• 한국지형학회지
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• 제17권4호
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• pp.41-52
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• 2010

양양군 오산리 일대에는 쌍호, 가평리습지, 궁개호와 염개호 등 4개의 석호가 높은 밀도로 나타난다. 쌍호는 동해안의 대표 석호군과 함께 해진극상기에 하구부가 익곡되어 현재까지 호수를 유지하고 있으나, 가평리습지와 궁개호, 염개호는 사빈의 제간습지에 형성되었다. 20세기동안 4개 석호는 대체로 축소 및 위치변화 정도가 심한데, 그 원인을 자연적인 요인과 인간의 영향, 그리고 기타 요인으로 구분하여 검토하였다. 지형발달에 따른 매적단계와 함께 20세기동안 급속하게 진행된 산업화와 개발에 따른 매립, 소규모 석호의 존재가치에 대한 인식 부족이나 지도 작성시 오류, 그리고 측량기술의 낙후성에 기인한다. 따라서 경관 복원 계획은 석호의 성격에 따라 다르게 진행되어야 하며, 쌍호를 우선적으로 복원하는 것이 권장되며, 인간의 영향이 최소한 미쳤던 1920년대의 지형으로 되돌리는 것이 바람직하다.

• 한국지리정보학회지
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• 제15권4호
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• pp.1-14
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• 2012

하천은 육지 표면에서 일정한 물길을 따라 흐르는 물줄기를 의미하며, 하천 매핑 작업은 하천유역의 지형 변화 연구 및 하천 유역의 홍수 모니터링 연구 등에 매우 중요한 역할을 한다. 그러나 하천의 수위변화로 인한 유역 내 지표면의 수위 및 유량의 불균일성 등으로 인하여, 기존의 지반조사 기술은 하천 매핑 작업에 효과적이지 않다. 공간 정보 자료는 해당 지역에 접근하지 않고도 해당 지역에 관한 지형적인 정보를 획득할 수 있어서, 하천 지형 조사 및 하천 측량 등 하천 유역의 지형연구에 굉장히 유용하게 쓰일 수 있다. 본 연구에서는, 각각의 다른 파라미터를 사용하여 영상분류 기법 중의 하나인 ISODATA(Iterative Self_Organizing Data Analysis) 분류기법을 적용하여 RapidEye 영상으로부터 하천을 추출하는 방법을 제시하였다. 우선, RapidEye 영상으로부터 NIR(Near InfraRed) 밴드 영상과 NDVI(Normalized Difference Vegetation Index) 영상을 생성한 뒤, 이를 각각의 파라미터로 설정한다. 생성된 각각의 영상에 ISODATA 기법을 적용한 뒤, 후처리 과정을 통하여 각각의 영상으로부터 하천을 추출하도록 한다. 각각의 영상에서 추출한 하천의 경계선 또한 Sobel 에지 추출 기법을 통하여 추출된다. 점검 점들을 이용하여 정확도 검증을 수행한 결과, NIR 밴드로부터 추출한 하천의 정확도가 NDVI 영상으로부터 추출한 하천의 정확도보다 더 높다는 것을 알 수 있다.

• 자원환경지질
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• 제49권5호
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• pp.381-388
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• 2016

본 연구에서는 독도 연안의 정밀 해저 지형도, 해저면 영상도와 고해상도 수중 영상 자료 결과들을 활용하여 통합 이미지화 및 3차원 중첩 주제도 작성을 통해 맵핑 기법에 대한 연구를 하고자 하였다. 통합 이미지화 기법은 해저 지형 자료와 해저면 영상도, 수중 영상 자료 등의 환경 정보를 통합하여 지구물리 자료를 보다 입체적으로 표현 가능한 주제도를 만드는 것이다. 정밀 해저 지형 자료 및 해저면 영상 자료는 독도 서도 남부 연안 주변의 수심 약 50 m 범위에서 획득하였으며, 고해상도 수중 영상은 같은 구역 내에서 주요 서식지 환경이 형성되어 있는 세 구역을 선정하고 촬영하여 획득하였다. 통합 맵핑 기법을 적용한 주제도는 정밀 해저 지형 자료를 기반으로 작성하였으며, 해저면 영상도와 고해상도 수중 영상을 지형 자료와 중첩 통합하고 분석 처리하여 독도 연안의 해저환경 및 서식지 특성을 나타내는 3차원 중첩 주제도를 작성하였다. 해저면 영상도와 고해상도 수중 영상 자료를 지형 자료와 통합한 3차원 중첩 주제도는 해저 지형 특성과 실제 해저면 환경을 연계하여 분석이 가능하므로 해저면 생태계의 환경 및 상황을 파악하는데 유용한 자료이다. 이는 독도 연안 환경과 같이 불규칙하고 다양한 외부 환경 변화 요소에 노출된 해저면 환경의 현재 해저면 환경 특성을 파악하고 모니터링을 위한 자료로의 활용이 가능할 것으로 판단되며, 자료의 활용 가치를 높이기 위해 향후에 지속적인 자료 축적을 수행하고 3차원 중첩 주제도 작성이 수반되어야 할 것이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.34-37
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• 2006

