Morphological and geomorphological analysis

Morphological and geomorphological analysis follow similar processes, condensed in this study as; visualisation, analysis, interpretation, classification, and reconstruction.

Visualisation

DEM, aerial photographs and satellite imagery, provide a basis to begin analysis and interpretation, commonly through draping aerial photographs over DEM models in Geographic Information Systems (GIS) software (i.e. ArcGIS Version 9.2, 3D visualisation application ArcScene). These models can be viewed from multiple perspectives, lighting, shading and layering.

Analysis

Analysis is typically performed within GIS software (i.e. ArcGIS Version 9.2, ArcMap) to commonly produce:

• Slope maps and slope frequency histograms, enable recognition of slope (degree) in an area (Figure 2.1A) with the histogram representing the

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occurrence of slope degrees vs. area. The steepness of the terrain is depicted through the colour intensity (i.e. the steeper the slope the brighter the colour).

Figure 2.1. Geomorphic analysis of Nevado de Toluca volcano, Mexico (Norini et al., 2004). A) Slope map and slope frequency histogram, orange colouration depicts the steepest slopes. B) Aspect map and aspect map legend, indicating the orientation a slope faces.

• Slope aspect maps (Figure 2.1B) display the direction a slope faces. Aspect maps enable easy recognition of ridgelines, valleys, and lineaments due to colour changes.

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• Drainage network analyses enable the simple recognition of current streams and valleys (i.e. Favalli and Pareschi, 2004), while the use of a Watershed tool defines catchment areas, with the intersection point of catchments orienting along ridgelines.

Interpretation

Interpretation is typically performed within GIS software (i.e. ArcMap 9.2) or computer drawing programmes (i.e. CorelDRAW X3). Through further analysis of GIS derived data key features or factors interpreted:

• Lineaments (Figure. 2.2) are commonly associated with faults (i.e. Jordan et al., 2005; Karàtson et al., 2006) or volcanic rifts (i.e. Norini and Seymour, 2006).

• Valley and ridge patterns, are closely associated to lineaments, these features will often radiate about a volcanic landform due to incision (Norini et al., 2004;

Szѐkely and Karàtson, 2004), or in the case of a caldera trend towards the central depression (Kouli and Seymour, 2006).

• Geomorphic features, for example major collapse scars, volcanic edifices and craters, escarpments, and canyons (i.e. Favalli et al., 2005)

• Cross sections of major structures to identify key features (i.e. crater rims, caldera collapse, lava domes or eruptive fractures (Norini et al., 2004; Kouli and Seymour, 2006)).

CHAPTER 2:PCTIMAGE ANALYSIS AND DEGRADATION OF LYTTELTON VOLCANO 29 Figure 2.2. Lineament and structural analysis on Nevado de Toluca Volcano, Mexico (Norini et al, 2004).

A) Identified lineament groups: a) NNW-SSE; b) NW-SE; c) NE-SW; d) NNE-SSW. B) Recognised fault structures: a) Taxco-Querataro fault system; b) Tenago fault; c) Zacango fault; d) NNE-SSW faulting structure.

Classification

Classification is dependent on the individual study, varying from geomorphic styles (i.e.

Favalli et al., 2005) to broad classification of landscape modifications (Szѐkely and Karàtson, 2004).

• Geomorphic signatures are commonly used within active to relatively unmodified (minimal erosion) volcanic landforms, where the resulting geomorphology is clearly identifiable to a source and a process (i.e. a sector collapse scar on a sub-aerial volcano, to the hummocky surface and more distal volcanic fans offshore (Aeolian Islands, Italy, Favalli et al., 2005).

• Lineaments previously recognised can then be classified to their origin (Figure 2.2), with two common styles, faulting or eruptive fissure (dyking). Commonly valley and ridge trends are incorporated into this analysis with the orientation

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of these commonly being affected by the surrounding tectonics or the surface geology (Norini et al., 2004; Jordan et al 2005; Karàtson et al., 2006; and Kouli and Seymour, 2006).

