استخراج و شناسایی لندفرم های یخچالی با استفاده از روش شی‌گرا (مطالعه موردی سیرک های یخچالی سبلان)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه محقق اردبیلی

2 دانشگاه تبریز

چکیده

طبقه بندی لندفرم در حقیقت یک موضوع پژوهشی اصلی در ژئومورفومتری و علومی است که تجزیه و تحلیل کمی از سطح زمین دارند. لندفرم­ها کنترل­کننده شرایط آستانه برای فراینده­های ژئومورفولوژیک فعلی و دیگر فرایندهایی مثل میکروکلیما، اکولوژی و هیدرولوژی سطحی و غیره است. از این رو شناسایی دقیق آنها میتواند کمک زیادی در زمینه مدیریت و برنامه­ریزی محیطی باشد. در این پژوهش با استفاده از روش شی­گرا و سه لایه انحنای پلان، انحنای میانگین و انحنای پروفایل، لندفرم های یخچالی(سیرک ها) دامنه­های شمالی سبلان مورد شناسایی قرار گرفته است. لایه مدل رقومی ارتفاعی زمین با قابلیت تفکیک زمینی 10 متر(تهیه شده از نقشه توپوگرافی 1:250000) به عنوان لایه پایه به منظور تهیه لایه­های انحنا استفاده شد. برای تعیین مقیاس مناسب جهت قطعه­بندی لایه­ها از نرم­افزار ESP < /span> و همچنین از ابزار الحاقی آن در نسخه 8 نرم­افزار ecognition استفاده شد با توجه به نتایج بدست آمده مقیاس 44 برای قطعه­بندی لابه ها انتخاب شد. در ادامه کار با در نظر گرفتن مدل مفهومی پژوهش و اجرای آن در نرم­افزار ecognition سیرک­های یخچالی منطقه به همراه لایه خط­الراس­ها شناسایی و استخراج شدند. مقایسه نتایج بدست آمده با بازدیدهای میدانی انجام شده و تصاویر ماهوار­ه­ای منطقه نشان می­دهد که روش فوق توانسته تا درجه زیادی اهداف مورد نظر در پژوهش را برآورد سازد.

کلیدواژه‌ها


عنوان مقاله [English]

Extraction and Identification of glacial landforms using object-oriented methods (Case Study: glacial Cirques Sabalan)

چکیده [English]

