Topografik Özellikleri Kullanarak Arazi Morfolojisi Analizi: Uşak Ulubey Kanyonu Örneği

Year 2019, Volume: 3 , 77 - 88, 31.12.2019

Ahmet Çilek Süha Berberoğlu Müge Ünal Çilek Cenk Dönmez

https://doi.org/10.30516/bilgesci.645588

Cited By: 2

Abstract

Yeryüzü
şekilleri, geçmişte fizyografik ve morfometrik haritalar el yöntemleri ile
çizilerek konumsal teknolojilerin gelişmesiyle arazi formlarının otomatik
üretilmesi, veri tabanlarında depolanması kolaylaşarak, jeomorfoloji, toprak,
ekoloji, peyzaj mimarlığı gibi fiziki planlarla ilgilenen pek çok bilim dalı
tarafından daha etkin kullanılmaya başlamıştır. Bu çalışmada Ulubey
Kanyonlarının arazi formlarını Coğrafi Bilgi Sistemleri aracılığıyla Topografik
Pozisyon İndeksi (TPI) ile morfolojik analizler yaparak sınıflandırmak
amaçlanmıştır. Uşak Ulubey Kanyonu, Amerika Birleşik Devletleri‘nin Arizona
eyaletinde bulunan Büyük Kanyon’dan (Grand Canyon) sonra dünyanın en büyük
ikinci kanyonu unvanına sahiptir. Uşak‘ın Ulubey ilçesinde yer alan kanyon,
Ulubey ve Banaz çayları boyunca devam eden bir ana kanyon ve buna bağlanan
onlarca büyük yan kanyonlardan oluşmaktadır. Morfolojik sınıflandırmaların
oluşturulmasında 30 m çözünürlükte ASTER Sayısal Yükseklik Modeli (SYM)
kullanılmıştır. Arazi morfolojisinin oluşturulmasında SYM verilerinden üretilen
eğim, eğrisellik, yükseklik farkı, topografik açıklık vb. morfolojik
parametreler kullanılmaktadır. TPI hesaplanmasında kullanılan Jennes
algoritması, en küçük kareleri kullanarak belirlenen pencere boyutuna ikinci
dereceden bir polinom yerleştirerek çok ölçekli bir yaklaşım kullanmaktadır.
Araştırmada farklı ölçekteki SYM verileri için 300 m ve 2000 m pencere
genişliği kullanılarak sonuçlar karşılaştırılmıştır. Oluşturulan morfolojk
sınıflar kanyonlar, sığ vadiler, yaylalar, tabanlı vadiler, ovalar, açık
yamaçlar, dik yamaçlar, vadilerde tepeler, orta eğimli sırtlar veya ovalardaki
küçük tepeler, zirveler olmak üzere 10 sınıfta toplanmaktadır.

Bu
çalışmadan elde edilen bilgiler, farklı özelliklere sahip arazi değişkenleri
(toprak, bitki örtüsü, yükseklik vb.) için doğal sınırlar olarak kabul edilen
yüzey morfolojisinin sınıflandırılması özellikle arazi bozulması ve
jeomorfolojide belirlenmesinde faydalı olacaktır.

Keywords

arazi formu, Ulubey kanyonu, topografik pozisyon indeksi, CBS

Landform Analysis using Topographic Characteristics: An Example of Usak Ulubey Canyon

