Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi

Fatmagül Kılıç Gül

doi:10.26650/JGEOG409177

Araştırma Makalesi

Geomorphometry-Automatic Landform Classification

Yıl 2018, Sayı: 36, 15 - 26, 22.06.2018

Fatmagül Kılıç Gül

https://doi.org/10.26650/JGEOG409177

Öz

In the past, landforms were represented in physiographic and morphometric maps by hand drawing. With developments in digital elevation models (DEM), geographic information systems (GIS) and image analyses, automatic extraction of landforms from morphological parameters and data storage in databases is now possible and are actively utilized in various fields, such as geomorphology, soil science, and ecology. In the above scopes, DEM data forms the database of morphometric parameters, such as, relief, slope, curvatures, and topographic openness. Presently, calculation of parameters, implementation of relationships with landforms, scaling, classification methods, topological relations, homogeneity, and generalizations during the transformation of 3D components of landforms, such as mountains, peaks, slopes, valleys, and plain, into 2D geometric elements in computers are being investigated. In this study, the methods and applications for the automatic extraction of the landforms developed by researchers across different disciplines were reviewed. Classification methods were grouped as combined parameters method and unsupervised/supervised classification methods based on pixel/object. This paper emphasizes the importance of adopting machine learning to implement new models applicable to all terrains.