Introduction
Semi-automated extraction of selected landform types from land-surface models such as  digital elevation models (DEMs), curvatures, and slope gradients is of particular interest in  geomorphology, hydrology and related fields(Eisank et al,2010:1). Geomorphometry is the science of quantitative land-surface analysis (Pike, 1995, 2000a; Rasemann et al., 2004). The morphometry of landforms perse, by or without the use of digital data, is more correctly considered part of quantitative geomorphology (Thorn, 1988; Scheidegger, 1991 Leopold et al., 1995; Rhoads and Thorn, 1996).
Evans (1972) was the first person that divided Geomorphometry in two branches the general and special Geomorphometry, in special Geomorphometry More is be discussed landforms and geomorphic processes such as glaciers and runoff in geomorphometry terrain segmentation is an approach for structuring terrain data such as digital elevation model(DEM) via derived land-surface into spatially discrete plan-view areas known as terrain units(strobl,2008).The shape of terrain, i.e. landforms, influence the flow of surface water, transport of sediments, soil production, and determines climate on local and regional scales, furthermore, natural phenomena like vegetation are directly influenced by landform patterns and their relative position across the landscape Landforms although have different meaning to different disciplines, they reveal common physiological and morphological characteristics of terrain which may guide through understanding past and present processes acting on terrain and provide necessary information to related disciplines about land characteristics and potentials(Gerçek, 2010:9). In this study, using MRS algorithms and Ecognition software have been studied glacial landforms the northern slopes of Sabalan.
 Methodology
    In this study, the DEM and derivative of its, have been used in order to extract glacial landforms. To prepare the digital elevation model layer have been used of topographic maps with 1: 25000 scale. Profile curvature, plan curvature and mean curvature are three important layers used in this study.The semi-automated methods refer to the automatic procedures of extracting landform based-process. This is mainly relying on unsupervised isodata classification, pixel-based clasification (supervised /subpixel classifier based on training material), analysis of digital elevation models (DEM), algorithms, hydrological modelling and object oriented analysis (Nabil and Moawad, 2014:42). In this study object-oriented methods and Ecognition software is used for classification and extraction of landforms.
 Results and discussion
In this study, we are looking for are extracted cirques the northern slopes of Sabalan. This area because of the high altitude receives high humidity this precipitation is mainly in the form of snow and is appropriate for the formation of glacier and for cirques. A cirque is one of the most prominent forms of glacial erosion (Embleton   and Hamann, 1988). According to Evans (2004: 154) cirques are “hollows formed at glacial sources in mountains and partly enclosed by steep, arcuate slopes    (headwalls)”. In general cirques exhibit concave shape in both plan and profile   direction, with a size ranging from hundreds of metres to a few kilometers (Glasser and Bennett, 2004). They are typically composed of a cirque crest, a steep headwall, and a gentler cirque floor often filled by a cirque lake. For extraction of circus having profile curvature, plan curvature and mean curvature layers is necessary. With respect to this aforementioned layers were obtained in the SAGA software.
Scale parameter is a crucial threshold that determines the maximum allowed heterogeneity for   segmentation, which   has   a   direct   influence   on   the   size   of   the   objects   to   be obtained. Scale parameter is recognized after a trial and error process (Gerçek, 2010:115).  In this study ultimately scale of 36 was selected for the segmentation.
Extracting ridge line position is very important in determining and identifying the the cirque. According to the morphometry of this landforms for classification the ridge were used convex shapes in layers.
In general, the convex shape of the ridge is determined by the positive values in mean and plan curvature. The Ecognition software and MRS algorithm was used for the execution of the model and Segmentation of the layers. Ridge layer was obtained by defining morphometriy characteristics of the ridge and comparing the results with field data. Finally, according to the semantic model of research, the relevant rules defined in Ecognition software and was extracted circus position.
 Conclusion
In this study glacial landforms (circus) were extracted with semi-automatic approach and by using object-oriented approach in northern slopes of Sabalan. The Result of research were presented in the form of a map which shows the location circuses.

کلیدواژه‌ها [English]

  • Circuses
  • glacial landforms
  • Object-Oriented
  • Ecognition
  • پورباقر کردی سیدمهدی، قنواتی عزت الله، کرم امیر، صفاری امیر(1394) کاربرد روش‌های قطعه‌بندی تصاویرطیفی در شناسایی و جدا سازی مخروط افکنه‌های حوضه یزد-اردکان، مجله پژوهش های جغرافیای طبیعی، دوره 47، شماره 3، پاییز 1394، صفحه 367-383 .
  • رجبی معصومه، بیاتی مریم(1387)، بررسی لندفرم دره های یخچالی مطالعه موردی: دره های یخچالی کوهستان سهند، پژوهشهای جغرافیایی :   تابستان 1387 , دوره  40 , شماره  64 ; از صفحه 105 تا صفحه 121.
  • سیاوش شایان، مجتبی یمانی، منوچهر فرج زاده، علی احمدآبادی، (1391)، طبقه بندی نظارت شده لندفرم های ژئومورفولوژیکی مناطق خشک با استفاده از پارامترهای ژئومورفومتریک (نمونه موردی: منطقه مرنجاب)، فصلنامه سنجش از دور و GIS ، سال چهارم، شماره 2 (پیاپی 14).صص 19-28.
    • علایی طالقانی، محمود­، (1384)، ژئومورفولوژی ایران، انتشارات قومس، چاپ دوم.
    • عاشورلو داوود, متکان علی اکبر, کاظمی آزاده, حسینی امین, آزادبخت محسن, حاجب محمد, غلام پور علی(1387)، تعیین اندازه پیکسل جهت محاسبه خصوصیات فیزیوگرافی حوضه آبریز برای نقشه های توپوگرافی 1:25000 ایران، فصلنامه زمین شناسی ایران :   زمستان 1387 , دوره  2 , شماره  8 ; از صفحه 47 تا صفحه 54 .
    •  مکرم مرضیه, نگهبان سعید(1393)، طبقه بندی لندفرم ها با استفاده از شاخص موقعیت توپوگرافی (TPI) (مطالعه موردی: منطقه جنوبی شهرستان داراب)، اطلاعات جغرافیایی :   زمستان 1393 , دوره  23 , شماره  92 ; از صفحه 57 تا صفحه 65 .
  • همتی رسول، (1386) طرح آمایش استان اردبیل- مطالعات اقلیمی – با سیستم اطلاعات جغرافیایی (gis)

