LANDFORM ANALYSIS USING TERRAIN ATTRIBUTES. A GIS APPLICATION ON THE ISLAND OF IKARIA (AEGEAN SEA, GREECE)

Transcription

1 Annals of Valahia University of Targoviste. Geographical Series (2017), 17(1): DOI: /avutgs ISSN (Print): , ISSN (Online): Copyright by Department of Geography. Valahia University of Targoviste LANDFORM ANALYSIS USING TERRAIN ATTRIBUTES. A GIS APPLICATION ON THE ISLAND OF IKARIA (AEGEAN SEA, GREECE) Athanasios Skentos 1, Anagnostopoulou Ourania 2 1 Mott Macdonald Ltd, Sydenham Road, CR0 2EE, Croydon (UK) athanasios.skentos@mottmac.com 2 Faculty of Geology & Geoenvironment - University of Athens, Panepistimiopolis, Ilissia, Greece anagnostopoulourania@gmail.com Abstract The main objective of this study is to classify the landforms of Ikaria Island by conducting morphometric analysis. The whole classification process is based on the calculation of the Topographic Position Index (TPI). The delivered TPI landform classes are spatially correlated with the geology, slope, valley depth and the topographic ruggedness of the island. The results of this study indicate the presence of two distinctive landform units, affected mainly by the local geological setting. Keywords: Landform classification, Geomorphometry, Topographic Positioning Index, Aegean Sea 1. INTRODUCTION Over the past few years, the implementation of automated techniques for landform classification has become very common among the scientific society (De Reu et al., 2013; Grohmann and Riccomini, 2009; Ilia et al., 2013; Rigol-Sanchez, et al. 2015; Tagil and Jenness, 2008). What is more, the application of such techniques is not limited to geosciences. In particular, landform classification has been proved a valuable processing tool for studies related to archaeology, ecology, agriculture, forestry, rural planning, hazards, etc. (Ho and Umitsu, 2011; Hoersch et al., 2002; Macmillan et al., 2003; Martin-Duque et al., 2003; Mcnab, 1993; Verhagen and Dragut, 2012). Concerning geomorphological research, studying the morphometric parameters of the terrain is of utmost significance for the landform interpretation. In this study, the landforms of Ikaria are classified by calculating Topographic Position Index (TPI). TPI is derived by conducting geometrical and topological analysis using local statistics (user-defined calculus area). Since both the geology and the ensuing topography determine significantly the landscape, the delivered TPI landform classes are related to the geological setting and terrain attributes (slope, valley depth, ruggedness) for further interpretation. 2. STUDY AREA AND GEOLOGICAL SETTING Ikaria Island is located at the eastern part of the Aegean Sea, covering an area of 250km 2 (Fig. 1). From a geomorphological point of view, the study area can be divided as follows; the eastern part dominated by Atheras Mount, the plain with low hills of Messaria at the center, and the western part featuring Pezi upland (Fig. 1). In general, the gradient of the relief is much lower close to the south coast and the hydrographic network much more developed along the north flank of the island (Stiros et al., 2011). Pezi, Chalaris, Charakas and Voutsides are the main rivers of Ikaria, draining the area to the northern shore (Fig. 1). 90

2 The presented complex geology of the island is due to its geotectonic position (Bozkurt and Oberhansli, 2001; Ktenas and Marinos, 1969). Stiros et al., (2011) suggest that Ikaria s geological formations correspond to an anticline with a NE-trending axis. According to the geological map of Photiades (2005), the study area may be divided in three distinctive geological patterns. Figure 1. Location map and topography of Ikaria Island featuring main rivers In particular, the western part of the island is dominated by granites, interrupted only by in situ Holocene deposits (Fig. 2). Messaria region (at the center of the island) and the easternmost part of the island consist of carbonate metamorphic rocks and schists. Moreover, Neogene formations and Holocene deposits appear mainly at the end of the valleys, just before the beach front (Fig. 2). Lastly, the eastern part of the island is dominated by gneisses, followed by granodiorites and small extents of Holocene deposits (allocated at the mouth of the rivers). Beyond these three distinctive patterns, a significant extent of molassic ophiolithic formation appears at the easternmost part of the island (Fig. 2). Figure 2. Simplified geological map of Ikaria Island based on PHOTIADES (2005) 91

3 3. METHODOLOGY 3.1 Calculating terrain attribute A high resolution DEM (25m 2 pixel size) produced by large scale topographic data, is used in order to compute the following topographic parameters; slope, valley depth, terrain ruggedness and TPI (Fig. 3). QGIS and SAGA GIS open-software are used for applying the appropriate algorithms. The pre-processing procedure includes a 25-meter radius Gaussian filter to smoothen the grid data, and the application of the Planchon/Darboux algorithm to fill DEM s depressions (Planchon and Darboux, 2001). Slope expresses the inclination of the surface of the terrain from either the horizontal or a local base level (Senthilvelan, 2015).In this paper, slope is categorized in 5 classes (Fig. 3A). Valley depth refers to the vertical distance to a channel network base level (Fig. 3B). The calculation algorithm for the specific index consists of two major steps; Interpolation of a channel network base level elevation, and subtraction of the channel network base level from the original elevations (Conrad et al., 2015). The Terrain Ruggedness Index (TRI) provides a rapid, objective measure of terrain heterogeneity (Riley et al., 1999). The algorithm calculates the sum change in elevation between a grid cell and its eight neighbor grid cells. Therefore, an increased TRI shows increased local relief heterogeneity (Fig. 3C). Finally, Topographic Position Index (TPI) is defined as the difference between the elevation at a cell and the average elevation in a cell that surrounds it within a predetermined radius (Weiss, 2001). TPI values above zero show locations that are higher than the average of the local window e.g. ridges. In contrast, negative TPI values represent locations that are lower e.g. valleys (Fig. 3D). Lastly, TPI values near zero are either flat areas (where the slope is near zero) or areas of constant slope (where the slope of the point is significantly greater than zero). Figure 3. DEM derived gradients of Ikaria Island (slope, valley depth, TRI, TPI) 92

4 3.2 TPI Landform Classification Therefore, TPI values calculated from two different neighbourhood sizes (small and large ones) provide more detailed information about the general shape of the landscape rather than the TPI values from just a single neighbourhood. Additionally, complex landforms may be identified (Tagil and Jenness, 2008). For the purpose of this study, 10m and 200m radius are used for the determination of the two neighbourhoods TPI classification (Fig. 4). Furthermore, the high and low TPI values are distinguished by setting a threshold of ±1 STDEV. The neighbourhood size selected for a TPI implementation is of utmost significance since different sizes reveal different landforms (De Reu et al., 2013; Ilia et al., 2013; Verhagen and Dragut, 2012; Weiss, 2001). Figure 4. Landform Classification based on combined TPI (R1=10m & R2=200m) 4. RESULTS The percentage distribution of each landform class is shown on figure 5. In particular, open slopes are the dominant class of the study area (60.83%). Upper slopes cover an area of 10.40%, followed by U-shaped valleys (8.36%). All other landforms are calculated between 2.5-5% each, except local ridges and upland drainages who cover less than 1% of the total area. At this point it should be mentioned that the application of TPI on coastal environments (and in general next to the DEM boundaries) returns errors on the classified landforms. For instance, coasts with steep slopes appear as canyons. However, the affected covering area along the coast is quite small in contrast to the whole study area, resulting to limited influence on the delivering classes. Moreover, the scale of the study indicates that such anomalies should not be taken into consideration. According to table 1, open slopes hold the greatest geodiversity. Granites that cover almost the whole western part of the island are related with half of the open slopes of the study area (30.98% in total of 61.28%). Moreover, more than half of the Holocene deposits are characterized as open slopes (Table 1). 93

5 Figure 5. Percentage distribution of TPI delivered landform classes Table 1. Landform classes related to the geological setting Canyos, Deeply Incised Streams Midslope Drainages, Shallow Valleys Upland Drainages, Headwaters Holocene Granites Molassic ophiolitic formation Schist and marble alternations Recrystallized limestones and dolomites Marbles Gneisses Granodiorites Marine Neogene deposits 0,22% 1,86% 0,02% 0,43% 0,00% 0,30% 1,93% 0,11% 0,02% 4,89% 0,23% 2,09% 0,04% 0,36% 0,00% 0,24% 1,28% 0,11% 0,03% 4,38% 0,00% 0,07% 0,00% 0,02% 0,00% 0,03% 0,08% 0,01% 0,00% 0,22% Total U-shaped Valleys 0,41% 2,86% 0,02% 0,85% 0,00% 0,53% 3,32% 0,15% 0,03% 8,17% Plains 0,60% 1,39% 0,07% 0,17% 0,00% 0,05% 0,10% 0,00% 0,05% 2,43% Open Slopes 3,81% 30,98% 0,41% 5,46% 0,05% 3,58% 16,16% 0,69% 0,13% 61,28% Upper Slopes, Mesas 0,11% 4,14% 0,04% 1,11% 0,05% 0,84% 3,95% 0,16% 0,00% 10,39% Local Ridges, Hills in Valleys Midslope Ridges, Small Hills in Plains Mountain Tops, High Ridges 0,02% 0,27% 0,00% 0,06% 0,00% 0,03% 0,31% 0,02% 0,00% 0,71% 0,25% 2,03% 0,04% 0,40% 0,00% 0,25% 1,38% 0,12% 0,04% 4,50% 0,03% 1,21% 0,01% 0,33% 0,02% 0,28% 1,09% 0,08% 0,00% 3,04% Total 5,67% 46,90% 0,65% 9,18% 0,13% 6,14% 29,59% 1,43% 0,31% 100,00% These are mainly in situ deposits formed by the weathering of the granites. The metamorphic rocks, covering almost the whole of the eastern part of the island, are related approximately 50% to open slopes (Table 1). However, a significant percentage of metamorphic rocks are characterized as upper slopes, U-shaped valleys and deeply incised streams (Table 1). Taking everything into consideration, it appears to be that the study area could be divided into two landform units (Fig. 6). Landform Unit 1 (LU1) covers the western part of the island where granites are the dominant geological formation. Subsequently, Landform Unit 2 (LU2) covers the 94

6 eastern part of Ikaria, characterized by the presence of Atheras Mount. On the western part, the terrain seems to be smoother than the eastern one, since 30% of the slopes are classified from level to moderate (6 o -35 o ) (Fig. 6). In general, the central part of LU1 (upland) is characterized by near flat areas directed SW-NE that transform into steep slopes just before reaching the beachfront. In contrast, LU2, presents a more complex landscape associated mainly with the hydrographic network. Therefore, slopes ranging from level to moderate are just over 15%. Steep slopes are the dominant class reaching up to 68.04% (Fig. 6). Another index that shows the difference between LU1 and LU2 is the valley depth. Specifically, over 45% of the LU1 presents valleys that are no more than 20 meters deep (Fig. 6). In contrast, almost 70% of LU2 s valleys are deeper than 20 meters (Fig. 6). Concerning the ruggedness of the terrain, LU2 appears to be far more rugged than LU1 (Fig. 6). In particular, almost 55% of the LU2 area ranges from highly rugged to extremely rugged. Similar LU1 terrain characteristics are limited 37% (Fig. 6). Figure 6. Spatial distribution of Landform Units (LUs) and local gradient statistics (slope, valley depth, TRI) 5. DISCUSSION All in all, it seems that both the geological setting and the topography of the island are contributory factors to the geomorphological evolution of the study area. The landscape of LU1 is mainly affected by the granites that cover almost the whole area. Thus, there is no highly developed hydrographic network to boost the geomorphological processes of erosion and deposition. Therefore, the Holocene deposits are mainly associated with the weathering of granites (in situ deposition on upland or side debris along the cliffy shore). As a result, the landscape of LU1 is characterized by an extensive near flat upland directed smoothly to the NE seafront, and cliffy coasts on all other directions. In contrary, the geological setting of the LU2 consisting mainly of gneisses and carbonate metamorphic rocks, allowed the development of an extensive hydrographic network on both sides of Atheras Mount that shaped the local topography. In general, by the power of fluvial processes, the relief of LU2 is getting smoother when reaching the beachfront. 95

