• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.368-371
• /
• 2006

A coastline is the boundary between land and ocean masses. Knowledge of coastline is essential for autonomous navigation, geographical exploration, coastal erosion monitoring and modelling, water line change, etc. Many methods have been researched to extract coastlines from the synthetic aperture radar (SAR) and optic images. Most methods were based on the intensity contrast between land and sea regions. However, in these methods, a coastline detection task was very difficult because of insufficient intensity contrast and the ambiguity in distinguishing coastline from other object line. In this paper, we propose an efficient method for the delineation of coastline using interferometric coherence values estimated from ERS tandem pair. The proposed method uses the facts that a tandem pair of ERS is acquired from a time interval of an accurate day and that the coherent and incoherent values in coherence map are land and water, respectively. The coherence map was generated from ERS tandem pair, filtered by MAP filter, and divided into land and water by the determination of threshold value that is based on the bimodality of the histogram. Finally, a coastline was detected by delineating the boundary pixels. There was a good visual match between the detected coastline and the manually contoured line. The interferometric coherence map will be helpful to identify land and water regions easily, and can be used to many applications that are related with a coastline.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.45-53
• /
• 2013

Global warming causes sea levels to rise and global changes apparently taking place including coastline changes. Coastline change due to sea level rise is also one of the most significant phenomena affected by global climate change. Accordingly, Coastline change detection can be utilized as an indicator of representing global climate change. Generally, Coastline change has happened mainly because of not only sea level rise but also artificial factor that is reclaimed land development by mud flat reclamation. However, Arctic coastal areas have been experienced serious change mostly due to sea level rise rather than other factors. The purposes of this study are automatic extraction of coastline and identifying change. In this study, in order to extract coastline automatically, contrast of the water and the land was maximized utilizing modified NDWI(Normalized Difference Water Index) and it made automatic extraction of coastline possibile. The imagery converted into modified NDWI were applied image processing techniques in order that appropriate threshold value can be found automatically to separate the water and land. Then the coastline was extracted through edge detection algorithm and changes were detected using extracted coastlines. Without the help of other data, automatic extraction of coastlines using LANDSAT was possible and similarity was found by comparing NLCD data as a reference data. Also, the results of the study area that is permafrost always frozen below $0^{\circ}C$ showed quantitative changes of the coastline and verified that the change was accelerated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.23 no.4
• /
• pp.419-426
• /
• 2005

Recently the interest in coast area has been increased in the view of management and usage of national territory. Rapid coastal development has caused directly or indirectly coastline changes which may make environmental problems or threaten the nearby residents' livelihood. CORONA was one of the US satellite reconnaissance programs, and it's imagery provides informations about past coastline with high resolution. In this study, we applied rigorous geo-referencing algorithm to CORONA imagery in order to generate the mosaic image of the East coast area of 1969 with 20m accuracy. This old era CORONA mosaic image was compared with SPOT image of 2005, and the coastline changes were analyzed. We were able to ascertain considerable erosion and accumulation in some parts of study area. erosion area which is calculated from imagery is $0.32\;km^2$ from Kosung to Kangnung. Results of coastline change detection can provide useful information for related studies.

• Journal of the Korean Geographical Society
• /
• v.50 no.5
• /
• pp.473-483
• /
• 2015

In a coastal area, a plenty of research has adopted remotely sensed data. This is because longterm interaction between land and ocean makes continuous geographical changes in a broad extent and unaccessible areas. However, conventional remote sensing platforms such as satellite or airplane has several disadvantages including limited temporal resolution and high operational costs. Hence, this study uses a UAV system to detect a coastline and its movement. Result of coastline detection shows how the coastline moves in a day. Time-series coastlines were derived from UAV aerial images through digital image processing. There is a drawback in the stability of UAV compared to the conventional remote sensing platform, but the advantage appears on the economical efficiency. Since the latest studies shows an improvement of UAV for a variety of purposes in many fields, a UAV can also be utilized for regional study and spatial data acquisition platform. geography can also utilize a UAV as a spatial data acquisition platform for regional study.

