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Geomorphometry-Automatic Landform Classification

Year 2018, Issue: 36, 15 - 26, 22.06.2018

Fatmagül Kılıç Gül

https://doi.org/10.26650/JGEOG409177

Abstract

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.

Keywords

Landforms DEM Classification

References

  • 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
  • MacMillan, R. A., Pettapiece, W. W., Nolan, S. C., Goddard, T. W. (2000). A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets and Systems, 113,(1) 81–109. doi: 10.1016/S0165-0114(99)00014-7
  • MacMillan, R. A., Martin, T. C., Earle, T. J. (2003). Automated analysis and classification of landforms using high-resolution digital elevation data: Applications and issues. Canadian Journal of Remote Sensing 29(5), 592–606. doi: 10.5589/m03-031
  • MacMillan, R. A., Shary, P. A. (2009). Landforms and Landform Elements in Geomorphometry. In T. Hengl, H. I. Reuter, Geomorphometry-Concepts, Software, Applications. Developments in Soil Science, 33, (pp. 227-254). Amsterdam: Elsevier
  • Mark, D.M. (1975). Geomorphometric parameters: A review and evaluation. Geografiska Annaler. Series A, Physical Geography 57(3/4), 165-177
  • Martins, F. M. G., Fernandez, H. M., Isidoro, J. M. G. P., Jordán, A., Zavala, L. (2016). Classification of landforms in Southern Portugal (Ria Formosa Basin). Journal of Maps, 12(3), 422–430. doi: 10.1080/17445647.2015.1035346
  • Mashimbye, Z. E., de Clercq, W. P., Van Niekerk, A. (2014). An evaluation of digital elevation models (DEMs) for delineating land components. Geoderma, 213, 312–319. doi: 10.1016/j.geoderma.2013.08.023
  • Miller, B. A., Schaetzl, R. J. (2015). Digital classification of hillslope position. Soil Science Society of America Journal 79(1),132-145. doi:10.2136/sssaj2014.07.0287
  • Milne, J. D. G., Clayden, B., Singleton, P. L., Wilson, A. D. (1995). Soil Description Handbook. Landcare: Manaaki Whenua Press
  • Minar, J., Evans, I.S. (2008). Elementary forms for land surface segmentation: The theoretical basis of terrain analysis and geomorphological mapping. Geomorphology, 95(3-4), 236-259. doi: 10.1016/j.geomorph.2007.06.003
  • Moravej, K., Karimian Eghbal, M., Toomanian, N., Shahla Mahmoodi, S. (2012). Comparison of automated and manual landform delineation in semi detailed soil survey procedure. African Journal of Agricultural Research 17(7): 2592-2600. doi: 10.5897/AJAR11.728
  • Morgan, J. M., Lesh, A. (2005, July). Developing landform maps using ESRI’s model builder. Proceedings of the 2005 ESRI International User Conference, 25–29, San Diego, CA
  • Norini, G., Zuluaga, M. C., Ortiz, İ. J., Aquino, D. T., Lagmay, A. M. F. (2016). Delineation of alluvial fans from digital elevation models with a GIS algorithm for the geomorphological mapping of the Earth and Mars. Geomorphology, 273(15), 134–149. doi: 10.1016/j.geomorph.2016.08.010
  • O'Caliaghan, J. F., Mark, D. M. (1984). The extraction of drainage networks from digital elevation data. Computer Vision, Graphics and Image Processing, 28(3), 323-344. doi: 10.1016/S0734-189X(84)80011-0
  • Pennock, D. J., Zebarth, B. J., DeJong, E. (1987). Landform classification and soil distribution in hummocky terrain, Saskatchewan, Canada. Geoderma, 40(3-4), 297-315. doi: 10.1016/0016-7061(87)90040-1
  • Peucker, D., Douglas H. (1975). Detection of surface-specific points by local parallel processing of discrete terrain elevation data. Computer Graphics and Image Processing, 4(4), 375-387. doi: 10.1016/0146-664X(75)90005-2
  • Pike, R. J. (1988). The geometric signature: Quantifying landslide-terrain types from digital elevation models. Mathematical Geology, 20(5), 491–511.
  • Pelfini M., Bollati I. (2014). Landforms and geomorphosites ongoing changes: Concepts and implications for geoheritage promotion. Quaestiones Geographicae 33(1), 131–143, doi: 10.2478/quageo-2014-0009, ISSN 0137-477X
  • Piloyan, A., Konečný, M. (2017). Semi-automated classification of landform elements in armenia based on SRTM DEM using k-means unsupervised classification. Quaestiones Geographicae, 36(1), 93-103. doi:10.1515/quageo-2017-0007
