مقایسة وضوح مکانی تصاویر اسپات و لندست در تعیین تکه تکه شدگی سیمای سرزمین

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

2 دانشیار دانشکده شیلات و محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

3 استادیار دانشکده شیلات و محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

4 دانشجوی دکتری محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

5 مربی دانشکده محیط زیست و منابع طبیعی، دانشگاه صنعتی خاتم الانبیاء بهبهان

چکیده

از زمان پیدایش بوم­شناسی سیمای سرزمین، همبستگی میان الگوهای مکانی و فرآیندهای بوم­شناختی همواره یکی از کلیدی­ترین موضوعات این رشته بوده است. در این راستا، معیارهای سیمای سرزمین اطلاعات ارزشمندی در توصیف سیمای سرزمین ارائه می­دهند. مشخص است که به منظور محاسبه و تفسیر صحیح معیارهای سیمای سرزمین، مقیاس داده­های ورودی و مقیاس تجزیه و تحلیل باید با هم سازگار باشند. روشی عمده که به منظور بررسی اثرات مقیاس بر معیارهای سیمای سرزمین به کار گرفته می­شود، تغییر اندازه دانه­بندی یا اندازه پیکسل در تصاویر ماهواره­ای است. در این مطالعه از تصاویر ماهواره­ای اسپات و لندست در سال­های 1365 و 1389 و نقشه­های شبیه­سازی شده مبتنی بر شبکه­های خودکار و مارکوف در سال 1399 استفاده گردید. اثرات وضوح مکانی نقشه­ها بر 8 معیار در سطح کلاس و سیمای سرزمین با استفاده از نرم­افزار فرگستیتس (FRAGSTATS) بررسی گردید. نتایج نشان داد که تغییر در اندازه دانه­بندی اثرات معنی­داری بر معیارهای سیمای سرزمین و تغییرات آنها در آینده دارد، به گونه­ای که با افزایش اندازه دانه­بندی مقادیر معیارهای تعداد لکه­ها، تراکم لکه­ها، معیار شکل سیمای سرزمین و پراکندگی کاهش یافتند. به طور کلی معیارها دو نوع رفتار نامنظم و افزایشی را با توجه به کاهش اندازه دانه­بندی از خود نشان دادند، در این میان معیارهای تعداد و تراکم لکه نسبت به سایر معیارهای بررسی شده در این مطالعه بیش­تر به تغییرات اندازه دانه­بندی حساس هستند. لذا کاربرد این معیارها در مطالعات سیمای سرزمین دقت بیشتری را می­طلبد.

کلیدواژه‌ها


عنوان مقاله [English]

Comparison of spatial resolution of LandSat and SPOT satellite images in measuring landscape fragmentation

نویسندگان [English]

  • Ehsan Rahimi 1
  • Abdol-Rasoul Salman Mahini 2
  • Seyed Hamed Mir Karimi 3
  • Hamid Reza Kamyab 4
  • Sattar Soltanian 5
1 MSc. Graduated of Environment, Gorgan University of Agricultural Sciences and Natural Resources
2 Assoc. Prof. College of Fisheries and Environmental Science, Gorgan University of Agricultural Sciences and Natural Resources
3 Assis. Prof. College of Fisheries and Environmental Science, Gorgan University of Agricultural Sciences and Natural Resources
4 PhD. Student of Environment, Gorgan University of Agricultural Sciences and Natural Resources
5 Lecturer, College of Natural Resources and Environment, Behbahan Khatam Alanbia University of Technology
چکیده [English]

Since the foundation of landscape ecology, the correlation between spatial patterns and ecological processes has always been regarded as one of key topics in this discipline. In this context, landscape metrics provide valuable information for the interpretation of landscape patterns. It is clear that the scale of input data and the scale of analysis must be coherent in order to calculate and interpret landscape metrics correctly. One main method that is often used to assess the scaling effects on landscape pattern is to manipulate the grain size or pixel size in satellite images. In this study, The SPOT and LandSat satellite images of 1986 and 2010 and simulations and maps of Markov-cellular automata models of 2020 were used. The effects of spatial resolution on 8 metrics were evaluated using the software FRAGSTATS in class and landscape levels. The results showed that the changes in grain size have significant effects on landscape metrics and their changes in the future so that the increased grain size will lead to the deacreased number of patches (NP), patch density (PD), LSI and CONAG. In general, metrics showed two types of irregular and increase behaviors according to the reduced grain size; in this study, the changes in grain size are more sensitive than the other metrics. So, the application of these metrics in landscape studies shoulde be considerably paid attention.

کلیدواژه‌ها [English]

  • Scale effects
  • Landscape metrics
  • SPOT and landSat satellite images
  • Land use change simulation
1. احمدی، ب.، ا. قربانی، ط. صفرراد و ب. سبحانی. 1394. بررسی دمای سطح زمین در رابطه با کاربری و پوشش اراضی با استفاده از داده­های سنجش از دور. سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 6(1): 61-77.

