• Journal of the Korean earth science society
• /
• v.39 no.3
• /
• pp.241-249
• /
• 2018

As the international trade increases, vessel traffics around the Korean Peninsula are also increasing. Maritime accidents hence take place more frequently in the southern coast of Korea where many big and small ports are located. Accidents involving ship collision and sinking result in a substantial human and material damage as well as the marine environmental pollution. Therefore, it is necessary to locate the ships quickly when such accidents occur. In this study, we suggest a new ship detection index by comparing and analyzing the reflectivity of each channel of the Korea MultiPurpose SATellite-2 (KOMPSAT-2) images of the area around the Gwangyang Bay. A threshold value of 0.1 is set based on a histogram analysis, and all vessels are detected when compared with RGB composite images. After selecting a relatively large ship as a representative sample, the distribution of spatial reflectivity around the ship is studied. Uniform shadows are detected on the northwest side of the vessel. This indicates that the sun is in the southeast, the azimuth of the actual satellite image is $144.80^{\circ}$, and the azimuth angle of the sun can be estimated using the shadow position. The reflectivity of the shadows is 0.005 lower than the surrounding sea and ship. The shadow height varies with the position of the bow and the stern, perhaps due to the relative heights of the ship deck and the structure. The results of this study can help search technology for missing vessels using optical satellite images in the event of a marine accident around the Korean Peninsula.

• Journal of Korea Water Resources Association
• /
• v.55 no.12
• /
• pp.1125-1135
• /
• 2022

Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.

• New & Renewable Energy
• /
• v.9 no.3
• /
• pp.14-19
• /
• 2013

Comparative evaluation of offshore wind retreival software, which use the satellite images taken by Synthetic Aperture Radar sensor; SARTools of CLS-SOPRONO, France and SpaceEye of London Research and Development Corporation, Canada is carried out. For a reference satellite image, ENVISAT ASAR imagery of Jeollanam-do Wan-do area when the winter-time northwestern wind prevails is processed by CMOD_IFR2, CMOD4, CMOD5 algorithms. Wind speed difference and its relative ratio are calculated to evaluate uncertainty of software selection.

• Korean Journal of Remote Sensing
• /
• v.25 no.2
• /
• pp.95-105
• /
• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Composites Research
• /
• v.37 no.3
• /
• pp.219-225
• /
• 2024

It is essential to develop a light-weight, high-performance structure for the deployable reflector antenna, which is the payload of a reconnaissance satellite, considering launch and orbital operation performance. Among them, the composite main reflector is a key component that constitutes a deployable reflector antenna. In particular, the development of a high-performance main reflector is required to acquire high-quality satellite images after agile attitude control maneuvers during satellite missions. To develop main reflector, the initial design of the main reflector was confirmed considering the structural performance according to the laminate stacking design and material properties of the composite main reflector that constitutes the deployable reflector antenna. Based on the initial design, four types of composite main reflectors were manufactured with the variable for manufacturing process. As variables for manufacturing process, the curing process of the composite structure, the application of adhesive film between the carbon fiber composite sheet and the honeycomb core, and the venting path inside the sandwich composite were selected. After manufacture main reflector, weight measurement, non-destructive testing(NDT), surface error measurement, and modal test were performed on the four types of main reflectors produced. By selecting a manufacturing process that does not apply adhesive film and includes venting path, for a composite main reflector with light weight and structural performance, we developed and verified a main reflector that can be applied to the SAR(Synthetic Aperture Rader) satellite.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_3
• /
• pp.1965-1974
• /
• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Proceedings of KOSOMES biannual meeting
• /
• 2007.11a
• /
• pp.57-60
• /
• 2007

The Han River is divided into North and South Korea by NLL(Northern Limit Line) and its area has been blocked by CCL(Civil Control Line) since the Korean War in 1950. Satellite remote sensing, therefore, is uniquely suited to monitoring bar transformation in the region. In river with bar, the characteristics of its physical conditions have a close relationship with bar morphology. In this paper, a monitoring approach of bar transformation in the Han River Estuary is presented using RADARSAT/SAR images from 2000 to 2005 and spatial patterns of bar morphology are presented. It could be said that in the estuary vegetated area and natural levees are developed well, but bars are shifted after an event like a flood. It is also showed that suspended solids such as silt transported through the estuary could contribute highly to a sedimentation environment around Incheon.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.1
• /
• pp.1-7
• /
• 2011

Terrain, building location and area, and building shape information is in need of implementing 3D map. This paper proposes a method of extracting a building area by an improved semi-automatic snake algorithm. The method consists of 3-stage: pre-processing, initializing control points, and applying an improved snake algorithm. In the first stage, after transforming a satellite image to a gray image and detecting the approximate edge of the gray image, the method combines the gray image and the edge. In the second stage, the user looks for the center point of a building and the system sets the circular or rectangular initial control points by an procedural method. In the third stage, the enhanced snake algorithm extracts the building area. In particular, this paper sets the one tenn of the snake in a new way in order to use the proposed method for specializing building area extraction. Finally, this paper evaluated the performance of the proposed method using sky view satellite image and it showed that the matching percentage to the exact building area is 75%.

• Proceedings of the KSRS Conference
• /
• 2009.03a
• /
• pp.97-100
• /
• 2009

The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 and 2000 using a dynamic technique, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series for tracking changes on the ground surface. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Korean Journal of Remote Sensing
• /
• v.11 no.3
• /
• pp.61-70
• /
• 1995

In this paper, the algorithm to extract the height of flat-rooftop structures in stereo aerial image is suggested with an assumption that location, orientation, focal length, and field of view of a camera are known. It can be adapted to stereo aerial or satellite images. For performing feature-based stereo matching, the line segments suitable to describe the shape of general buildings are chosen as the feature. This paper is composed of three categories;the first step is to extract edges of structures with the polygon extraction algorithm which utilizes the edge following method, the second step is to perform the line segment matching with the camera information, and the last step is to calculate the location of each matched line and to estimate heights. The stereo images used in experiments are not real but synthetic ones. The experiment shows good results.