  • Prima, O. D. A., Echigo, A., Yokoyama, R., Yoshida, T. (2006). Supervised landform classification of Northeast Honshu from DEM-derived thematic maps. Geomorphology, 78(3-4), 373-386. doi: /10.1016/j.geomorph.2006.02.005
  • Romstad, B. (2001). Improving relief classification with contextual merging. In J. T. Bjørke, H. Tveite, Proceedings of the 8th Scandinavian Research Conference on Geographical Information Science, 3-14. Ås, Norway
  • Romstad, B., Etzelmüller, B. (2012). Mean-curvature watersheds: a simple method for segmentation of a digital elevation model into terrain units. Geomorphology, 139–140, 293–302. doi: 10.1016/j.geomorph.2011.10.031
  • Ruhe, R. V. (1960). Elements of the soil landscape, In Trans. 7th int. Congr. Soil Sci. 4 (pp. 165-170)
  • Schmidt, J., Hewitt, A. (2004). Fuzzy land element classification from DTMs based on geometry and terrain position. Geoderma 121(3-4), 243-256. doi. 10.1016/j.geoderma.2003.10.008
  • Seijmonsbergen, A. C., Hengl, T., Anders, N. S. (2011). Semi-automated identification and extraction of geomorphological features using digital elevation data. In M. J. Smith, P. Paron, J. S. Griffiths (Eds.), Geomorphological Mapping (pp. 297–335). Amsterdam: Elsevier
  • 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., Sharaya L. S., Mitusov A. V. (2002). Fundamental quantitative methods of land surface analysis, Geoderma, 107(1-2), 1 –32. doi: 10.1016/S0016-7061(01)00136-7
  • Skidmore A. K. (1990). Terrain position as mapped from a gridded digital elevation model. International Journal of Geographical Information Systems, 4(1), 33-49. doi: 10.1080/02693799008941527
  • Speight, J. G. (1974). A parametric approach to landform regions. Progress in Geomorphology, Special Publication, 7 (pp. 213-230). Oxford: Alden Press
  • Speight, J.G. (1990). Landform. In McDonald, et al. (Eds.), Australian Soil and Land Survey Field Handbook (pp. 9-57). Melbourne: Inkata Press
  • Stepinski, T. F., Bagaria, C. (2009). Segmentation-based unsupervised terrain classification for generation of physiographic maps, IEEE Geoscience and Remote Sensing Letters, 6(4), 733-737. doi: 10.1109/LGRS.2009.2024333
  • Tarboton, D. G., Ames, D. P. (2001, May). Advances in the mapping of flow networks from digital elevation data. World Water and Environmental Resources Congress, Orlando, Florida
  • Tunçay, T., Bayramin, İ., Öztürk, H. S., Kibar, M., Başkan, O. (2014). The use of remote sensing and geographic İnformation system techniques to determine relationships between land use and landform. Toprak Su Dergisi, 3(2), 124-136
  • van Asselen, S., Seijmonsbergen, A. C. (2006). Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM. Geomorphology, 78(3-4), 1309-320. doi: 10.1016/j.geomorph.2006.01.037
  • Ventura, S. J., Irvin, B. J. (2000). Automated landform classification methods for soil landscape studies. In J. P. Wilson & J. C. Gallant (Eds.), Terrain Analysis Principals and Applications (pp. 245-294). New York: John Wiley & Sons
  • Verhagen, P., Dragut, L. (2012). Object-based landform delineation and classification from DEMs for archaeological predictive mapping. Journal of Archaeological Science, 39(3), 698–703. doi: 10.1016/j.jas.2011.11.001
  • Weiss, A. (2001). Topographic Position and Landforms Analysis. ESRI User Conference. San Diego, CA
  • Wysocki, D. A., Schoeneberger, P. J., LaGarry, H. E. (2000). Geomorphology of soil landscapes. In P. M. Huang, Y. Li, M. E. Sumner (Eds.), Handbook of Soil Sciences: Properties and Processes (pp. 5-40). Boca Raton: CRC Press
  • Zevenbergen, L.W., Thorne, C.R., 1987. Quantitative analysis of land surface topography. Earth Surface Processes and Landforms, 12, 47–56. doi: 10.1002/esp.3290120107
  • Zhao, W. F., Xiong, L. Y., Ding, H., Tang, G. (2017). Automatic recognition of loess landforms using Random Forest method. Journal of Mountain Science 14(5). 885-897. doi: 10.1007/s11629-016-4320-9
  • Wood J. (1996). The Geomorphological Characterisation of Digital Elevation Models. Ph.D. Thesis. University of Leicester, England

Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi

Year 2018, Issue: 36, 15 - 26, 22.06.2018

Fatmagül Kılıç Gül

https://doi.org/10.26650/JGEOG409177

Abstract

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.

Keywords

SYM Yeryüzü şekilleri Sınıflandırma

References

  • 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
  • MacMillan, R. A., Pettapiece, W. W., Nolan, S. C., Goddard, T. W. (2000). A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets and Systems, 113,(1) 81–109. doi: 10.1016/S0165-0114(99)00014-7
  • MacMillan, R. A., Martin, T. C., Earle, T. J. (2003). Automated analysis and classification of landforms using high-resolution digital elevation data: Applications and issues. Canadian Journal of Remote Sensing 29(5), 592–606. doi: 10.5589/m03-031
  • MacMillan, R. A., Shary, P. A. (2009). Landforms and Landform Elements in Geomorphometry. In T. Hengl, H. I. Reuter, Geomorphometry-Concepts, Software, Applications. Developments in Soil Science, 33, (pp. 227-254). Amsterdam: Elsevier
  • Mark, D.M. (1975). Geomorphometric parameters: A review and evaluation. Geografiska Annaler. Series A, Physical Geography 57(3/4), 165-177
  • Martins, F. M. G., Fernandez, H. M., Isidoro, J. M. G. P., Jordán, A., Zavala, L. (2016). Classification of landforms in Southern Portugal (Ria Formosa Basin). Journal of Maps, 12(3), 422–430. doi: 10.1080/17445647.2015.1035346
  • Mashimbye, Z. E., de Clercq, W. P., Van Niekerk, A. (2014). An evaluation of digital elevation models (DEMs) for delineating land components. Geoderma, 213, 312–319. doi: 10.1016/j.geoderma.2013.08.023
  • Miller, B. A., Schaetzl, R. J. (2015). Digital classification of hillslope position. Soil Science Society of America Journal 79(1),132-145. doi:10.2136/sssaj2014.07.0287
  • Milne, J. D. G., Clayden, B., Singleton, P. L., Wilson, A. D. (1995). Soil Description Handbook. Landcare: Manaaki Whenua Press
  • Minar, J., Evans, I.S. (2008). Elementary forms for land surface segmentation: The theoretical basis of terrain analysis and geomorphological mapping. Geomorphology, 95(3-4), 236-259. doi: 10.1016/j.geomorph.2007.06.003
  • Moravej, K., Karimian Eghbal, M., Toomanian, N., Shahla Mahmoodi, S. (2012). Comparison of automated and manual landform delineation in semi detailed soil survey procedure. African Journal of Agricultural Research 17(7): 2592-2600. doi: 10.5897/AJAR11.728
  • Morgan, J. M., Lesh, A. (2005, July). Developing landform maps using ESRI’s model builder. Proceedings of the 2005 ESRI International User Conference, 25–29, San Diego, CA
  • Norini, G., Zuluaga, M. C., Ortiz, İ. J., Aquino, D. T., Lagmay, A. M. F. (2016). Delineation of alluvial fans from digital elevation models with a GIS algorithm for the geomorphological mapping of the Earth and Mars. Geomorphology, 273(15), 134–149. doi: 10.1016/j.geomorph.2016.08.010
  • O'Caliaghan, J. F., Mark, D. M. (1984). The extraction of drainage networks from digital elevation data. Computer Vision, Graphics and Image Processing, 28(3), 323-344. doi: 10.1016/S0734-189X(84)80011-0