Anahtar Kelimeler

Landforms, DEM, Classification

Kaynakça

Anders, N. S., Seijmonsbergen, A. C., Bouten, W. (2011). Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping. Remote Sensing of Environment, 115(12), 2976-2985. doi:10.1016/j.rse.2011.05.007
Arrell, K. E., Peter, Fisher, P. F., Tate N. J., Bastin, L. (2007). A fuzzy c-means classification of elevation derivatives to extract the morphometric classification of landforms in Snowdonia, Wales. Computers & Geosciences, 33(10), 1366-1381. doi: 10.1016/j.cageo.2007.05.005 Band, L. E. (1986). Topographic partition of watersheds with digital elevation models. Water Resources Research, 22(1), 15-24. doi: 10.1029/WR022i001p00015
Batuk F., Emem O., Görüm T., Gökaşan E. (2008, January). Implementation of GIS for landforms of Southern Marmara , FIG Working Week, Stokholm, Isveç
Blaschke, T., Strobl, J. (2003). Defining landscape units through integrated morphometric characteristics. In E. Buhmann, & S. Ervin (Eds.) Landscape modelling: Digital techniques for landscape architecture (pp. 104-113). Heidelberg: Wichmann Verlag
Bolongaro-Crevenna A., Torres-Rodríguez V., Sorani V., Framed D., Ortiz M. A. (2005). Geomorphometric analysis for characterizing landforms in Morelos State, Mexico. Geomorphology 67(3-4), 407–422. doi: 10.1016/j.geomorph.2004.11.007
Brabyn, L. (1998, November). GIS analysis of macro landform. Proceedings of the Spatial Information Research Centre’s 10th Colloquium, 35-48. Dunedin, New Zealand
Burrough, P. A., van Gaans, P. F. M., MacMillan, R. A. (2000). High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems, 113(1), 37-52. doi: 10.1016/S0165-0114(99)00011-1
Congalton, R., Green, K. (1999). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. New York: Lewis Publishers
Del Val, M., Iriarte, E., Arriolabengoa, M., Aranburu, A. (2015). An automated method to extract fluvial terraces from LiDAR based high resolution digital elevation models: The Oiartzun Valley, a case study in the Cantabrian margin. Quaternary International, 364, 35–43. doi: 10.1016/j.quaint.2014.10.030
Dikau, R. (1989). The application of a digital relief model to landform analysis in geomorphology. In J. Raper (Eds.), Three dimensional application in geographic information systems (pp. 51-77) London, UK :Taylor & Francis
Dikau, R., Brabb, E. E., Mark, R. M. (1991). Landform classification of New Mexico by computer. USA- Geological Survey Open-File Report, 91(634)
Dikau, R., Brabb, E., Mark, R. K., Pike, R. J. (1995). Morphometric landform analysis of New Mexico. Z. Geomorphol. Suppl. 101, 109–126
Dragut L., Blaschke T. (2006). Automated classification of landform elements using object-based image analysis. Geomorphology 81(3-4), 330–344. doi: 10.1016/j.geomorph.2006.04.013
Drescher, K., Frey, W. D. (2009, Agust-Sept). Landform classification using GIS, Position IT, 30-34
Evans, I.S. (1980). An integrated system of terrain analysis and slope mapping. Zeitschrift für Geomorphologie, Supplementband 36, 274–295.
Fisher, P., Wood, J., Cheng, T. (2004). Where is Helvellyn? Fuzziness of multi-scale landscape morphometry. Transactions of the Institute of British Geographers, 29(1), 106–128. doi: 10.1111/j.0020-2754.2004.00117.x
Gallant, A. L., Brown, D. D., Hoffer, R. M. (2005). Automated mapping of Hammond's landforms. IEEE Geoscience and Remote Sensing Letters, 2(4), 384-388. doi: 10.1109/LGRS.2005.848529
Gökgöz, T. Moustafa Khalil, M. B. (2015). Large scale landform mapping using Lidar DEM. ISPRS International Journal of Geo-Information, 4(3), 1336-1345. doi: 10.3390/ijgi4031336
Gruber, F. E., Baruck, J., Geitner, C. (2017). Algorithms vs. surveyors: A comparison of automated landform delineations and surveyed topographic positions from soil mapping in an Alpine environment. Geoderma, 308, 9-17. doi: 10.1016/j.geoderma.2017.08.017
Hammond, E. H. (1954). Small scale continental landform maps. Annals of Association of American Geographers 44, 33-42
Hrvatin, M., Perko, D. (2009). Suitability of Hammond's method for determining landform units in Slovenia. Acta Geographica Slovenica, 49(2), 343-366. doi: 10.39 86/AGS49204
Hutchinson, M. F. (1988). Calculation of hydrologically sound digital elevation models. Proceedings of the Third International Symposium on Spatial Data Handling, 117-133. Sydney, Australia.
Iwahashi, J., Pike, R. (2007). Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature. Geomorphology, 86(3-4), 409-440. doi: 10.1016/j.geomorph.2006.09.012
Iwahashi, J., Kamiya, I., Matsuoka, M. et al. (2018). Global terrain classification using 280 m DEMs: Segmentation, clustering, and reclassification. Progress in Earth and Planetary Science 5(1), 1-31.. doi:10.1186/s40645-017-0157-2
Jamil, A., Bayram, B. (2018). Tree species extraction and land use/cover classification from high-resolution digital orthophoto maps, IEEE Journal of Selected Topics In Applied Earth Observations and Remote Sensing, 11(1), 89-94. doi: 10.1109/JSTARS.2017.2756864
Jasiewicz, J., Stepinski, T.F. (2013). Geomorphons - a pattern recognition approach to classification and mapping of landforms, Geomorphology, 182(2013), 147–156. doi: 10.1016/j.geomorph.2012.11.005
Jasiewicz, J., Netzel P., Stepinski, T. F. (2014). Landscape similarity, retrieval, and machine mapping of physiographic units. Geomorphology 221, 104–112
Jenson, S.K., Domingue, J.O. (1988). Extracting topographic structure from digital elevation data for GIS analysis. Photogrammetric Engineering & Remote Sensing, 54(11):1593-1600.
Karagulle, D., Frye, C., Sayre, R., Breyer, S., Aniello, P., Vaughan, R., Wright, D. (2017). Modeling global Hammond landform regions from 250-m elevation data. Transactions in GIS. 21(5) 1040-1060. doi: 10.1111/tgis.12265
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Kramm, T., Hoffmeister, D., Curdt, C., Maleki, S., Khormali, F., Kehl, M. (2017). Accuracy assessment of landform classification approaches on different spatial scales for the Iranian loess plateau. ISPRS International Journal of Geo-Information, 6(11), 1-22. doi: 10.3390/ijgi6110366
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Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi

Yıl 2018, Sayı: 36, 15 - 26, 22.06.2018

Fatmagül Kılıç Gül

https://doi.org/10.26650/JGEOG409177

Öz

Yeryüzü şekilleri, geçmişte fizyografik ve morfometrik haritalarda elle çizilerek gösterilirken, jeomorfometri, sayısal yükseklik modelleri (SYM), görüntü işleme ve coğrafi bilgi sistemleri (CBS) alanındaki gelişmeler şekillerin otomatik çıkarılmasını, veri tabanlarında depolanmasını ve jeomorfoloji, toprak bilimi, ekoloji vb. pek çok alanda daha etkin kullanımını sağlamıştır. Bu tür çalışmalarda temel veri SYM ve ondan hesaplanan eğim, eğrisellik, yükseklik farkı, topografik açıklık vb. morfolojik parametrelerdir. Yeryüzünde bileşenleri üç boyutlu (3B) olan yamaç, düzlük, vadi vb. şekillerin sınırlarının, iki boyutlu (2B) geometrik elemanlara yazılımlar ile dönüştürülmesinde parametrelerin hesaplanması, şekillenme ile ilişkilerinin kurulması, ölçek, sınıflandırma yöntemi, yeryüzü şekillerinin doğada birbirlerine göre topolojik ilişkileri, homojenlik, genelleştirme halen araştırılan konular arasındadır. Bu çalışmada, farklı disiplinlere mensup araştırmacılar tarafından yeryüzü şekillerinin otomatik belirlenmesine yönelik geliştirilen yöntemler ve uygulamalar incelenmiş, yöntemler; parametrelerin kombinasyonu ile yapılan denetimsiz sınıflandırma; piksel tabanlı denetimsiz/denetimli sınıflandırma ve obje tabanlı sınıflandırma şeklinde ayrıştırılmıştır. Örüntüler, öğrenme tabanlı modeller vb. algoritmalar ile her tür araziye uygulanabilecek modellerin geliştirilmesinin önemi vurgulanmıştır.