• Domains / sectors were defined by Norini et al (2004) on slope and aspect distribution maps, DEM’s and perspective views and surface texture (Figure 2.3). Szѐkely and Karàtson (2004) defined sectors based on ridge orientations (ultimately catchment regions).

Figure 2.3. Domains of Nevado de Toluca volcano, Mexico (Norini et al., 2004). 1)irregular morphology with numerous flank ruptures. 2) Nevado de Toluca cone. 3) North-eastern lower flank of the volcanic edifice. 4) Southern DEM portion, limited by a more or less sharp slope break. 5) north-westernmost DEM portion.

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Geological Models

The result or synthesis of the aforementioned analyses are broad, somewhat schematic geological models (i.e. Karàtson et al., 2005), or classifications of volcanic landforms to a specific region (Favalli et al., 2005). Szѐkely and Karàtson (2004) however further analysed their data, producing a polar coordinate transformed map (PCT map), a DEM image of a once conical volcanic structure rotated and transformed about a proposed centre of volcanism (Figure 2.4).

Figure 2.4. Transformation of conical volcanic features of a DEM to a PCT map. A) Schematic cone volcano with both radial and non radial valley and ridges. B) PCT map, crater rim displayed along the bottom axis, parallel to each other and perpendicular to crater rim are radial ridges, whereas the non-radial valley is at an oblique angle to the crater rim.

A polar Coordinate Transformed map (PCT’s) is the result of transforming DEM data around a single point; in this instance proposed centres of volcanism (Szѐkely and Karàtson, 2004). A polar coordinate transformed map images any concentric and radial features to a radius-axis parallel or angle-axis parallel feature, while any non-concentric and non-radial features will become scattered (Figure 2.4). The data for a PCT image is obtained by running an Avenue script in ArcView GIS 3.2 (details in Szѐkely and Karàtson, 2004). The script requires inputs of the centre of volcanism (Cartesian coordinates), the volcano radius (radial distance), and the number of divisions required (relating to overall resolution). The script produces a text file with three categories (angular coordinates, radial coordinates, and angular resolution). This

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data is then converted to a grid file and displayed in Surfer 8 (a contouring and 3D surface mapping program produced by Golden Software) as shaded relief images.

Figure 2.5. Digital elevation model (DEM) of Mt St Helens and transformed PCT map. A) Mt St Helens with the defined 1980’s sector collapse amphitheatre and circular crater rim. B) PCT map of Mt St Helens, sector collapse depression is defined by a break in the circular crater rim, almost parallel to the base line, which represents the volcanic centre.

The resulting image presents a transformed DEM as a rectangle, with the bottom axis representing the single point of rotation, or centre of volcanism. This image presents features of the volcano, which either support the proposed centre of volcanism or disprove the hypothetical centre. The production of these images also enables the further recognition of sectors of the volcano, for example:

1) Related to the centre of volcanism (i.e. radial and concentric features);

2) Related to the centre of volcanism but are modified through later volcanism or erosion; or

3) Unrelated to the proposed volcanic centre. Szѐkely and Karàtson (2004) produced an example PCT of Mt St Helens (Figure 2.5) where a defined sector

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collapse depression (1980 collapse event) is evident, as well as the near-circular caldera rim and radiating valley systems.

Szѐkely and Karàtson’s (2004) study highlighted PCT maps as a useful tool in identifying catastrophic collapse regions on both highly eroded (Borzsony Mountains, Hungary) and recent volcano’s (Mt St Helens, USA; Figure 2.5; Szѐkely and Karàtson, 2004). As catastrophic collapse is proposed to have occurred throughout the evolution of Lyttelton Volcano (Shelley, 1987; 1992; Sewell et al., 1992), the methodology of producing a PCT map in the identification of both catastrophic collapse and associated geomorphic signatures on a large conical volcano is undertaken.