. Rafieyan, O. 2003. The Area Change Detection in the Northern Forests for the years between 73 to 80 images of Iran Using ETM⁺ Data. Master thesis. University of Tehran. (In Persian)


36. Darvishsefat, A., 1994. Einsatz und Fusion von Multi sensoralen Satelliten Daten zur Erfassung von Waldinveturen, Ph.D. Thesis, University of Waikato, 341 P.


37. Rangzan, K. et al. 2009. NDVI index conflation and the thermal band image loaders to extract the map of vegetation density using RS and GIS (case study area kamestan), Geomatics Conference, Iran Mapping Organization, Tehran, May 20 and 21. (In Persian)