7 6. CONCLUSIONS It is an undeniable fact that automated landform classification is a powerful geoprocessing technique for geomorphometry. However, it should be stated that landform analysis can be succeeded only by relating the TPI calculated landform classes with the geological setting of the study area. Moreover, the DEM derived gradients (slope, valley depth, terrain ruggedness) contributed significantly to the interpretation of the landscape of Ikaria Island that was further divided in two landform units. Concerning future GIS applications, more DEM derived gradients such as local relief, curvature, topographic openness, etc. could be analysed for morphometric purposes. Lastly, the implementation of an algorithm based on pattern recognition (texture) rather than differential geometry (geomorphometry) may deliver more accurate results along the coast. REFERENCES Bozkurt, E. & Oberhansli, R. (2001), Menderes Massif (Western Turkey): structural, meta-morphic and magmatic evolution a synthesis. International Journal of Earth Sciences, 89:4, , Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fiscer, E., Gerlitz, L., Wehberg, J., Wichmann, V., Bohner, J. (2015), System for Automated Geoscientific Analyses (SAGA) v Geosci. Model Dev., 8, , De Reu, J., Bourgeois, J., Bats, M., Zwervaegher, A., Gerolini, V., De Smedt, P. Chu, W., Antrop, M., De Maeer, P., Finke, P.; Van Meirvenne, M., Verniers, J., Crombe, P. (2013), Application of the topographic position index to heterogeneous landscapes. Geomorphology, 186, 39-49, Martin-Duque, J. F., Godfrey, A. E., Pedraza, J., Diez, A., Sanz, M. A., Carrasco, R. M., Bodoque, J. M. (2003), Landform Classification for Land Use Planning in Developed Areas: An Example in Segovia Province (Central Spain). Environmental Management, 32:4, , Grohmann, C.H. & Riccomini, C. (2009), Comparison of roving-window and search-window techniques for characterizing landscape morphometry. Computers and Geosciences, 35:10, , 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, 31:3, , 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, 26:2-3, , 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, Vol 47, , Κtenas, Κ. & Μarinos, P. G. (1969), Ikaria island geology. ΙGME, vol. ΧΙΙΙ, VOL Geological and Geophysical research, Νο 2, Αthens. Macmillan, R. A., Martin, T. C., Earle, T. J., Mcnabb, T. H. (2003), Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues. Canadian Journal of Remote Sensing, 29:5, , Mcnab, W. H. (1993), A topographic index to quantify the effect of mesoscale landform on site productivity. Canadian Journal of Forest Research, 23:6, , 96

8 Planchon, O. & Darboux, F. (2001), A fast, simple and versatile algorithm to fill the depressions of digital elevation models. Catena, 46:2-3, , Photiades, A. (2005), Ikaria Island Sheet. Program for complying the geological map of Greece in scale 1: IGME editions. Riley, S.J., De Gloria, S.D., Elliot, R. (1999), A Terrain Ruggedness that Quantifies Topographic Heterogeneity. Intermountain Journal of Science, 5:1-4, Rigol-Sanchez, J.P., Stuart, N., Pulido-Bosch, A. (2015), ArcGeomorphometry: A toolbox for geomorphometric characterization of DEMs in the ArcGIS environment. Computers & Geosciences, 85:A, , Senthilvelan, A. (2015), A GIS Based Study on Slope Characteristics of Porandalar Watershed, Amaravathi Sub-Basin, Tamil Nadu. Indian Journal of Applied Research, 5:12, 1-3. Stiros, S. C., Laborel, J., Laborel-Deguen, F., Morhange, C. (2011), Quaternary and Holocene coastal uplift in Ikaria Island, Aegean Sea. Geodinamica Acta, 24:3-4, 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, 8:6, , Verhagen, P. & Dragut, L. (2012), Object-based landform delineation and classification from DEMs for archaeological predictive mapping. Journal of Archaeological Science, 39:3, , Weiss, A.D. (2001), Topographic position and landforms analysis. ESRI Users Conference, San Diego, CA, USA. 97