• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.801-810
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• 2018

Ship monitoring using satellite synthetic aperture radar (SAR) images consists of ship detection, ship discrimination, and ship classification. A large number of methods have been proposed to improve the detection and discrimination capabilities, while only a few studies exist for ship classification. Thus, many studies for the ship classification are needed to construct ship monitoring system having high performance. Note that constructing database (DB), which contains both SAR images and labels of various ships, is important for research on the ship classification. In the airborne SAR classification, many methods have been developed using moving and stationary target acquisition and recognition (MSTAR) DB. However, there has been no publicly available DB for research on the ship classification using satellite SAR images. Recently, Shanghai Key Laboratory has constructed OpenSARShip DB using both SAR images of various ships generated from Sentinel-1 satellite of European Space Agency (ESA) and automatic identification system (AIS) information. Thus, the applicability of OpenSARShip DB for ship classification should be investigated by using the concepts of airborne SAR classification which have shown high performances. In this study, ship classification using satellite SAR images are conducted by applying the concepts of airborne SAR classification to OpenSARShip DB, and then the applicability of OpenSARShip DB is investigated by analyzing the classification performances.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.75-87
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• 2011

This paper presents a method for region-based building extraction from high resolution satellite images(HRSI) using integrated information of spectral and color invariant features without user intervention such as selecting training data sets. The purpose of this study is also to evaluate the effectiveness of the proposed method by applying to IKONOS and QuickBird images. Firstly, the image is segmented by the MSRG method. The vegetation and shadow regions are automatically detected and masked to facilitate the building extraction. Secondly, the region merging is performed for the masked image, which the integrated information of the spectral and color invariant features is used. Finally, the building regions are extracted using the shape feature for the merged regions. The boundaries of the extracted buildings are simplified using the generalization techniques to improve the completeness of the building extraction. The experimental results showed more than 80% accuracy for two study areas and the visually satisfactory results obtained. In conclusion, the proposed method has shown great potential for the building extraction from HRSI.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.59-68
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• 2011

The analysis of optimal infiltration path is one of the representative fields in which the GIS technology can be useful for the military purpose. Usually the analysis of the optimal path is done with network data. However, for military purpose, it often needs to be done with raster data. Because raster data needs far more computation than network data, it is difficult to apply the methods usually used in network data, such as Dijkstra algorithm. The genetic algorithm, which has shown great outcomes in optimization problems, was applied. It was used to minimize the detection probability of infiltration route. 2D binary array genes and its crossover and mutation were suggested to solve this problem with raster data. 30 tests were performed for each population size, 500, 1000, 2000, and 3000. With each generation, more adoptable routes survived and made their children routes. Results indicate that as the generations increased, average detection probability decreased and the routes converged to the optimal path. Also, as the population size increases, more optimal routes were found. The suggested genetic algorithm successfully finds the optimal infiltration route, and it shows better performance with larger population.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.507-520
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• 2011

Conventional radar altimeter system measured directly the distance between the satellite and the ocean surface and frequently used by aircraft for approach and landing. The radar altimeter is good at flat surface like sea whereas it is difficult to determine precise three dimensional ground coordinates because the ground surface, unlike ocean, is very indented. To overcome this drawback of the radar altimeter, we have developed and validated the interferometric radar altimeter signal processing which is combined with new synthetic aperture and interferometric signal processing algorithm to extract precise three-dimensional ground coordinates. The proposed algorithm can accurately measure the three dimensional ground coordinates using three antennas. In a set of 70 simulations, the averages of errors in x, y and z directions were approximately -0.40 m, -0.02 m and 4.22 m, respectively and the RMSEs were about 3.40 m, 0.30 m and 6.20 m, respectively. The overall results represent that the proposed algorithm is effective for accurate three dimensional ground positioning.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.303-314
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• 2014

Mt. SAKRAJIMA in southern Kagosima, japan is one of the most active volcanoes in the world. On 18 August 2013, the SAKRAJIMA volcano recently went into the largest scaled eruption with a huge plume of volcanic ash. Therefore, the concern arises if this considerable amount of ashes might flow into the Korea peninsula as well as Japan. In this paper, we performed numeric experiment to analyze how volcanic product resulted from the SAKRAJIMA volcano has impacted on Korea. In order to predict the spread pathway of ash, HYSPLIT model and UM data has been used and 17th September 2013 has been selected as observation date since it is expected that the volcanic ash would flow into the South Korea. In addition, we have detected ash dispersion by using optical Communication, Ocean and Meteorological Satellite- Geostationary Ocean Color Imager (COMS-GOCI) images. As the results, we come to a very satisfactory conclusion that the spread pathway of volcanoes based on HYSPLIT model are matched 63.52 % with ash dispersion area detected from GOCI satellites image.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.879-888
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• 2017