Anahtar Kelimeler

SYM, Yeryüzü şekilleri, Sınıflandırma

Kaynakça

Anders, N. S., Seijmonsbergen, A. C., Bouten, W. (2011). Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping. Remote Sensing of Environment, 115(12), 2976-2985. doi:10.1016/j.rse.2011.05.007
Arrell, K. E., Peter, Fisher, P. F., Tate N. J., Bastin, L. (2007). A fuzzy c-means classification of elevation derivatives to extract the morphometric classification of landforms in Snowdonia, Wales. Computers & Geosciences, 33(10), 1366-1381. doi: 10.1016/j.cageo.2007.05.005 Band, L. E. (1986). Topographic partition of watersheds with digital elevation models. Water Resources Research, 22(1), 15-24. doi: 10.1029/WR022i001p00015
Batuk F., Emem O., Görüm T., Gökaşan E. (2008, January). Implementation of GIS for landforms of Southern Marmara , FIG Working Week, Stokholm, Isveç
Blaschke, T., Strobl, J. (2003). Defining landscape units through integrated morphometric characteristics. In E. Buhmann, & S. Ervin (Eds.) Landscape modelling: Digital techniques for landscape architecture (pp. 104-113). Heidelberg: Wichmann Verlag
Bolongaro-Crevenna A., Torres-Rodríguez V., Sorani V., Framed D., Ortiz M. A. (2005). Geomorphometric analysis for characterizing landforms in Morelos State, Mexico. Geomorphology 67(3-4), 407–422. doi: 10.1016/j.geomorph.2004.11.007
Brabyn, L. (1998, November). GIS analysis of macro landform. Proceedings of the Spatial Information Research Centre’s 10th Colloquium, 35-48. Dunedin, New Zealand
Burrough, P. A., van Gaans, P. F. M., MacMillan, R. A. (2000). High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems, 113(1), 37-52. doi: 10.1016/S0165-0114(99)00011-1
Congalton, R., Green, K. (1999). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. New York: Lewis Publishers
Del Val, M., Iriarte, E., Arriolabengoa, M., Aranburu, A. (2015). An automated method to extract fluvial terraces from LiDAR based high resolution digital elevation models: The Oiartzun Valley, a case study in the Cantabrian margin. Quaternary International, 364, 35–43. doi: 10.1016/j.quaint.2014.10.030
Dikau, R. (1989). The application of a digital relief model to landform analysis in geomorphology. In J. Raper (Eds.), Three dimensional application in geographic information systems (pp. 51-77) London, UK :Taylor & Francis
Dikau, R., Brabb, E. E., Mark, R. M. (1991). Landform classification of New Mexico by computer. USA- Geological Survey Open-File Report, 91(634)
Dikau, R., Brabb, E., Mark, R. K., Pike, R. J. (1995). Morphometric landform analysis of New Mexico. Z. Geomorphol. Suppl. 101, 109–126
Dragut L., Blaschke T. (2006). Automated classification of landform elements using object-based image analysis. Geomorphology 81(3-4), 330–344. doi: 10.1016/j.geomorph.2006.04.013
Drescher, K., Frey, W. D. (2009, Agust-Sept). Landform classification using GIS, Position IT, 30-34
Evans, I.S. (1980). An integrated system of terrain analysis and slope mapping. Zeitschrift für Geomorphologie, Supplementband 36, 274–295.
Fisher, P., Wood, J., Cheng, T. (2004). Where is Helvellyn? Fuzziness of multi-scale landscape morphometry. Transactions of the Institute of British Geographers, 29(1), 106–128. doi: 10.1111/j.0020-2754.2004.00117.x
Gallant, A. L., Brown, D. D., Hoffer, R. M. (2005). Automated mapping of Hammond's landforms. IEEE Geoscience and Remote Sensing Letters, 2(4), 384-388. doi: 10.1109/LGRS.2005.848529
Gökgöz, T. Moustafa Khalil, M. B. (2015). Large scale landform mapping using Lidar DEM. ISPRS International Journal of Geo-Information, 4(3), 1336-1345. doi: 10.3390/ijgi4031336
Gruber, F. E., Baruck, J., Geitner, C. (2017). Algorithms vs. surveyors: A comparison of automated landform delineations and surveyed topographic positions from soil mapping in an Alpine environment. Geoderma, 308, 9-17. doi: 10.1016/j.geoderma.2017.08.017
Hammond, E. H. (1954). Small scale continental landform maps. Annals of Association of American Geographers 44, 33-42
Hrvatin, M., Perko, D. (2009). Suitability of Hammond's method for determining landform units in Slovenia. Acta Geographica Slovenica, 49(2), 343-366. doi: 10.39 86/AGS49204
Hutchinson, M. F. (1988). Calculation of hydrologically sound digital elevation models. Proceedings of the Third International Symposium on Spatial Data Handling, 117-133. Sydney, Australia.
Iwahashi, J., Pike, R. (2007). Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature. Geomorphology, 86(3-4), 409-440. doi: 10.1016/j.geomorph.2006.09.012
Iwahashi, J., Kamiya, I., Matsuoka, M. et al. (2018). Global terrain classification using 280 m DEMs: Segmentation, clustering, and reclassification. Progress in Earth and Planetary Science 5(1), 1-31.. doi:10.1186/s40645-017-0157-2
Jamil, A., Bayram, B. (2018). Tree species extraction and land use/cover classification from high-resolution digital orthophoto maps, IEEE Journal of Selected Topics In Applied Earth Observations and Remote Sensing, 11(1), 89-94. doi: 10.1109/JSTARS.2017.2756864
Jasiewicz, J., Stepinski, T.F. (2013). Geomorphons - a pattern recognition approach to classification and mapping of landforms, Geomorphology, 182(2013), 147–156. doi: 10.1016/j.geomorph.2012.11.005
Jasiewicz, J., Netzel P., Stepinski, T. F. (2014). Landscape similarity, retrieval, and machine mapping of physiographic units. Geomorphology 221, 104–112
Jenson, S.K., Domingue, J.O. (1988). Extracting topographic structure from digital elevation data for GIS analysis. Photogrammetric Engineering & Remote Sensing, 54(11):1593-1600.
Karagulle, D., Frye, C., Sayre, R., Breyer, S., Aniello, P., Vaughan, R., Wright, D. (2017). Modeling global Hammond landform regions from 250-m elevation data. Transactions in GIS. 21(5) 1040-1060. doi: 10.1111/tgis.12265
Keller, E. A., & Pinter, N. (2001). Active Tectonics: Earthquakes, Uplift, and Landscape. Upper Saddle River, N.J. : Prentice Hall
Kılıç F., Öztürk D. (2013, Mayıs). Yeryüzü Şekillerinin Sayısal Yükseklik Modelleri İle Otomatik Çıkarılması, TUFUAB V. Sempozyumu, Trabzon
Klingseisen, B., Metternicht G., Paulus G. (2007). Geomorphometric landscape analysis using a semi-automated GIS-approach, Environmental Modelling & Software 23 (1), 109-121. doi: 10.1016/j.envsoft.2007.05.007
Kramm, T., Hoffmeister, D., Curdt, C., Maleki, S., Khormali, F., Kehl, M. (2017). Accuracy assessment of landform classification approaches on different spatial scales for the Iranian loess plateau. ISPRS International Journal of Geo-Information, 6(11), 1-22. doi: 10.3390/ijgi6110366
Kringer, K., Tusch, M., Geitner, C., Rutzinger, M., Wiegand, C., & Meißl, G. (2009, September). Geomorphometric analyses of LiDAR digital terrain models as input for digital soil mapping. Proceedings of Geomorphometry 2009, 74–81. Zurich, Switzerland
Luo, W., Stepinski ,T. F. (2008). Identification of geologic contrast from landscape dissection pattern: an application to the Cascade Range, Oregon, USA. Geomorphology, 99(1-4), 90-98. doi: /10.1016/j.geomorph.2007.10.014
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Toplam 75 adet kaynakça vardır.

