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مورفولوژی نوری و کاربرد آن در ژئومورفولوژی | ||
| پژوهش های جغرافیای طبیعی | ||
| مقاله 2، دوره 50، شماره 4، دی 1397، صفحه 611-638 اصل مقاله (4.47 M) | ||
| نوع مقاله: مقاله کامل | ||
| شناسه دیجیتال (DOI): 10.22059/jphgr.2018.234682.1007069 | ||
| نویسندگان | ||
| سینا صلحی1؛ عبدالله سیف* 2 | ||
| 1دانشجوی دکتری، گروه جغرافیای طبیعی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان، اصفهان، ایران | ||
| 2دانشیار، گروه جغرافیای طبیعی، دانشکدة علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان، اصفهان، ایران | ||
| چکیده | ||
| ژئومورفولوژیستها برای نمایش ناهمواریها و اشکال ژئومورفیک سطح زمین از مدلهای مختلفی استفاده میکنند؛ یکی از پُرکاربردترین آنها مدل سایه- روشن است که با تابش فرضی نور از یک منبع از آن برای تشخیص و نمایش عوارض مختلف ژئومورفیک و فرمهای خطی استفاده میشود. ثابتبودن منبع نور و تنوع و پیچیدگی سطوح زمین در بسیاری مواقع مدلها و الگوریتمهای استاندارد را با محدودیت روبهرو و تفسیر عوارض سطح زمین را دشوار میکند. برای تصحیح، بهبود، و نمایش هدفمند توپوگرافی از مفهومی با نام «مورفولوژی نوری» استفاده شد. مؤلفههای ژئومورفولوژیکی مانند شیب، جهت شیب، فراوانی، و توزیع جهات و میزان و نوع همگرایی- واگرایی سطوح زمین مد نظر قرار گرفت. از چهارده مدل مختلف انحنا و شش مدل نوسان زوایای آزیموتی و سمتالرأسی برای آشکارسازی و تصحیح نمایش عوارض استفاده شد. آنالیز جهتی، مورفولوژیک، و کنتراست بر روی همة مدلها انجام و با نتایج مدل استاندارد مقایسه شد و نحوة عملکرد و ارتباط هر یک با لندفرمها تحلیل شد و کاربردهای رایج آنها در شناسایی لندفرمها تحلیل گردید. همة مدلها در محیط پایتون اجرا و توسط واسط گرافیکی پایتون طراحی شد. نرمافزار Optical Morphology برای اجرای همة مدلها ارائه شد. | ||
| کلیدواژه‌ها | ||
| برنامهنویسی پایتون؛ ژئومورفولوژی؛ سایه- رنگزنی محاسباتی؛ مورفولوژی نوری | ||
| عنوان مقاله [English] | ||
| Optical Morphology and its Application in Geomorphology | ||
| نویسندگان [English] | ||
| Sina Solhi1؛ Abdollah Seif2 | ||
| 1PhD Student in Physical Geography, Faculty of Geographic Science and Planning, University of Isfahan, Isfahan, Iran | ||
| 2Associate Professor of Physical Geography, Faculty of Geographic Science and Planning, University of Isfahan, Isfahan, Iran | ||
| چکیده [English] | ||
| Introduction Geomorphologists use different models to illustrate topography and geomorphic features. One of these common models is to use hillshading, as an effective tool to detect and represent morphological shape of the terrain. This model applys a light source to make a contrast between bright sections and the parts that fall in the shadows. Many researchers have worked on the hillshade modelling. Some of them work on the azimuthal and zenithal angle of light source illumination on the earth surfaces. Others focussed on the direction and the gradient of the earth and their effect on the quality of the shadows and bright areas representations. In this research new concepts called optical morphology is introduced which is considerred as a set of methods, models and technics for representing geomorphologic and topographic features more accurate and visible. We have employed 14 terrain curvature models and also 6 models for azimuthal and zenithal angle adjustmernt. For running these models, Digital Surface Model (DSM) extracted from ALOS satellite data was used on Iran diverse geomorphological landforms. Then, these models were scripted by python and Graphical User Interface (GUI)using Python Tkinter library. A GIS-Based toolkit named Optical Morphology was prepared to calculate all introduced models in the form of raster file format. Finally, numerical analysis, including statistical, morphological, directional and contrast analysis, were run for all the model outputs. The performances and some general applications of these models are described in the field of geomorphology. Materials and methods In this research, Digital Surface Model published by Japan Aerospace Exploration Agency (JAXA), with a spatial resolution, near 23m, has been used for the purpose. The data were obtained from ALOS satellite image. The database is based on the global 3-D topographical DSM, which is currently the most accurate elevation data on the global scale. Several hill-shade modeling is used to