This study is a preliminary research conducted in Buhansan mountain National Park to develop a management system to predict and control oak wilt disease by indicating spatial factors which affect diffusion of the disease. After analysing altitude factor during the estimation of spatial analysis of damaged area, it is indicated that damaged trees are mainly distributed at altitude of 200-500 m and number decreased drastically over the altitude of 500 m. The result showed that 92% of total damaged trees are on slope between 20~40 degrees and the number decreased drastically on slope steeper than 40 degrees. It is indicated that damaged area is mainly distributed on southern aspect. It is estimated by using CART that slope factor affected the diffusion of disease mostly but aspect factor did not. Surface temperature and altitude showed similar effect.By simulating possible diffusion scenario, it is estimated that the disease could spread to DO-BONG Mt., northeast of Bukhansan mountain.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.639-645
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• 2016

Yeongjong-do is seventh largest island in the west coast of Korea which is 4.8 km away in the direction of south-west from Incheon. The mudflat area around the Yeongjong-do has variable dimension according to tide level. In addition, Yeongjong-do is important area with high environmental value as wintering sites for migratory birds. The mudflat of Yeongjong-do is also meaningful region because it is used as place of education and tourist attraction. But, there are increasing concerns about preservation of mudflat area caused by artificial development such as land reclamation project and Incheon airport construction. In this paper, mudflat area was detected using Landsat 7 ETM+ images that United States Geological Survey (USGS) is providing the data in 16 days period. The false color composite was made from band 7, 5, and 3 that could dividing boundary between water and land for the purpose of appearance of boundary line in mudflat region. This area was calculated using results of classification based on false color composite images and was digitized through repetitive algorithm during research of period. Therefore, the change of northeastern area in Yeongjong-do was detected according to tide level during 16 years from 2000 to 2015 on the basis of providing period at tide station. This paper will expect as indicator for range of area in same tide level prior to the start of the research for preservation of mudflat. It will be also scientific grounds about change of mudflat area caused by artificial development.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.123-131
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• 2010

In this paper we applied Ground-Based Synthetic Aperture Radar(GB-SAR) interferometry to detect artificial displacement of a reflector and performed an atmospheric humidity correction to improve the accuracy. A series of GB-SAR images were obtained using a center frequency of 5.3 GHz with a range resolution of 25 cm and a azimuth resolution of $0.324^{\circ}$, all in full-polarization (HH, VV, VH, HV) modes. A triangular trihedral corner reflector was located 160 m away from the system, and the artificial displacements of 0-40 mm was implemented during the GB-SAR image acquisition. The result showed that the RMS error between the actual and measured displacements, averaged in all polarization data, was 1.22 mm, while the maximum error in case of the 40 mm displacement was 2.72 mm at HH-polarization. After the atmospheric correction with respect to the humidity, the RMS error was reduced to 0.52 mm. We conclude that a GB-SAR system can be used to monitor the possible displacement of artificial/natural scatterers and the stability assessment with sub-millimeter accuracy.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.445-454
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• 2009

Localized unprecedented torrential rain and heavy rainfall cause repeated damages and make it difficult to detect and predict the landslide caused by heavy rainfall. To analyze the landslide characteristics of Inje area this study used satellite images photographed after the occurrence of landslide caused by the typhoon Ewiniar occurred in July, 2006, and for GIS analysis purpose, interpreted the satellite images (SPOT5) visually to digitize into developing parts, water traveling parts and sediment parts. For analysis of spatial characteristics, landslide areas obtained from visual interpretation of digital map, 3rd & 4th forest vegetation maps and detailed soil map and grids were overlaid and analyzed. As a result, in regard to topographic features, landslide occurred at places, of which average slope is $26.34^{\circ}$, had south, south-east, south-west aspects and average altitude of 627m. From hydrological analysis, it was found out that water traveling area rapidly spread approaching water traveling area and sediment area. From forest type analysis, it was found out that landslide occurrence was high in pine woods, and in terms of girth class attribute, landslide occurred in small-sized woods, in which the crown occupancy of trees that have the diameter at breast height, 6~16cm, was greater than 50%. From the analysis of soil series, landslide areas constitute 37.85% of OdF and 37.35% of SmF, which had sandy loam soil and excellent drainage capacity. Through this study, landslides in Inje area were characterized and SPOT5 images of 2.5m resolution could be used. But there was a difficulty in determining water traveling parts adjacent to urban area.