2. سنجری، ص. و ن. برومند. 1392. پایش تغییرات کاربری/ پوشش اراضی در سه دهه گذشته با استفاده از تکنیک سنجش از دور (مطالعه موردی: منطقه زرند کرمان). سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی. 4(1): 57-67.

3. فاضلی فارسانی، ا.، ر. قضاوی و م. ح. فرزانه. 1394. بررسی عملکرد الگوریتم­های طبقه­بندی کاربری اراضی با استفاده از تکنیک­های ادغام تصاویر (مطالعه موردی: زیرحوزه بهشت­آباد). سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی. 6(1): 91-105.

4. Baldwin DJ, Weaver K, Schnekenburger F, Perera AH. 2004. Sensitivity of landscape pattern indices to input data characteristics on real landscapes: implications for their use in natural disturbance emulation. Landscape Ecology, 19(3): 255-271.

5. Benedek Z, Nagy A, Rácz IA, Jordán F, Varga Z. 2011. Landscape metrics as indicators: quantifying habitat network changes of a bush-cricket Pholidoptera transsylvanica in Hungary. Ecological Indicators, 11(3): 930-933.

6. Botequilha Leitão A, Miller J, Ahern J, McGarigal K, 2006. Measuring landscapes: a planner's handbook. Island Press. 272 pp.

7. Buyantuyev A, Wu J. 2007. Effects of thematic resolution on landscape pattern analysis. Landscape Ecology, 22(1): 7-13.

8. Darvishsefat AA. 2007. GIS and Remote Sensing concepts. Part 2 and 3 (Book of Environmental Evaluation and Planning by Geographic Information System). 2nd edition. Tehran University Press. 25-122.

9. Delcourt HR, Delcourt PA. 1996. Presettlement landscape heterogeneity: evaluating grain of resolution using General Land Office Survey data. Landscape Ecology, 11(6): 363-381.

10. Ewers RM, Didham RK, Pearse WD, Lefebvre V, Rosa I, Carreiras J, Lucas RM, Reuman DC. 2013. Using landscape history to predict biodiversity patterns in fragmented landscapes. Ecology letters, 16(10): 1221-1233.

11. Farina A. 2006. Principles and Methods in Landscape Ecology: Towards a Science of Landscape. Springer, Dordrecht. 412 pp.

12. Ferrari JR, Lookingbill TR, Neel MC. 2007. Two measures of landscape-graph connectivity: assessment across gradients in area and configuration. Landscape Ecology, 22(9): 1315-1323.

13. Gao J, Li S. 2011. Detecting spatially non-stationary and scale-dependent relationships between urban landscape fragmentation and related factors using geographically weighted regression. Applied Geography, 31(1): 292-302.

14. Gong J, Liu Y, Xia B. 2009. Spatial heterogeneity of urban land-cover landscape in Guangzhou from 1990 to 2005. Journal of Geographical Sciences, 19(2): 213-224.

15. Gustafson EJ. 1998. Quantifying landscape spatial pattern: what is the state of the art? Ecosystems, 1(2): 143-156.

16. Hargis CD, Bissonette JA, David JL. 1998. The behavior of landscape metrics commonly used in the study of habitat fragmentation. Landscape Ecology, 13(3): 167-186.

17. Hulshoff RM. 1995. Landscape indices describing a Dutch landscape. Landscape Ecology, 10(2): 101-111.

18. Jaeger JA. 2000. Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landscape Ecology, 15(2): 115-130.

19. Kelly M, Tuxen KA, Stralberg D. 2011. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time. Ecological Indicators, 11(2): 263-273.

20. Li H, Wu J. 2004. Use and misuse of landscape indices. Landscape Ecology, 19(4): 389-399.

21. Li X, He HS, Bu R, Wen Q, Chang Y, Hu Y, Li Y. 2005. The adequacy of different landscape metrics for various landscape patterns. Pattern Recognition, 38(12): 2626-2638.

22. Lin T, Xue X, Shi L, Gao L. 2013. Urban spatial expansion and its impacts on island ecosystem services and landscape pattern: a case study of the island city of Xiamen, Southeast China. Ocean & Coastal Management, 81: 90-96.

23. Lin Y-P, Wu P-J, Hong N-M. 2008. The effects of changing the resolution of land-use modeling on simulations of land-use patterns and hydrology for a watershed land-use planning assessment in Wu-Tu, Taiwan. Landscape and Urban Planning, 87(1): 54-66.

24. Liu D, Hao S, Liu X, Li B, He S, Warrington D. 2013. Effects of land use classification on landscape metrics based on remote sensing and GIS. Environmental Earth Sciences, 68(8): 2229-2237.

25. Lü Y, Feng X, Chen L, Fu B. 2013. Scaling effects of landscape metrics: a comparison of two methods. Physical Geography, 34(1): 40-49.

