• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.163-169
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• 2011

This paper introduces a method about water line detection using SAR image. The method includes pre-processing of the SAR image with the threshold of the histogram to recognize the boundary between the water and the landmass area. Finally we applied the image differentiation to detect the water line in the SAR image. The TerraSAR-X and the Cosmo-SkyMed images, which are the high spatial resolution X-band SAR data, are used for the evaluation of our algorithm. The accuracy is verified over the stream line in urban area with the result from the Cosmo-SkyMed.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.79-90
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• 2017

Urban environment represent one of the most dynamic regions on earth. As in other countries, forests, green areas, agricultural lands are rapidly changing into residential or industrial areas in South Korea. Monitoring such rapid changes in land use requires rapid data acquisition, and satellite imagery can be an effective method to this demand. In general, SAR(Synthetic Aperture Radar) satellites acquire images with an active system, so the brightness of the image is determined by the surface roughness. Therefore, the water areas appears dark due to low reflection intensity, In the residential area where the artificial structures are distributed, the brightness value is higher than other areas due to the strong reflection intensity. If we use these characteristics of SAR images, settlement areas can be extracted efficiently. In this study, extraction of settlement areas was performed using TerraSAR-X of German high-resolution X-band SAR satellite and KOMPSAT-5 of South Korea, and object-oriented image classification method using the image segmentation technique is applied for extraction. In addition, to improve the accuracy of image segmentation, the speckle divergence was first calculated to adjust the reflection intensity of settlement areas. In order to evaluate the accuracy of the two satellite images, settlement areas are classified by applying a pixel-based K-means image classification method. As a result, in the case of TerraSAR-X, the accuracy of the object-oriented image classification technique was 88.5%, that of the pixel-based image classification was 75.9%, and that of KOMPSAT-5 was 87.3% and 74.4%, respectively.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.305-319
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• 2021

The overseas calibration sites such as Mongolia used for Korea Multi-purpose Satellite (KOMPSAT-5 or K5), have a disadvantage in that maintenance and repair costs are high and immediate response is difficult when an unexpected problem occurs. Accordingly, the necessity of establishing a domestic SAR calibration site was suggested, but the progress of related research is insignificant. In this paper, we investigated what conditions should be satisfied in terms of backscattering characteristics to construct a site for SAR satellite image quality evaluation and calibration. First of all, it was selected first by applying general indicators such as accessibility and availability among places recommended as satellite image calibration candidate sitesin Korea. Next, three places, site A (Goheung-gun, Jeollanam-do), site B (Jeonju-si, Jeollabuk-do), and site C (Daedeok Research Complex, Daejeon), were selected as the final candidates because they are relatively wide and easy to install AT or CR. Site A, located in Goheung-gun, Jeollanam-do, was best considered in terms of slope measurements, minimum site area to obtain ISLR, uniformity of DN values and backscatter coefficients, interference by strong reflectors, and backscatter clutter level.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.53-65
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and SAR interferometry(InSAR) for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. This study is associated with improvements of accuracy with consistency of image's characteristics between two different DEMs coming from stereoscopy for the optical images and interferometry for SAR images. The MWD(Multiresolution Wavelet Decomposition) and HPF(High-Pass Filtering), which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. DEM fusion is tested with two sets of SPOT and ERS-l/-2 satellite imagery and for the analysis of results, DEM generated from digital topographic map(1 to 5000) is used. As a result of an integration of DEMs, it can more clearly portray topographic slopes and tilts when applying the strengths of DEM of SAR image to DEM of an optical satellite image and in the case of HPF, the resulting DEM.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.368-368
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• 2008

Oil spills are a principal factor of the ocean pollution. The complicated problems involved in detecting oil spills are usually due to varying wind and sea surface condition such as ocean wave and current. The Hebei Spirit accident was happened in the west sea ($36^{\circ}$41'04" N, $126^{\circ}$03'12" E) near about 8 km distant from Tae-An, Korea on December 7, 2007. The aim of this work is to improve the detection and classification performance in order to define a more accurate training set and identifying the feature of oil spill region. This paper deals with an optimization technique for the detection and classification scheme using multi-frequency and multi-polarization SAR and optical image data sets of the oil spilled sea. The used image data are the ENVISAT ASAR WS and Radarsat-1 of C-band and ALOS PALSAR of L-band SAR data and KOMPSAT-2 optical images together with meteorological or oceanographic data. Both the theory and the experimental results obtained are discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.117-125
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• 2014

Korea's first X-band SAR satellite KOMPSAT-5 has been launched in 2013, so the research related to the X-band SAR satellite image is required to increase the utilization of KOMPSAT-5. In this study, we generated a DEM(Digital Elevation Model) using X-band SAR satellite images based on three methods which are InSAR, radargrammetry and RPC(Rational Polynomial Coefficients), and evaluated the performance of each methods. The four stripmap mode TerraSAR-X images taken in Daejeon were used to generate DEM, and accuracy was evaluated using DEM by IKONOS RPC. As results, DEM produced by the InSAR showed the highest accuracy. Also, we knew that RPC could be effective method if you want to create a large area DEM which contains the various elevation.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.243-253
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• 2009

For the last 14 years, space-borne satellite SAR system such as RADARSAT-1, ERS-2, and ENVISAT ASAR have provided a continuous observation over the ocean. However, the data acquired from those systems were limited to C-band frequency until the advent of the first spacebome German X-band SAR system TerraSAR-X in 2007. Korea is also planning to launch the nation's first X-band SAR satellite (KOMPSAT-5) in 2010. It is timely and necessary to develop X-band models for estimating geophysical parameters from these X-band SAR systems. In this study, X-band wind retrieval model was investigated and developed based on numerical ocean scattering model (radar backscattering model and hydrodynamic interaction model). Although these models have not yet been tested and validated for broad ranges of wind conditions, the estimated wind speeds from TerraSAR-X data show generally good agreement with in-situ measurements.