 

  • Band, L., Tague, C., Brun, S., Tenenbaum, D., Fernandes, R., 2000. Modelling watersheds as spatial object hierarchies: structure and dynamics. Trans. GIS 4, 181–196.
  • Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing 65, 2–16.
  • Baatz, M. and Schäp, A.  (2000). "Multiresolution Segmentation: an optimization approach for high quality multi-scale image segmentation". Heidelberg. Pp. 12-23.
  • Didon, J., and Germain, Y.M., 1976, Le Sablan, Volcan Plio-Quaternaire de l’Azerbaidjan oriental (Iran): étude géologique ET pétrographique de l'édifice ET de son environment regional." PhD diss., University Scientifique ET Medical de Grenoble (1976).
  • Drăguţ, L., Blaschke, T., 2006. Automated classification of landform elements using object based image analysis. Geomorphology 81, 330–344.
  • Drăguţ, L, Eisanka, C, Strasser, T,(2010) Local variance for multi-scale analysis in geomorphometry, Geomorphology, Volume 130, Issues 3–4, 15 July 2011, Pages 162–172.
    • Drăguţ .L, Clemens Eisank(2011), Automated object-based classification of topography from SRTM data, Geomorphology141-142(2012)21–33.
  • Ecoginition Developer 2012: User guide, Ecoginition Developer imaging.
  • Eisank, C., Drăguţ, L., Götz, J. and Blaschke, T. (2010) Developing a semantic model of glacial landforms for object-based terrain classification - the example of glacial cirques. In: Addink, E.A. and F.M.B. Van Coillie (Eds.) GEOBIA 2010-Geographic Object-Based Image Analysis. Ghent University, Ghent, Belgium, 29 June – 2 July. ISPRS Vol.No. XXXVIII-4/C7, Archives ISSN No 1682-1777.
  • Eisank, C., Smith, M., Hillier, J.,(2014), Assessment of multiresolution segmentation for delimiting drumlins in digital , Geomorphology, GEOMOR-04677; No of Pages 13
  • Embleton,   C.   And   Hamann,   C., 1988.   A   comparison   of   cirque forms between the Austrian Alps and the Highlands of Britain. Zeitschrift für Geomorphology, Suppl.-Bd. 70, pp. 75-93.
  • Evans, I.S., 1972. General Geomorphometry, derivatives of altitude, and descriptive statistics. In: Chorley, R.J. (Ed.), Spatial Analysis in Geomorphology. Harper & Row, pp. 17–90.
  • Evans, I.S., 2004.    Cirque,   glacial.   In:  A.S.    Goudie    (Ed), Encyclopedia of Geomorphology, Volume    1, A-I.  Routledge, London and New York, pp. 154-158.
  • Fisher, P., Wood, J. and Cheng, T., 2004. Where is Helvellyn Fuzziness of multi-scale landscape morphometry, Transactions of the Institute of British Geographers, 29(1), pp. 106-128.
  • Gerçek, D., 2010, Object-based classification of landforms based on their local geometry and geomorphometric context, Ph.D., Department of Geodetic and Geographic Information Technologies , Supervisor: Prof. Dr. Vedat Toprak Co-Supervisor: Prof. Dr. Josef Strobl March 2010, 202 pages.
  • Giles, P.T., Franklin, S.E., 1998. An automated approach to the classification of the slope units using digital data. Geomorphology 21, 251–264.
  • Glasser,     N.F.   Bennett,     M.R.,    2004.   Glacial    erosional landforms:      origins    and    significance    for   palaeoglaciology. Progress in Physical Geography, 28(1), pp. 43-75.
  • Leopold, L.B., Wolman, M.G., Miller, J.P., 1995. Fluvial Processes in Geomorphology. Dover, New York, 522 pp., reprinted from 1964 edition.