When tsunami waves propagate across open ocean they are steered by Coriolis force and refraction due to gentle gradients in the bathymetry on scales longer than the wavelength. When the wave encounters steep gradients at the edges of continental shelves and at the coast, the wave becomes non-linear and conservation of momentum produces squirts of surface current at the head of submerged canyons and in coastal bays. HF coastal ocean radar is well-conditioned to observe the current bursts at the edge of the continental shelf and give a warning of 40 minutes to 2 hours when the shelf is 50-200km wide. The period of tsunami waves is invariant over changes in bathymetry and is in the range 2-30 minutes. Wavelengths for tsunamis (in 500-3000 m depth) are in the range 8.5 to over 200 km and on a shelf where the depth is about 50 m (as in the Great Barrier Reef) the wavelengths are in the range 2.5 - 30 km. It is shown that the phased array HF ocean surface radar being deployed in the Great Barrier Reef (GBR) and operating in a routine way for mapping surface currents, can resolve surface current squirts from tsunamis in the wave period range 20-30 minutes and in the wavelength range greater than about 6 km. There is a trade-off between resolution of surface current speed and time resolution. If the radar is actively managed with automatic intervention during a tsunami alert period (triggered from the global seismic network) then it is estimated that the time resolution of the GBR radar may be reduced to about 2 minutes, which corresponds to a capability to detect tsunamis at the shelf edge in the period range 5-30 minutes. It is estimated that the lower limit of squirt velocity detection at the shelf edge would correspond to a tsunami with water elevation of less than 5 cm in the open ocean. This means that the GBR HF radar is well-conditioned for use as a monitor of small and medium scale tsunamis, and has the potential to contribute to the understanding of tsunami genesis research.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.827-830
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• 2006

The tsunami from the megathrust earthquake magnitude 9.3 on 26 December 2004 is the largest tsunami the world has known in over forty years. This tsunami destructively attacked 13 countries around Indian Ocean with at least 230,000 fatalities, displaced people 2,089,883 and 1.5 million people who lost their livelihoods. The ratio of women and children killed to men is 3 to 1. The total damage costs US$ 10.73 billion and rebuilding costs US$ 10.375 billion. The tsunami's death toll could have been drastically reduced, if the warning was disseminated quickly and effectively to the coastal dwellers along the Indian Ocean rim. With a warning system in Indian Ocean similar to that operating in the Pacific Ocean since 1965, it would have been possible to warn, evacuate and save countless lives. The best tribute we can pay to all who perished or suffered in this disaster is to heed its powerful lessons. UNESCO/IOC have put their tremendous effort on better disaster preparedness, functional early warning systems and realistic arrangements to cope with tsunami disaster. They organized ICG/IOTWS (Indian Ocean Tsunami Warning System) and the third of this meeting is held in Bali, Indonesia during $31^{st}$ July to $4^{th}$ August 2006. A US$ 53 million interim warning system using tidal gauges and undersea sensors is nearing completion in the Indian Ocean with the assistance from IOC. The tsunami warning depends strictly on an early detection of a tsunami (wave) perturbation in the ocean itself. It does not and cannot depend on seismological information alone. In the case of 26 December 2004 tsunami when the NOAA/PMEL DART (Deep-ocean Assessment and Reporting of Tsunami) system has not been deployed, the initialized input of sea surface perturbation for the MOST (Method Of Splitting Tsunami) model was from the tsunamigenic-earthquake source model. It is the first time that the satellite altimeters can detect the signal of tsunami wave in the Bay of Bengal and was used to validate the output from the MOST model in the deep ocean. In the case of Thailand, the inundation part of the MOST model was run from Sumatra 2004 for inundation mapping purposes. The medium and high resolution satellite data were used to assess the degree of the damage from Indian Ocean tsunami of 2004 with NDVI classification at 6 provinces on the Andaman seacoast of Thailand. With the tide-gauge station data, run-up surveys, bathymetry and coastal topography data and land-use classification from satellite imageries, we can use these information for coastal zone management on evacuation plan and construction code.