enhance terrain feature’s representation. For this purpose, Python programming is used to prepare all these models. The main local terrain descriptors such as slope and aspect have also been used to enhance terrain morphology appearance. The 6 models were run based on changes of azimuthal and zenithal angles of light source position. The models for azimuthal and zenithal analysis are including Aspect Frequency Distribution Analysis (AFDA), Un-weighted Multi-Directional Light Source (UMDLS), Weighed Multi-Directional Light Source (WMDLS), Vertical Light Source Illumination (VLSI), Slope Shading Model (SSM), and Sinusoidal Light Source Fluctuation (SLSF). The 14 models run according to the terrain curvatures are including Profile Curvature Shading Model (PCSM), Tangential Curvature Shading Model (TCSM), Plan Curvature Shading Model (PCSM), Un-sphericity Curvature Shading Model (UCSM), Mean Curvature Shading Model (MCSM), Differential Curvature Shading Model (DCSM), Maximal Curvature Shading Model (MaCSM), Minimal Curvature Shading Model (MiCSM), Horizontal Excess Curvature Shading Model (HECSM), Vertical Excess Curvature Shading Model (VECSM), Total Gaussian Curvature Shading Model (TGCSM), Total Accumulation Curvature Shading Model (TACSM), Flowlines Curvature Shading Model (FCSM), and Total Ring Curvature Shading Model (TRCSM). All these models are programmed using python (V.2.7 and Tkinter for GUI programming). Results and discussion In this research, optical morphology of terrain has been performmed using basic geographic information system concepts. The python programming has been used to execute different hillshade models. Some topographical factors such as terrain slope and aspect have been considered with regards to light source directions (Azimuthal and zenithal directions). In general, 20 different shading models have been programmed for calculating optical morphology and prepared as GIS toolkit named Optical Morphology. This tool is able to uses Digital Elevation Model as an input to analyze its raster structure and then store results as an ASCII file format. Finally, we have explained results, applications, advantages and disadvantages of these models. Conclusion Light source direction modeling combined with the geomorphological attributes is a powerful tool to more accurately recognize and detect landforms and could help geomorphologist in different field of studies. In this research, optical morphology modeling was done using Python programming language to enhance representation of the geomorphological terrain features. The results of these efforts are abstracted in the GIS-based toolkit which is applicable in the quantitative geomorphology area. These models have different approaches against local topographic properties, local conditions of each place and shading properties. Some geomorphological factors such as slope and aspect, topographic characteristics, terrain curvatures and, pixel distribution are effective and suitable in running and performing and adjusting the models. | ||
| کلیدواژه‌ها [English] | ||
| optical morphology, geomorphology, python programming, analytical hill-shading | ||
| مراجع | ||
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ArcGIS Resources (2008). Aspect-slope map, http://blogs.esri.com/esri/arcgis/ (last accessed: 7 April 2014). Association of American Geographers (AAG) (2014). AAG Annual Meeting. http://meridian.aag.org. Batson, R.M.; Edwards, K. and Eliason, E.M. (1975). Computer-generated shaded relief images, Journal of Research of the US Geological Survey, 3(4): 401-408. Brassel, K. (1973). Modelle und Versuche zur automatischen Schraglichtschattierung(Ein Beitrag zur Computer-Kartographie), ETH, Zurich. Brassel, K. (1974). A model for automatic hill-shading, The American Cartographer, 1(1): 15-27. El-Sheimy, N.; Valeo, C. and Ayman, H. (2005). Digital Terrain Modeling Acquisition, Manipulation, and Applications, Artech House, London. ESRI (2009). ArcGIS Desktop Help V.9, Environmental Systems Research Institute, California, United states. Evans, I.S. and Chorley, R.J. (1972). Spatial Analysis in Geomorphology (General geomorphometry, derivatives of altitude, and descriptive statistics), Harper & Row, PP. 17-90. Florinsky, I.V. (1998). Accuracy of local topographic variables derived from digital elevation models, International Journal of Geographical Information Science, 12(1): 47-62. Gallant, J.C. and Wilson, J.P. (1996). TAPES-G: A Grid-based Terrain Analysis Program for the Environmental Sciences, Computers & Geosciences, 22(7): 713-722. Gauss, K.F. (1828). Disquisitiones generales circa superficies curvas, Commentationes Societatis Regiae Scientiarum Gottingensis, 6: 99-146. Gouraud, H. (1971). Continuous shading of curved surfaces, Computers, IEEE Trans-actions on, 100(6): 623-629. Hobbs, K.F. (1999). An investigation of RGB multi-band shading for relief visualization, International Journal of Applied Earth Observation and Geoinformation, 1(3): 181-186. Horn, B.K.P. (1981). Hill shading and the reflectance map, Proceedings of the IEEE, 69(1): 14-47. Horn, B.K.P. and Sjoberg, R.W. (1979). Calculating the reectance map, Applied Optics, 18(11): 1770-1779. Imhof, E. (1982). Cartographic Relief Presentation, Walter de Gruyter, New York and Berlin. Jenny, B. (2000). Computergestutzte Schattierung in der Kartograe, ETH, Zurich. Jenny, B. (2001a). Computergestutzte Schattierung, Kartographische Bausteine, 18: 61- 69. Jenny, B. (2001b). An Interactive Approach to Analytical Relief Shading, Cartographica, The International Journal for Geographic Information and Geo-visualization, 38(1): 67-75. Jenny, B. (2009). Software for terrain mapping, http://terraincartography.com/(last accessed: 7 April 2014). Jenny, B. and Hurni, L. (2006). Swiss-style color relief shading modulated by elevation and by exposure to illumination, The Cartographic Journal, 43(3): 198-207. Jenny, B. and Raber, S. (2002). Relief shading (Online), Zurich Institute of Cartography, ETH. Online (accessed 8 July 2009): www.reliefshading.com. Jones, K.H. (1998). A comparison of algorithms used to compute hill slope as a property of the DEM, Computers & Geosciences, 24 (4): 315-323. Katzil, Y. and Doytsher, Y. (2003). A logarithmic and sub-pixel approach to shaded relief representation, Computers & Geosciences, 29(9): 1137-114. Kennelly, P.J. (2008). Terrain maps displaying hill-shading with curvature, Geomorphology, 102(3): 567-577. Kennelly, P.J. (2009). Hill-shading techniques to enhance terrain maps, In Proceedingsof the 24th International Cartographic Conference, PP. 15-21. Kennelly, P.J. and Kimerling, A.J. (2001). Modifications of Tanaka's illuminated contour method, Cartography and Geographic Information Science, 28(2): 111-123. Kennelly, P.J. and Kimerling, A.J. (2004). Hillshading of terrain using layer tints with aspect-variant luminosity, Cartography and Geographic Information Science, 31(2): (67-77. Kimerling, A.J. and Moellering, H. (1989). The development of digital slope-aspect displays, Inuto Carto 9: Ninth International Symposium on Computer-AssistedCartography, PP. 241-244. Krcho, J. (1973). Morphometric analysis of relief on the basis of geometric aspect of field theory, Acta Geographica Universitatis Comenianae, Geographico-Physica, 1(1): 7-233. Krcho, J. (1983). Teoretická concepcia a interdisciplinarne aplikacie komplexného digitalneho modelu reliéfu pri modelovanï dvojdimenzionalnych poli, Geografický casopis, 35(3): 265-291. Loisios, D.; Tzelepis, N. and Nakos, B. (2007). A methodology for creating analytical hill-shading by combining different lighting directions, In Proceedings of the 23rdInternational Cartographic Conference, August 4-10, Moscow, Russian. Lukas, K. and Weibel, R. (1995). Assessment and improvement of methods for analytical hillshading, In Proceedings of the 17th International Cartographic Conference, Barcelona, Spain, 3-9 September 1995. Marsik, Z. (1971). Automatic relief shading, Photogrammetria, 27(2): 57-70. Mitášová, H. and Hofierka, J. (1993). Interpolation by regularized spline with tension, II Application to terrain modelling and surface geometry analysis, Mathematical Geology, 25(6): 657-669. Moellering, H. (2012). Perspectives on 3-D visualization of spatial geodata and future prospects ,True-3D in Cartography Springer, 1-19. Moellering, H. and Kimerling, A.J. (1990). A new