Abstract

Earth shapes, physiographic and morphometric maps have been drawn by
hand in the past. With the development of spatial technologies, automatic
production of landforms and storage in databases has become easier and has been
used more effectively by many disciplines interested in physical plans such as
geomorphology, soil, ecology and landscape planning. This study aims to
classify the landforms of Ulubey Canyons by morphological analysis with
Topographic Positions Index (TPI) using Geographical Information Systems. Usak
Ulubey Canyon is the second largest canyon in the world after the Grand Canyon
in Arizona, USA. The canyon, located in the Ulubey district of Usak, consists
of a main canyon along the Ulubey and Banaz streams and dozens of large side
canyons connected to it. ASTER Digital Elevation Model (DEM) with 30 m resolution
was used to form the morphological classifications. Morphological parameters
such as slope, curvature, height difference, topographic aperture, etc. are
used to generate the land morphology. The Jennes algorithm used in the TPI
calculation uses a multi-scale approach by placing a quadratic polynomial in
the specified window size using the least squares. In this study, 300 m and
2000 m window widths were combined for landform classification. The
morphological classes are classified into 10 class including i) canyons, deeply
incised streams ii) mid-slope drainages, shallow valleys iii) upland drainages,
headwaters iv) U-shape valleys v) plains vi) open slopes vii) upper slopes,
mesas viii) local ridges/hills in valleys ix) mid-slope ridges, small hills in
plains x) mountain tops, high ridges. The information obtained from this study,
classification of surface morphology considered as natural boundaries for land
variables (soil, vegetation, height, etc.) with different characteristics will
be useful in determining land degradation and geomorphology.