26. MacArthur RH. 1972. Geographical Ecology: Patterns in the Distribution of Species. Princeton University Press, Princeton, New Jersey, USA. 288 pp.

27. Macedo RD, de Almeida CM, dos Santos JR, Rudorff BFT. 2013. Modeling of land cover Spatial dynamicand land use change associated with the sugarcane expansion. Boletim de Ciências Geodésicas, 19: 313–337.

28. Marja R, Uuemaa E, Mander Ü, Elts J, Truu J. 2013. Landscape pattern and census area as determinants of the diversity of farmland avifauna in Estonia. Regional Environmental Change, 13(5): 1013-1020.

29. McGarigal K, Cushman SA, Neel MC, Ene E. 2002. FRAGSTATS: Spatial Pattern AnalysisProgram for Categorical Maps. Computer software program produced by the authors at theUniversity of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

30. Meentemeyer V. 1989. Geographical perspectives of space, time, and scale. Landscape ecology, 3(3-4): 163-173.

31. Millington AC, Velez-Liendo XM, Bradley AV. 2003. Scale dependence in multitemporal mapping of forest fragmentation in Bolivia: implications for explaining temporal trends in landscape ecology and applications to biodiversity conservation. ISPRS Journal of Photogrammetry and Remote Sensing, 57(4): 289-299.

32. Pascual-Hortal L, Saura S. 2007. Impact of spatial scale on the identification of critical habitat patches for the maintenance of landscape connectivity. Landscape and Urban Planning, 83(2): 176-186.

33. Riitters Riitters KH, O'neill R, Hunsaker C, Wickham JD, Yankee D, Timmins S, Jones K, Jackson B. 1995. A factor analysis of landscape pattern and structure metrics. Landscape Ecology, 10(1): 23-39.

34. Rutledge D. 2003. Landscape indices as measures of the effects of fragmentation: Can pattern reflect process? In Doc Science Internal Series, Vol. 98 Wellington: Department of Conservation. 26 pp.

35. Sang L, Zhang C, Yang J, Zhu D, Yun W. 2011. Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Mathematical and Computer Modelling, 54(3): 938-943.

36. Saura S, Castro S. 2007. Scaling functions for landscape pattern metrics derived from remotely sensed data: Are their subpixel estimates really accurate? ISPRS Journal of Photogrammetry and Remote Sensing, 62(3): 201-216.

37. Shao G, Liu D, Zhao G. 2001. Relationships of image classification accuracy and variation of landscape statistics. Canadian Journal of Remote Sensing, 27(1): 33-43.

38. Shen W, Darrel Jenerette G, Wu J, H Gardner R. 2004. Evaluating empirical scaling relations of pattern metrics with simulated landscapes. Ecography, 27(4): 459-469.

39. Simon AL. 1992. The problem of pattern and scale in ecology. Ecology, 73(6): 1943-1967.

40. Sklenicka P, Pixová K. 2004. Importance of spatial heterogeneity to landscape planning and management. Ekologia(Bratislava)/Ecology(Bratislava), 23: 310-319.

41. Turner MG, Gardner RH, O’Neill RV. 2001. Landscape ecology in theory and practice: pattern and process. Springer Verlag, New York,U.S.A. 406 pp.

42. Turner MG, O'Neill RV, Gardner RH, Milne BT. 1989. Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecology, 3(3-4): 153-162.

43. Turner MG. 2005. Landscape ecology in North America: past, present, and future. Ecology, 86(8): 1967-1974.

44. Turner MG. 2005. Landscape ecology: what is the state of the science? Annual review of ecology, evolution, and systematic, 36: 319-344.

45. Turner SJ. 2003. Landscape Ecology Concepts, Methods, and Applications. Landscape Ecology, 20(8): 1031-1033.

46. Uuemaa E, Roosaare J, Mander Ü. 2005. Scale dependence of landscape metrics and their indicatory value for nutrient and organic matter losses from catchments. Ecological Indicators, 5(4): 350-369.

47. Wu J, Hobbs R. 2002. Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landscape Ecology, 17(4): 355-365.

48. Wu J, Loucks OL. 1995. From balance of nature to hierarchical patch dynamics: a paradigm shift in ecology. Quarterly Review of Biology, 70: 439-466.

49. Wu J, Shen W, Sun W, Tueller PT. 2002. Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecology, 17(8): 761-782.

50. Wu J. 2004. Effects of changing scale on landscape pattern analysis: scaling relations. Landscape Ecology, 19(2): 125-138.

51. Yang X, Zheng X-Q, Chen R. 2014. A land use change model: Integrating landscape pattern indexes and Markov-CA. Ecological Modelling, 283: 1-7.

52. Zheng D, Heath LS, Ducey MJ. 2008. Modeling grain-size dependent bias in estimating forest area: a regional application. Landscape ecology, 23(9): 1119-1132.