Digital Slope-aspect Display Process, Cartography and Geographic Information Systems, 17(2): 151-159. Orzan, A.; Bousseau, A.; Barla, P.; Winnemoller, H.; Thollot, J. and Salesin, D. (2013). Diffusion curves: a vector representation for smooth-shaded images, Communications of the ACM, 56(7): 101-108. Panigrahi, N. (2014). Computing in Geographic Information Systems, by Taylor & Francis Group, LLC, Minnesota, USA. Patterson, T. (2014). Shaded relief: Ideas and techniques about relief presentation on maps, http:// www. hadedrelief.com. Patterson, T. and Jenny, B. (2010). Shaded relief archive, http://shadedreliefarchive.com. Podobnikar, T. (2012). Multidirectional visibility index for analytical shading enhancement, The Cartographic Journal, 49(3): 195-207. Robinson, A.H. and Thrower, N.J.W. (1957). A new method of terrain representation, Geographical Review, 47(4): 507-520. Serebryakova, M. and Hurni L. (2014). Automatic Adjustment of Image Sharpness in Relief Shading, Master Thesis, Advisor: Prof. Dr. Lorenz Hurni, Advisor: Dr. Fabio Veronesi, Institude of Cartography and Geoinformation Department of Civil, Environmental and Geomatic Engineering Swiss Federal Institute of Technology. Shary, P.A. (1995). Land surface in gravity points classification by a complete system of curvatures, Mathematical Geology, 27(3): 373-390. Shary, P.A. and Stepanov, I.N. (1991). On the second derivative method in geology, Doklady AN SSSR, 319(2): 456-460. Shary, P.A.; Sharaya, L.S. and Mitusov, A.V. (2002). Fundamental quantitative methods of land surface analysis, Geoderma, 107(12): 1-32. Surfer® 13. (2017). Golden Software, LLC, www.goldensoftware.com, Colorado. Tadono, T.; Ishida, H.; Oda, F.; Naito, S.; Minakawa, K. and Iwamoto, H. (2014). Precise Global DEM Generation by ALOS PRISM, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(4): 71-76. Takaku, J; Tadono, T. and Tsutsui, K. (2014). Generation of High Resolution Global DSM from ALOS PRISM, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL(4): 243-248. Tanaka, K. (1950). The relief contour method of representing topography on maps, Geographical Review, 40(3): 444-456. Tutic, D.; Lapaine, M. and Posloncec-Petric, V. (2007). Some experiences in analytical relief shading, In Petrovic, D., editor, Proceedings of 5th Mountain Cartography Work- shop, International Cartographic Association, Commision on Mountain Cartography, Ljubljana, PP. 249-258. Veronesi, F., Hurni, L., (2015). A GIS tool to increase the visual quality of relief shading by automatically changing the light direction, Computers & Geosciences, 74: 121-127. Ware, C. (1989). Fast hill shading with cast shadows, Computers & Geosciences, 15(8): 1327-1334. Wiechel, H. (1878). Theorie und Darstellung der Beleuchtung von nicht gesetzmassig gebildeten Flachen mit Rucksicht auf die Bergzeichnung, Civilingenieur, 24, PP. 335-364. Yoeli, P. (1959). Relief shading, Surveying and Mapping, 19(2): 29-232. Yoeli, P. (1965). Analytical hill shading, Surveying and Mapping, 25(4): 573-579. Yoeli, P. (1966). Analytical hill shading and density, Surveying and Mapping, 26(2): 253- 259. Yoeli, P. (1967a). Die Richtung des Lichtes bei analytischer Schattierung, Kartographis-che achrichten, 2: 37-44. Yoeli, P. (1967b). The mechanization of analytical hill shading, The Cartographic Journal, 2: 82-88. Young, M. and Evans, I. (1978). Terrain analysis: program documentation, Report 6 on Grant DA-ERO-591-73-G0040, Statistical characterization of altitude matrices by computer, Department of Geography, University of Durham, UK, PP. 1-27. Young, T. (1805). An essay on the cohesion of fluids, Philosophical Transactions of the Royal Society of London, 95: 65-87. Zaksek, K.; Ostir, K. and Kokalj, Z. (2011). Sky-view factor as a relief visualization technique, Remote Sensing, 3(2): 398-415. Zhou, Q. (1992). Relief shading using digital elevation models, Computers & Geo-sciences, 18(8): 1035-1045. Zhou, X. and Dorrer, E. (1995). An adaptive algorithm of shaded-relief images from DEMs based on wavelet transform. In Digital photogrammetry and remote sensing95,SPIE Proceedings Series, volume 26)46(: 212-224.
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