Keywords

Landform, Ulubey canyon, topographic position index, GIS

References

• Blaszczynski, J. S. (1997). Landform characterization with geographic information systems. Photogrammetric Engineering and Remote Sensing.
• De Reu, J., Bourgeois, J., Bats, M., Zwertvaegher, A., Gelorini, V., De Smedt, P., vd. (2013). Application of the topographic position index to heterogeneous landscapes. Geomorphology. doi:10.1016/j.geomorph.2012.12.015
• Grohmann, C. H., & Riccomini, C. (2009). Comparison of roving-window and search-window techniques for characterising landscape morphometry. Computers and Geosciences. doi:10.1016/j.cageo.2008.12.014
• Guisan, A., Weiss, S. B., & Weiss, A. D. (1999). GLM versus CCA spatial modeling of plant species distribution. Plant Ecology. doi:10.1023/A:1009841519580
• Han, H., Jang, K., Song, J., Seol, A., Chung, W., & Chung, J. (2011). The effects of site factors on herb species diversity in Kwangneung forest stands. Forest Science and Technology, 7(1), 1–7. doi:10.1080/21580103.2011.559942
• Ho, L. T. K., & Umitsu, M. (2011). Micro-landform classification and flood hazard assessment of the Thu Bon alluvial plain, central Vietnam via an integrated method utilizing remotely sensed data. Applied Geography. doi:10.1016/j.apgeog.2011.01.005
• 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 and Urban Systems. doi:10.1016/S0198-9715(01)00039-4
• Ilia, I., Rozos, D., & Koumantakis, I. (2017). Landform classification using GIS techniques. The case of Kimi municipality area, Euboea Island, Greece. Bulletin of the Geological Society of Greece, 47(1), 264. doi:10.12681/bgsg.10940
• Ilia I, Rozos D, & Koumantakis I. (2013). LANDFORM CLASSIFICATION USING GIS TECHNIQUES. THE CASE OF KIMI MUNICIPALITY AREA, EUBOEA ISLAND, GREECE. Bulletin of the Geological Society of Greece.
• Jenness, J. (2006). Topographic Position Index (tpi_jen.avx) extension for ArcView 3.x, v. 1.2. Jenness Enterprises.
• Jones, K. B., Heggem, D. T., Wade, T. G., Neale, A. C., Ebert, D. W., Nash, M. S., vd. (2000). Assessing landscape condition relative to water resources in the western united states: A strategic approach. Içinde Environmental Monitoring and Assessment. doi:10.1023/A:1006448400047
• Mac Millan, R. A., Martin, T. C., Earle, T. J., & Mc Nabb, D. H. (2003). Automated analysis and classification of landforms using high-resolution digital elevation data: Applications and issues. Canadian Journal of Remote Sensing. doi:10.5589/m03-031
• Martín-Duque, J. F., Pedraza, J., Sanz, M. A., Bodoque, J. M., Godfrey, A. E., Díez, A., & Carrasco, R. M. (2003). Landform Classification for Land Use Planning in Developed Areas: An Example in Segovia Province (Central Spain). Environmental Management. doi:10.1007/s00267-003-2848-2
• McNab, W. H. (2007). A topographic index to quantify the effect of mesoscale landform on site productivity. Canadian Journal of Forest Research. doi:10.1139/x93-140
• Mert, A., Şentürk, Ö., Güney, C. O., Akdemir, D., & Özkan, K. (2013). Mapping of Some Distal Variables Available for Mapping Habitat Suitabilities of The Species . A Case Study from Buldan District. Içinde 3rd International Geography Symposium - GEOMED 2013 (ss. 489–497).
• Mokarram, M., Roshan, G., & Negahban, S. (2015). Landform classification using topography position index (case study: salt dome of Korsia-Darab plain, Iran). Modeling Earth Systems and Environment, 1(4), 1–7. doi:10.1007/s40808-015-0055-9
• Mokarram, M., & Sathyamoorthy, D. (2018). A review of landform classification methods. Spatial Information Research, 26(6), 647–660. doi:10.1007/s41324-018-0209-8
• Oruç, M. S., Mert, A., & Özdemir, İ. (2017). Modelling Habitat Suitability for Red Deer ( Cervus elaphus L .) Using Environmental Variables in Çatacık Region, Eskişehir. Bilge International Journal of Science and Technology Research, 1(2), 135–142.
• Özdemir, S., & Özkan, K. (2016). Ecological properties of Turkish Oregano (Origanum onites L.) and balsamic sage (Salvia tomentosa Miller) in the Ovacık Mountain district of the Mediterranean region. İstanbul Üniversitesi Orman Fakültesi Dergisi, 66(1), 264–277. doi:10.17099/jffiu.39407
• Rigol-Sanchez, J. P., Stuart, N., & Pulido-Bosch, A. (2015). ArcGeomorphometry: A toolbox for geomorphometric characterisation of DEMs in the ArcGIS environment. Computers and Geosciences. doi:10.1016/j.cageo.2015.09.020
• Seif, A. (2014). Using Topography Position Index for Landform Classification (Case study: Grain Mountain). BEPLS Bull. Env. Pharmacol. Life Sci, 311(311), 33–39. http://www.bepls.com/october2014bepls/6.pdf
• Skentos, A., & Ourania, A. (2017). Landform Analysis Using Terrain Attributes. A Gis Application on the Island of Ikaria (Aegean Sea, Greece). Annals of Valahia University of Targoviste, Geographical Series, 17(1), 90–97. doi:10.1515/avutgs-2017-0009
• Şentürk, Ö., Negis M.G. & Gülsoy, S. (2019). Alpha Species Diversity and Ecological Site Factor Relations in Brutian Pine Forests: A Case Study From Gölhisar District. Bilge International Journal of Science and Technology Research, 3(2), 178-188.
• Tekin, S. & Çan, T. (2019). Slide Type Landslide Susceptibility Assessment of the Ermenek River Watershed (Karaman) Using Artificial Neural Network. Bilge International Journal of Science and Technology Research, 3(1), 21-28.
• Tagil, S., & Jenness, J. (2008). GIS-based automated landform classification and topographic, landcover and geologic attributes of landforms around the Yazoren Polje, Turkey. Journal of Applied Sciences. doi:10.3923/jas.2008.910.921
• Verhagen, P., & Drâguţ, L. (2012). Object-based landform delineation and classification from DEMs for archaeological predictive mapping. Journal of Archaeological Science. doi:10.1016/j.jas.2011.11.001
• Weiss, A. (2001). Topographic position and landforms analysis (Poster presentation). Içinde ESRI User Conference, San Diego, CA, July 9-13.