  • Pennock, D. J., Zebarth, B. J., DeJong, E. (1987). Landform classification and soil distribution in hummocky terrain, Saskatchewan, Canada. Geoderma, 40(3-4), 297-315. doi: 10.1016/0016-7061(87)90040-1
  • Peucker, D., Douglas H. (1975). Detection of surface-specific points by local parallel processing of discrete terrain elevation data. Computer Graphics and Image Processing, 4(4), 375-387. doi: 10.1016/0146-664X(75)90005-2
  • Pike, R. J. (1988). The geometric signature: Quantifying landslide-terrain types from digital elevation models. Mathematical Geology, 20(5), 491–511.
  • Pelfini M., Bollati I. (2014). Landforms and geomorphosites ongoing changes: Concepts and implications for geoheritage promotion. Quaestiones Geographicae 33(1), 131–143, doi: 10.2478/quageo-2014-0009, ISSN 0137-477X
  • Piloyan, A., Konečný, M. (2017). Semi-automated classification of landform elements in armenia based on SRTM DEM using k-means unsupervised classification. Quaestiones Geographicae, 36(1), 93-103. doi:10.1515/quageo-2017-0007
  • Prima, O. D. A., Echigo, A., Yokoyama, R., Yoshida, T. (2006). Supervised landform classification of Northeast Honshu from DEM-derived thematic maps. Geomorphology, 78(3-4), 373-386. doi: /10.1016/j.geomorph.2006.02.005
  • Romstad, B. (2001). Improving relief classification with contextual merging. In J. T. Bjørke, H. Tveite, Proceedings of the 8th Scandinavian Research Conference on Geographical Information Science, 3-14. Ås, Norway
  • Romstad, B., Etzelmüller, B. (2012). Mean-curvature watersheds: a simple method for segmentation of a digital elevation model into terrain units. Geomorphology, 139–140, 293–302. doi: 10.1016/j.geomorph.2011.10.031
  • Ruhe, R. V. (1960). Elements of the soil landscape, In Trans. 7th int. Congr. Soil Sci. 4 (pp. 165-170)
  • Schmidt, J., Hewitt, A. (2004). Fuzzy land element classification from DTMs based on geometry and terrain position. Geoderma 121(3-4), 243-256. doi. 10.1016/j.geoderma.2003.10.008
  • Seijmonsbergen, A. C., Hengl, T., Anders, N. S. (2011). Semi-automated identification and extraction of geomorphological features using digital elevation data. In M. J. Smith, P. Paron, J. S. Griffiths (Eds.), Geomorphological Mapping (pp. 297–335). Amsterdam: Elsevier
  • 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., Sharaya L. S., Mitusov A. V. (2002). Fundamental quantitative methods of land surface analysis, Geoderma, 107(1-2), 1 –32. doi: 10.1016/S0016-7061(01)00136-7
  • Skidmore A. K. (1990). Terrain position as mapped from a gridded digital elevation model. International Journal of Geographical Information Systems, 4(1), 33-49. doi: 10.1080/02693799008941527
  • Speight, J. G. (1974). A parametric approach to landform regions. Progress in Geomorphology, Special Publication, 7 (pp. 213-230). Oxford: Alden Press
  • Speight, J.G. (1990). Landform. In McDonald, et al. (Eds.), Australian Soil and Land Survey Field Handbook (pp. 9-57). Melbourne: Inkata Press