• 한국제4기학회지
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• 제20권2호
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• pp.51-57
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• 2006

동해안의 봉길리에서 정자지역에 분포하는 해안단구 퇴적물에 대한 지질조사와 새로운 연대측정 자료를 이용하여 우리나라 동해안 남부지역의 해안단구 층서를 재조명하였다. 동해안 해안단구는 해발고도에 따라 uHT ($90{\sim}130m$), HT ($63{\sim}86m$), MT ($36{\sim}55m$), 그리고 LT ($8{\sim}25m$) 등으로 구분된다. Lower Terrace I은 MIS 5c시기의 Aso-4 및 MIS 5d 혹은 5e시기의 Ata 테프라를 포함하고 있다. 이러한 테프라와 OSL 연대자료로 미루어 Lower Terrace I은 MIS 5e동안 형성된 것으로 해석된다. Lower Terrace II의 연대도 역시 테프라와 OSL 연대자료로 미루어 MIS 5a인 것으로 생각된다. Lower Terrace가 형성되었던 MIS 5동안의 한반도 남동부의 융기율은 $0.08{\sim}0.25\;mm$이며, 평균 0.15 mm인 것으로 계산되었다. 이러한 융기율은 일본과 대만으로 비롯한 조구조운동이 활발한 다른 지역의 융기율에 비해서 매우 작은 값이다.

• 대한원격탐사학회지
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• 제21권3호
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• 대기
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• 제21권4호
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• pp.439-446
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• 2011

NCEP reanalysis data were analyzed in order to provide distribution of global wind resource and wind speed in the surface layer for the years 2000-2009. Wind speed at 10 m above ground level (AGL) was converted to wind speed at 80 m above the ground level using the power law. The global average 80 m wind speed shows a maximum value of $13ms^{-1}$ at the storm track region. High wind speed over the land exists in Tibet, Mongolia, Central North America, South Africa, Australia, and Argentina. Wind speed over the ocean increased with a large value in the South China Sea, Southeast Asia, East Sea of the Korea. Sea surface wind in Western Europe and Scandinavia are suitable for wind farm with a value of $7-8ms^{-1}$. Areas with great potential for wind farm are also found in Eastern and Western coastal region of North America. Sea surface wind in Southern Hemisphere shows larger values in the high latitude of South America, South Africa and Australia. The distribution of low-resolution reanalysis data represents general potential areas for wind power and can be used to provide information for high-resolution wind resource mapping.

• 한국수산과학회지
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• 제42권5호
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• pp.509-517
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• 2009

Seagrass meadows are important biogenic habitats for a wide variety of marine animals and plants, a source of organic carbon for commercially important animals, and act as a nutrient filter in estuarine and coastal ecosystems. As such, mapping the distribution of seagrass beds provides us with an important component of management and conservation strategies. To survey seagrass distribution within Deukryang Bay, we directly observed seagrass beds using SCUBA in Boseong-gun, Goheung-gun, and Jangheung-gun. Seagrass distribution in Geogeum and Gumdang islands were not observed. Specifically, we monitored the distribution area, species composition, morphology, density, and biomass of seagrass meadows. Seagarss beds were mapped for Daikum-ri coast, Deukryang island, Yongjeong-ri coast, Samsan-ri coast and Ongam-ri coast. Total seagrass coverage in Deukryang Bay was $5.1\;km^2$, $4.8\;km^2$ of which was Zostera marina, $0.3\;km^2$ Z. caulescence and $0.01\;km^2$ Z. japonica. Z. japonica was found in intertidal zones, Z. marina was found from the intertidal to subtidal zones of 2 m MSL (mean sea level) depth, and Z. caulescence was found in subtidal zones of 2.5-5 m MSL.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.487-490
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• 2006

Ocean Color Monitor (OCM) onboard the Indian Remote Sensing Satellite IRS-P4 has been used to retrieve chlorophyll concentration in the Bay of Bengal and the Arabian Sea using a bio-optical algorithm. Cloud masking and atmospheric corrections have been performed before applying mapping function to derive chlorophyll concentration from IRS-P4 OCM data. We have retrieved chlorophyll concentration from OCM, and MODIS during the summer and winter season along the eastern and western coast of India at every 1 degree latitude at increasing distance (25, 50, 100, 150 and 200km) away from the coast as well as near river mouths for the period 2000-2003. We have also studied spatial and temporal dynamics of monthly MODIS Aqua (for period July 2002-April 2004). The seasonal dynamics of chlorophyll concentration over the Bay of Bengal and the Arabian Sea have been discussed using OCM and MODIS for both the coastal region and the open sea.