  • MacMillan, R.A., Jones, R.K., McNabb, D.H., 2004. Defining a hierarchy of spatial entities for environmental analysis and modeling using digital elevation models (DEMs). Compute. Environ. Urban. Syst. 28, 175–200.
  • Mark, D. and Smith, B., 2004. A science of topography: From qualitative ontology to digital representations. In: M. Bishop and J. Shroder (eds), Geographic Information Science and Mountain Geomorphology. Springer, Berlin Heidelberg, pp. 75-100.
  • Matsuura, T., Aniya, M., 2012. Automated segmentation of hillslope profiles across ridges and valleys using a digital elevation model. Geomorphology 177 (178), 167–177.
  • Miliaresis, G.C., 2001. Extraction of bajadas from digital elevation models and satellite imagery. Compute. Geosci. 27, 1157–1167.
    • Nabil S .E, Moawad B. M,2014, A semi-automated approach for mapping geomorphology of El Bardawil Lake, Northern Sinai, Egypt, using integrated remote sensing and GIS techniques, The Egyptian Journal of Remote Sensing and Space Sciences (2014) Volume 17, Issue 1, June 2014, Pages 41–60.
  • Pedersen , G.B.M. (2016), Semi-automatic classification of glaciovolcanic landforms: An object-based mapping approach based on geomorphometry, Journal of Volcanology and Geothermal Research ,Volume 311, 1 February 2016, Pages 29–40
  • Pike, R.J., 1995. Geomorphometry—progress, practice, and prospect. Zeitschrift für Geomorphology, Supplement band 101, 221–238.
  • Rasemann, S., Schmidt, J., Schrott, L., Dikau, R., 2004. Geomorphometry in mountain terrain. In: Bishop, M.P., Shroder, J.F. (Eds.), GIS & Mountain Geomorphology. Springer, Berlin, pp. 101–145.
  • Rhoads, B.L., Thorn, C.E.  (Eds.), 1996.  The Scientific Nature of Geomorphology, 27th Binghamton Symposium in Geomorphology, Proceedings. 27–29 September. Wiley, Chichester, UK, 481 pp.
  • Scheidegger, A.E., 1991. Theoretical Geomorphology, 3rd edition. Springer-Verlag, Berlin, 434 pp.
  •  Thorn, C.E., 1988. An Introduction to Theoretical Geomorphology. Unwin Hyman, Boston, 247 pp. Thornbury, W.D., 1954. Principles of Geomorphology. Wiley, New York, 618 pp.
  • Seijmonsbergen,    A.C., 2012.   Current   trends in geomorphological mapping.  Geophysical Research Abstracts, vol.  14, EGU 2012– 6114, 2012, EGU General Assembly, Vienna.
  • Sethupathi A.S ,Lakshmi Narasimhan C ,Vasanthamohan.V(2012), valuation of hydro geomorphological landforms and lineaments using GIS And Remote Sensing techniques in Bargur–Mathur sub watersheds, Ponnaiyar River basin, India, International Journal of Geomatics and Geosciences Volume 3 Issue 1, 2012. PP178-190.
  • Strobl,   J.   (2008).   Segmentation-based   Terrain   Classification.   In:   Q.   Zhou,   B.   Lees   and   G.   A.   Tang, Advances in Digital Terrain Analysis, Series Lecture Notes in Geoinformation and Cartography, New York, Springer, 125-139.
  • Van A, S., Seijmonsbergen, A.C., 2006. Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM. Geomorphology 78, 309–320.
  • Vaz, D.A., Sarmento, P.T.K, Barata, M.T., Fenton, L.K., Michaels, T.I. (2015), Object-based Dune Analysis: Automated dune mapping and pattern characterization for Ganges Chasma and Gale crater, Mars, Geomorphology Volume 250, 1 December 2015, Pages 128–139.
  • Woodcock, C.E., Strahler, A.H., 1987.  The factor of scale in remote-sensing.  Remote Sensing of Environment 21, 311–332.