Ayrıntılar

Birincil Dil	Türkçe
Bölüm	Araştırma Makalesi
Yazarlar	Fatmagül Kılıç Gül 0000-0003-3467-9288
Yayımlanma Tarihi	22 Haziran 2018
Gönderilme Tarihi	23 Mart 2018
Yayımlandığı Sayı	Yıl 2018 Sayı: 36

Kaynak Göster

APA	Kılıç Gül, F. (2018). Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography(36), 15-26. https://doi.org/10.26650/JGEOG409177
AMA	Kılıç Gül F. Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography. Haziran 2018;(36):15-26. doi:10.26650/JGEOG409177
Chicago	Kılıç Gül, Fatmagül. “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”. Journal of Geography, sy. 36 (Haziran 2018): 15-26. https://doi.org/10.26650/JGEOG409177.
EndNote	Kılıç Gül F (01 Haziran 2018) Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography 36 15–26.
IEEE	F. Kılıç Gül, “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”, Journal of Geography, sy. 36, ss. 15–26, Haziran 2018, doi: 10.26650/JGEOG409177.
ISNAD	Kılıç Gül, Fatmagül. “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”. Journal of Geography 36 (Haziran 2018), 15-26. https://doi.org/10.26650/JGEOG409177.
JAMA	Kılıç Gül F. Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography. 2018;:15–26.
MLA	Kılıç Gül, Fatmagül. “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”. Journal of Geography, sy. 36, 2018, ss. 15-26, doi:10.26650/JGEOG409177.
Vancouver	Kılıç Gül F. Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography. 2018(36):15-26.

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