Filtering of satellite images in geological lineament analyses: an application to a fault zone in Central Turkey

Lineament extraction and analysis is one of the routines in mapping large areas using remotely-sensed data, most of which is the satellite images. In this study, we aimed to test different lineament extraction techniques including single band, multiband enhancements and spatial domain filtering techniques. A fast algorithm has been developed for time and cost limited surveys in an area with known dominant and/or any selected orientation of lineaments. During the study for single band analysis, histogram equalization and stretching, for multiband, Principal Components Analysis (PCA) and for spatial domain filtering Prewitt and Sobel filters are utilized. Furthermore, we have developed a new algorithm which consists of a combination of large smoothing filters and gradient filters, in order to get rid of the artificial lineaments which are out of interest and to determine discontinuous and/or closely spaced regional lineaments. The results are as follows; the number of lineaments and their total lengths are 218 285.3 km using the single band; 255 343.9 km in multiband enhancements, and 347 644.9 km in the combination of spatial domain filtering including our algorithm. The 59.17 per cent increase in the number of lineaments and the 126.04 per cent increase in the total lengths indicate that a combination of spatial domain filters is the most cost-time efficient algorithm in lineament analyses.


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Tutsak, Ersin; Özsoy, Emin; Department of Physical Oceanography (2012)
Time series and spectral analyses are applied to meteorological data (wind velocity, air temperature, barometric pressure) and sea level measurements from a total of 13 monitoring stations along the Turkish Coast. Analyses of four-year time series identify main time scales of transport and motion while establishing seasonal characteristics, i.e. distinguishing, for instance, between winter storms and summer sea-breeze system. Marine flow data acquired by acoustic doppler current pro filers (ADCP) is also a...
Investigation of Terrestrial Laser Scanning Reflectance Intensity and RGB Distributions to Assist Construction Material Identification
Hassan, Muhammad Usman; Akçamete Güngör, Aslı; Akgül, Çağla (2017-07-07)
t: Terrestrial Laser Scanning (TLS) allows collection of dense 3D point cloud data that captures a structure's as-is conditions. The geometric information from the collected data could be used to generate a 3D-model of the structure. However, the generated model usually lacks functional information - a basic requirement for a semantically rich information model. Some of the functional information (such as cost, mechanical and thermal performance) could be derived if the material used in a particular geometr...
Dimension reduction using global and local pattern information-based maximum margin criterion
Sakarya, Ufuk (2016-07-01)
Dimension reduction is an important research area in pattern recognition when dealing with high-dimensional data. In this paper, a novel supervised dimension reduction approach is introduced for classification. Advantages of using not only global pattern information but also local pattern information are examined in the maximum margin criterion framework. Experimental comparative results in object recognition, handwritten digit recognition, and hyperspectral image classification are presented. According to ...
Analysis of Airborne LiDAR Point Clouds With Spectral Graph Filtering
Bayram, Eda; Frossard, Pascal; Vural, Elif; Alatan, Abdullah Aydın (Institute of Electrical and Electronics Engineers (IEEE), 2018-08-01)
Separation of ground and nonground measurements is an essential task in the analysis of light detection and ranging (LiDAR) point clouds; however, it is challenge to implement a LiDAR filtering algorithm that integrates the mathematical definition of various landforms. In this letter, we propose a novel LiDAR filtering algorithm that adapts to the irregular structure and 3-D geometry of LiDAR point clouds. We exploit weighted graph representations to analyze the 3-D point cloud on its original domain. Then,...
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Musa, Mohamed Elhafiz Mustafa; Atalay, Mehmet Volkan; Department of Computer Engineering (2003)
In pattern recognition, when data has different structures in different parts of the input space, fitting one global model can be slow and inaccurate. Learning methods can quickly learn the structure of the data in local regions, consequently, offering faster and more accurate model fitting. Breaking training data set into smaller subsets may lead to curse of dimensionality problem, as a training sample subset may not be enough for estimating the required set of parameters for the submodels. Increasing the ...
Citation Formats
M. L. Süzen, “Filtering of satellite images in geological lineament analyses: an application to a fault zone in Central Turkey,” INTERNATIONAL JOURNAL OF REMOTE SENSING, pp. 1101–1114, 1998, Accessed: 00, 2020. [Online]. Available: