• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.13-24
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• 2000

SAR imagery usually reveals the influence of antenna look-direction on the delineation of geological structures. In this study, the look-direction bias in SAR image is quantitatively analyzed specifically for geological lineament study. Geologic lineaments are estimated using both Landsat TM and JERS-1 SAR images over the study area to quantitatively compare and analyze the look-direction bias in the SAR image. The standard geologic lineaments in the study area are established from lineaments estimated from TM images, field mapping, and fault lines in a published geologic map. The results show that lineaments normal to radar look-direction are extremely well enhanced while those parallel to look-direction are less visible as expected. However, certain lineaments even parallel to radar look-direction can still be detectable in a favorable topographic condition. Compared with TM image, the total number of detected lineaments in each direction in the SAR image increases or decreases ranging from 33% to 159% in length and from 28% to 187% in occurrence. The ratio of lineaments in SAR image to those in TM image with respect to direction can be fitted by a cosine function. The fitted function indicates that geological lineament is more easily detected in SAR image than in TM image within about $\pm$50$^{\circ}$ normal to radar look-direction. And lineaments with limited extension appear to be more sensitive to the look direction bias effect.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.49-62
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• 1994

Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

• Korean Journal of Remote Sensing
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• v.12 no.2
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• pp.139-154
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• 1996

In order to evaluate the sensor`s look direction bias in the Landsat TM image and to estimate trends of primary geological lineaments, we have attempted to systematically compare lineaments in TM image, relief shadowed DEM's, and actual lineaments of geologic and topographic map through the Hough transform technique. Hough transform is known to be very effective to estimate the trend of geological lineaments, and help us to obtain the true trends of lineaments. It is often necessary to compensate the preferential enhancements of terrain lineaments in a TM image occurred by to look direction bias, and that can be achieved by utilizing an auxiliary data. In this study, we have successfully adopted the relief shadowed DEM in which the illuminating azimuth angle is perpendicular to look direction of a TM image for assessing true trends of geological lineaments. The results also show that the sum of four relief shadowed DEM's directional components can possibly be used as an alternative. In Euiseong-gun area where Sindong Group and Mayans Group are mainly distributed, geological lineaments trending $N5^{\circ}$~$10^{\circ}$W are dominant, while those of $N55^{\circ}$~$65^{\circ}$ W are major trends in Cheongsong-gun area where Hayang Group, Yucheon Group and Bulguksa Granite are distributed. Using relief shadowed DEM as an auxiliary data, we found the $N55^{\circ}$~$65^{\circ}$ W lineaments which are not cleanly observed in TM image over Euiseong-gun area. Compared with the trend of Gumchon and Gaum strike-slip faults, these lineaments are considered to be an extension of the faults. Therefore these strike-slip faults possibly extend up to Sindong Group in the northwest parts in the study area.

• Economic and Environmental Geology
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• v.32 no.1
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• pp.19-31
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• 1999

In this study, we have estimated lineaments in the Euiseong area, Kyungbuk Province, from Landsat TM by applying the algorithm developed by Kim and Won et al. which can effectively reduce the look direction bias associated with the Sun's azimuth angle. Fratures over the study area were also mapped in the field at 57 selected sites to compare them with the results from the satellite image. The trends of lineaments estimated from the Landsat TM images are characterized as $N50^{\circ}$~70W, NS~$N10^{\circ}$W, and $N10^{\circ}$~$60^{\circ}$E trends. The spatial distribution of lineaments is also studied using a circular grid, and the results show that the area can be divided into two domains : domain A in which NS~$N20^{\circ}$E direction is dominant, and domain B in which west-north-west direction is prominent. The trends of lineaments can also be classified into seven groups. Among them, only C, D and G trends are found to be dominant based upon Donnelly's nearest neighbor analysis and correlations of lineament desities. In the color composite image produced by overlaying the lineament density map of these C-, D-, and G-trends, G-trend is shown to be developed in the whole study area while the eastern part of the area is dominated by D-trend. C-trend develops extensively over the whole are except the southeastern part. The orientation of fractures measured at 35 points in the field shows major trends of NS~$N30^{\circ}$E, $N50^{\circ}$~$80^{\circ}$W, and N80$^{\circ}$E~EW, which agree relatively well with the lineaments estimated form the satellite image. The rose diagram analysis fo field data shows that WNW-ESE trending discontinuities are developed in the whole area while discontinuities of NS~$N20^{\circ}$E are develped only in the estern part, which also coincide with the result from the satellite image. The combined results of lineaments from the satellite image and fracture orientation of field data at 22 points including 18 minor faults in Sindong Group imply that the WNW-ESE trend is so prominent that Gumchun and Gaum faults are possibly extended up to the lower Sindong Group in the study area.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.