• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1173-1183
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• 2023

Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.

• 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.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.250-253
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• 2009

고해상도 컬러 위성 영상 촬영을 위한 다중분광 센서를 탑재한 위성의 영상은, 탑재체에 장착된 센서의 위치에 따라, 동일 지역에 대해 센서 간의 촬영시각의 차이가 발생한다. 만약 이동하는 구름이 촬영될 경우, 센서별 촬영 영상간에는 구름과 지상과의 상대적 위치가 달라진다. 고해상도 컬러 위성 영상을 생성하기 위해, 영상 정합(image registration) 기법이 사용되는 데, 일반적인 영상 정합 알고리즘은 촬영 영상에서의 특징점(feature point)이 움직이지 않는 것을 전제로 수행한다. 그 결과 이동하는 구름 경계부에서 정합점(matching point)이 추출될 경우, 지상 영역에서의 정합품질이 좋지 않다. 따라서, 본 연구에서는 구름 경계부에서 정합점이 추출되지 않는 알고리즘을 제안하였다. 실험 영상으로 구름이 존재하는 아리랑2호 영상을 사용하였고, 제안된 영상 정합 알고리즘은 지상 영역에서의 정합 품질이 높였음을 보였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.89-100
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• 2010

The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.25-28
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• 2007

본 논문은 KOMPSAT-2호 및 3호의 화상활용 일환으로 임반 단위의 임상정보 추출에 관한 시범연구이다. QuickBird 화상을 통해 획득한 결과를 요약하면, 첫째로 회색단계공발생 행렬(GLCM)에 기초한 질감(texture)매개변수 화상은 소나무림과 잣나무림의 임상판별을 가능하게 만든다. 단, 동령림 조건과 사면 방위에 무관한 상태의 추가연구가 요구된다. 둘째로 Matlab의 분수계(watershed)산법에 기초한 분할화상에서 소나물김과 잣나무림의 수관투명 면적 대소를 파악할 수 있다. 역시 동령림 조건하의 보충 연구가 필요하다. 셋째로 형태배율과 진원도(roundness)에 기초한 소나무림과 잣나무림의 구별에서 진원도에서는 차이의 유의성이 없고, 형태배율에서는 수관둘레의 불규칙에 의해 유의성있게 구분된다. 본 연구의 임상정보 추출기법은 정밀임업의 정량정보 제공에 기여할 것이다.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.44-47
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• 2008

본 논문은 KOMPSAT-2호 및 3호의 화상활용 일환으로 고해상도 위성화상을 이용한 정량화 기반의 산불피해등급 분류도에 관한 시범연구이다. 무엇보다 중적외선 밴드가 없는 IKONOS화상에서 NBR산법개발과 NBR에 기초한 산불피해림의 등급분류도를 작성하였다. 본연구의 결과물인 삼척산불지역의 피해등급분류도는 -1과 1사이의 NBR 지수값을 갖는 8bit 회색조 영상을 심 중 경 구분의 산불피해등급별에 따라 각각 적 황 청색으로 나타낸 유색밀도편분 화상이다. 현지 실측의 CBI에 의한 검정에서 정밀 정확으로 평가될 경유, 고해상도 화상을 이용한 NBR기반의 산불피해등급 분류도는 산불 후 피해복구 선택, 즉 자연복원과 인공식재복원에 결정정보가 될 것이다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.271-273
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• 2010

고해상도 위성영상을 이용하여 대상물을 분류하는 것은 원격탐사의 중요한 분야이며, 위성영상 분류에 대한 주요 주제 중 하나는 분류정확도를 높이는 것이다. 본 연구에서는 KOMPSAT-2 영상을 이용하여 SVM(Support Vector Machine)과 MLC(Maximum Likelihood Classification) 방법으로 감독분류를 수행하고 각 분류결과의 비교를 통해 분류방법에 따른 정확도를 평가하고자 하였다. 적은 수의 표본 데이터를 이용한 고해상도 위성영상의 분류결과 SVM이 MLC에 비해 양호한 분류결과를 나타냄을 알 수 있었다.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.445-449
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• 2006

Diffuse pollution has been considering as a major source of the quality deterioration of water resources. The establishment of riparian vegetation strips or buffers along those areas of water bodies is used to reduce the threat of diffuse pollution. Remote sensing offers a means by which critical areas could be identified, so that subsequent action toward the establishment of riparian zones can be taken. On the behalf of KOMPSAT-2 satellite imagery as a high resolution spatial data, Landsat TM satellite data are used to aquire the land cover for the riparian buffers studied. This investigation aims to assess the riparian buffers established on the upper Geum river as a pollution mitigation. Through comparing the delineation of riparian buffer zones developed with the existing zones established by the government, we can find the critical distortion points of the existing riparian buffer zone.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.15-20
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• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.113-125
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• 2012

This research is aimed at evaluating the land surface characterization of KOMPSAT-3A middle infrared (MIR) data. Airborne Hyperspectral Scanner (AHS) data, which has MIR bands with high spatial resolution, were used to assess land surface temperature (LST) retrieval and classification accuracy of MIR bands. Firstly, LST values for daytime and nighttime, which were calculated with AHS thermal infrared (TIR) bands, were compared to digital number of AHS MIR bands. The determination coefficient of AHS band 68 (center wavelength $4.64{\mu}m$) was over 0.74, and was higher than other MIR bands. Secondly, The land cover maps were generated by unsupervised classification methods using the AHS MIR bands. Each class of land cover maps for daytime, such as water, trees, green grass, roads, roofs, was distinguished well. But some classes of land cover maps for nighttime, such as trees versus green grass, roads versus roofs, were not separated. The image classification using the difference images between daytime AHS MIR bands and nighttime AHS MIR bands were conducted to enhance the discrimination ability of land surface for AHS MIR imagery. The classification accuracy of the land cover map for zone 1 and zone 2 was 67.5%, 64.3%, respectively. It was improved by 10% compared to land cover map of daytime AHS MIR bands and night AHS MIR bands. Consequently, new algorithm based on land surface characteristics is required for temperature retrieval of high resolution MIR imagery, and the difference images between daytime and nighttime was considered to enhance the ability of land surface characterization using high resolution MIR data.