• Korean Journal of Remote Sensing
• /
• v.33 no.4
• /
• pp.437-444
• /
• 2017

Since land pixels often generate false alarms in ship detection using Synthetic Aperture Radar (SAR), land masking is a necessary step which can be processed by a land area map or water database. However, due to the continuous coastline changes caused by newport, bridge, etc., an updated data should be considered to mask either the land or the oceanic part of SAR. Furthermore, coastal concrete facilities make noise signals, mainly caused by side lobe effect. In this paper, we propose two methods. One is a semi-automatic water body data generation method that consists of terrain correction, thresholding, and median filter. Another is a dynamic land masking method based on water database. Based on water database, it uses a breadth-first search algorithm to find and mask noise signals from coastal concrete facilities. We verified our methods using Sentinel-1 SAR data. The result shows that proposed methods remove maximum 84.42% of false alarms.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.225-230
• /
• 2007

Currently, looking at the field of producing national coastlines, the lengths of coastlines are inaccurate due to the vague definition of dividing coastline boundaries and insufficient observation data. The level of accuracy and reliability of previous data are also in the very low. This paper used aerial photographs with certain intervals to monitor the change in coastal areas of Songjeong, Haeundae, Kwanganri, Songdo and Dadaepo. The local area subjected for this research was limited to areas near Busan. Launching quantitative/time series analyses on the change of coastal areas using aortal photographs, satellite image data and RTK-GPS surveys. And developing an automatic edge detection program to extract coastlines, suggesting the performance of the program and analyzing the efficiency of the program.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.17 no.2
• /
• pp.61-69
• /
• 2005

The coastal erosion and the look of a heap which are mainly occurred in the district along the coast are found for various forms such as the estuary closing, the estuary sand bar the development of the coast sand bar, and the modification of coastline. Recently, due to the coastal development, these transformations have been intensified. The change of coast, which has been made slow progress is required long-term study on a searching examination of the root cause and a suggestion of a counter measure. In this research, ortho aerial photos were produced to analyze volumes of topographical alternations that have been progressed fer the long run, by 10s cycle from 1940s through 1990s, to compute accurate volumes of coastline variation, through a datum point and G.C.P (Ground Control Point). Also in this study, without respect to water level, the coastline variation was analyzed by using comparatively analyzed a Idlest land map, a cadastral map. And to analyze topographical variation volumes, the tidal station's materials was used under consideration f3r tide. Finally, topographical variation volumes are comparatively analyzed through surveying and sounding and a point of fine of aviation photographing was calculated and revised. After this research, by using ortho aerial photos, We can understand efficiency of these in computing volumes of variations of coastline by analyzing quantitatively erosion and look of a heap. Besides, in the future, these will be used for information gathering of the coastline integration control system.

• 한국지형공간정보학회:학술대회논문집
• /
• 2004.10a
• /
• pp.167-173
• /
• 2004

The erosion(or sediment) reaches very serious level due to the aftermath by the imprudent reclamation on the coast. Continuous studies for long on coastline erosion may be warranted and possible countermeasures proposed because the change of the coastline has been progressed slowly for a long period of time in a wide area. Many experts anticipate that the global sea level's average increase by 19-35 cm due to global warming may certainly have an effect on the coastal erosion throughout the world. Thus, a more rigorous study on the causes of changing coastlines is particularly proposed to find ways to counteract any possible threats against coastal environments. In this study, Ortho aerial photo and hydrographic survey datum were utilized to quantitatively analyze coastal erosion and sediment patterns. This paper also seeks to prove that a parcel under the sea occurred due to relatively significant changes to the coastline. We created Ortho aerial photo using aerial photos taken each decade ('81, '93, '00), overlaid them onto a cadastral registration map, and calculated each amount of erosion and sediment while accounting for the tide level and without considering it. As the result of this study, we could propose that the methods of Ortho aerial photo and the marine observation datum were the effective ways of change detection in erosion, sediment, and artificial reclamation of the coastline for a long time.

• Korean Journal of Remote Sensing
• /
• v.30 no.5
• /
• pp.607-616
• /
• 2014

This research is to observe the shoreline changes in Jinha beach over the 50 years with aerial photographs and satellite images. The shoreline image feature was retrieved from the corrected images using wet and dry techniques and analyzed by DSAS from the statistical point of view. From 1967 to 1992, the mouth of Hoeya River was severely blocked and the northern shoreline off Jinha beach was eroded. The blockade of river mouth seemed to have been eased along with the completion of the dike, but soil continued to be deposited along the high sea away from the river month. Compared to the past, a layer of sediment has been formed off the northern coastline while the southern coastline has eroded. At least in the region subject to this research, the construction of a training dike is to blame. On top of that, a mere combination of dredges and artificial nourishment is not enough to take under control the changing shorelines properly. Thus, it is necessary to devise a more fundamental solution by taking into account reasons behind sediment from the river area that could change the shorelines besides the costal environment.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.8
• /
• pp.311-318
• /
• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.