HR: 17:00h
AN: T34A-03    [Abstracts]
TI: Surface Deformation Analysis by Means of Fractal Dimension and Lacunarity Approaches
AU: * Mahmood, S
EM: amerpqakistan@gmail.com
AF: Remote Sensing Group, Institute of Geology, B.von cotta str.2 TU Freiberg, Freiberg, Sa 09599, Germany
AU: Shahzad, F
EM: geoquaidian@gmail.com
AF: Remote Sensing Group, Institute of Geology, B.von cotta str.2 TU Freiberg, Freiberg, Sa 09599, Germany
AU: Glaouguen, R
EM: glaoguen@geo.tu-freiberg.de
AF: Remote Sensing Group, Institute of Geology, B.von cotta str.2 TU Freiberg, Freiberg, Sa 09599, Germany
AB: Fractals and scaling laws such as river networks and runoff series are abundant in nature, and geometry of river networks and basins is a superb example of this. The unrelenting competition between tectonics, surface uplift and erosional processes on the earth has resulted in a variety of drainage patterns by linearizing the normal flow patterns of river networks. These patterns are fractals and their variable spatial distribution can be used to examine the vulnerability of surface deformation. At first we extract the drainage network from Shuttle Radar Topographic Mission's digital elevation data (SRTM-90m) using D8 algorithm. We convert the drainage network into a binary image where the area of interests (AOIs) i.e. drainage are represented with pixels value of 1. The fractal dimension (D) analysis using Box Counting method is used to identify the anomalous drainage patterns of vulnerable sites. We prepare a D distribution map using a moving window of 1 arc sec. by 1 arc sec. on the binary image of river network. The space occupied by AOIs reveals variable distribution of D and lower values suggest that the drainage pattern has become linearized due to the influence of tectonics and surface processes. We use lacunarity analysis using Gliding Box method to see the relative vulnerability as two AOIs can have similar D values. The AOIs with a high lacunarity of drainage pattern are more vulnerable than AOIs with lower lacunarity values. Three AOIs i.e. Vanch and Yazgulem Basin (VYB) in northwestern Pamir, Tirch Mir Fault Zone (TMFZ) in Hindukush region, and Central Badakhshan (CB) with high vulnerability and three sites i.e. Central Pamir, Shiveh Lake Region in Afghanistan and Darvaz Fault Zone with medium vulnerability were identified using fractal dimension. The lacunarity analysis was used to diferentiate between the relative vulnerability of these AOIs. Results from Pyanj river network and adjacent areas show that VYB, TMFZ, and CB have relatively high vulnerability to surface deformation. The fractal dimensions derived from two different drainage patterns may be not sufficient for distinguishing them genetically. For this reason, lacunarity analysis is applied as a useful tool for the distinction between different textural patterns with similar fractal dimension.
DE: 0480 Remote sensing
DE: 0540 Image processing
DE: 1209 Tectonic deformation (6924)
DE: 1856 River channels (0483, 0744)
DE: 4440 Fractals and multifractals
SC: Tectonophysics [T]
MN: 2009 Joint Assembly