  • Stepinski, T. F., Bagaria, C. (2009). Segmentation-based unsupervised terrain classification for generation of physiographic maps, IEEE Geoscience and Remote Sensing Letters, 6(4), 733-737. doi: 10.1109/LGRS.2009.2024333
  • Tarboton, D. G., Ames, D. P. (2001, May). Advances in the mapping of flow networks from digital elevation data. World Water and Environmental Resources Congress, Orlando, Florida
  • Tunçay, T., Bayramin, İ., Öztürk, H. S., Kibar, M., Başkan, O. (2014). The use of remote sensing and geographic İnformation system techniques to determine relationships between land use and landform. Toprak Su Dergisi, 3(2), 124-136
  • van Asselen, S., Seijmonsbergen, A. C. (2006). Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM. Geomorphology, 78(3-4), 1309-320. doi: 10.1016/j.geomorph.2006.01.037
  • Ventura, S. J., Irvin, B. J. (2000). Automated landform classification methods for soil landscape studies. In J. P. Wilson & J. C. Gallant (Eds.), Terrain Analysis Principals and Applications (pp. 245-294). New York: John Wiley & Sons
  • Verhagen, P., Dragut, L. (2012). Object-based landform delineation and classification from DEMs for archaeological predictive mapping. Journal of Archaeological Science, 39(3), 698–703. doi: 10.1016/j.jas.2011.11.001
  • Weiss, A. (2001). Topographic Position and Landforms Analysis. ESRI User Conference. San Diego, CA
  • Wysocki, D. A., Schoeneberger, P. J., LaGarry, H. E. (2000). Geomorphology of soil landscapes. In P. M. Huang, Y. Li, M. E. Sumner (Eds.), Handbook of Soil Sciences: Properties and Processes (pp. 5-40). Boca Raton: CRC Press
  • Zevenbergen, L.W., Thorne, C.R., 1987. Quantitative analysis of land surface topography. Earth Surface Processes and Landforms, 12, 47–56. doi: 10.1002/esp.3290120107
  • Zhao, W. F., Xiong, L. Y., Ding, H., Tang, G. (2017). Automatic recognition of loess landforms using Random Forest method. Journal of Mountain Science 14(5). 885-897. doi: 10.1007/s11629-016-4320-9
  • Wood J. (1996). The Geomorphological Characterisation of Digital Elevation Models. Ph.D. Thesis. University of Leicester, England
There are 75 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Fatmagül Kılıç Gül 0000-0003-3467-9288

Publication Date June 22, 2018
Submission Date March 23, 2018
Published in Issue Year 2018 Issue: 36

Cite

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. June 2018;(36):15-26. doi:10.26650/JGEOG409177
Chicago Kılıç Gül, Fatmagül. “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”. Journal of Geography, no. 36 (June 2018): 15-26. https://doi.org/10.26650/JGEOG409177.
EndNote Kılıç Gül F (June 1, 2018) Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi. Journal of Geography 36 15–26.
IEEE F. Kılıç Gül, “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”, Journal of Geography, no. 36, pp. 15–26, June 2018, doi: 10.26650/JGEOG409177.
ISNAD Kılıç Gül, Fatmagül. “Jeomorfometri-Yeryüzü Şekillerinin Otomatik Belirlenmesi”. Journal of Geography 36 (June 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, no. 36, 2018, pp. 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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