• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.82-84
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• 2003

Watershed boundaries and flow paths within the watershed are the most important factors required in watershed analysis. Most often the derivation of watershed boundaries and stream network and flow paths is based on topographical maps but spatial variation of flow direction is not clearly understandable using this method. Water resources projects currently use 1: 50, 000-scale ground survey or aerial photography-based topographical maps to derive watershed boundary and stream network. In basins, where these maps are not available or not accessible it creates a real barrier to watershed geo-spatial analysis. Such situations require the use of global datasets, like GTOPO30. Global data sets like ETOPO5, GTOPO30 are the only data sets, which can be used to derive basin boundaries and stream network and other terrain variations like slope aspects and flow direction and flow accumulation of the watershed in the absence of topographic maps. Approximately 1-km grid-based GTOPO 30 data sets can derive better outputs for larger basins, but they fail in flat areas like the Karkheh basin in Iran and the Amudarya in Uzbekistan. A new window in geo-spatial hydrology has opened after the launching of the space-borne satellite stereo pair of the Terra ASTER sensor. ASTER data sets are available at very low cost for most areas of the world and global coverage is expected within the next four years. The DEM generated from ASTER data has a reasonably good accuracy, which can be used effectively for hydrology application, even in small basins. This paper demonstrates the use of stereo pairs in the generation of ASTER DEMs, the application of ASTER DEM for watershed boundary delineation, sub-watershed delineation and explores the possibility of understanding the drainage flow paths in irrigation command areas. All the ASTER derived products were compared with GTOPO and 1:50,000-based topographic map products and this comparison showed that ASTER stereo pairs can derive very good data sets for all the basins with good spatial variation, which are equal in quality to 1:50,000 scale maps-based products.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.654-655
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• 2003

Korea has experienced 10 a Cochlodinium polykrikoides red tide outbreaks during the last 10 years (1993-2002). The monitoring activities at National Fisheries Research and Development Institute (NFRDI) in Korea have been extended to all the coastal waters after the worst of fish killing by C. polykrikoides blooms in 1995. NFRDI is looking forward to finding out the feasibility of red tide detection around Korean waters using satellite remote sensing of NOAA/AVHRR, Orbview-2/SeaWiFS, IRS-P4/OCM and Terra/MODIS on real time base. In this study, we used several alternative methods including climatological analysis, spectral and optical methods which may offer a potential detection of the major species of red tide in Korean waters. The relationship between the distribution of SST and C. polykrikoides bloom areas was studied. In climatological analysis, NOAA, SeaWiFS, OCM satellite data in 20th and 26th August 2001 were chosen using the known C. polykrikoides red tide bloom area mapped by helicopter reconnaissance and ground observation. The 26th August, 2001 SeaWiFS chlorophyll a anomaly imageries against the imageries of non-occurring red tide for August 20, 2001 showed the areas C. polykrikoides occurred. The anomalies of chlorophyll a concentration from satellite data between before and after red tide outbreaks showed the similar distribution of C. polykrikoides red tide in 26th August, 2001. The distribution of the difference in SST between daytime and nighttime also showed the possibility of red tide detection. We used corrected vegetation index (CVI) to detect floating vegetation and submerged vegetation containing algal blooms. The simple result of optical absorption from C. polykrikoides showed that if we use the optical characteristics of each red tide we will be able to get the feasibility of the red tide detection.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.154-154
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• 2012

지표에서의 토양수분은 작은 구성비를 가짐에도 불구하고 여러 수문 현상을 연계하는 매우 중요한 인자로써 최근 관련 연구가 활발하게 진행되고 있다. 토양수분은 침투나 침루를 통하여 강우와 지하수를 연결하는 기능을 함과 동시에 강우사상에 따른 유출특성에 직접적인 영향을 미치며 증발산을 통하여 에너지 순환을 연결하는 중요한 기능을 한다. 토양수분을 측정하는 방법에는 세타 탐침(Theta Probe), 장력계, TDR(Time Domain Reflectrometry) 등이 이용되고 있으며, 광역 토양수분자료의 보다 정확한 공간 변동성의 관측을 위하여 항공원격탐사와 인공위성 원격탐사기술이 개발되어 적용되고 있다. 인공위성 영상은 자료의 분석이 간편하며, 공간자료이므로 공간 변화를 분석하는 데 있어 매우 편리하다. 그 중 MODIS(Moderate Resolution Imaging Spectroradiometer) 위성영상은 저해상도 영상으로 극궤도 위성인 Terra와 Aqua 위성에 장착되어 있으며, NASA에서 필요한 정보를 받아 사용할 수 있다. 본 연구에서는 유역의 물리적 지형자료와 같은 방대한 양의 자료 수집 없이도, 모형이 구축되면 인공위성자료와 강우자료만으로도 신뢰성 높은 결과를 단시간 내에 효율적으로 산정할 수 있는 자료 지향형 모형인 ANFIS(Adaptive Neuro-Fuzzy Inference System)를 사용하였다. 사용된 퍼지변수로는 시험유역의 토양수분 관측자료와 강수량 및 인공위성 자료인 MODIS NDVI(Normalize Difference Vegetation Index), MODIS LST(Land-Surface Temperature) 영상을 이용하였다. MODIS NDVI는 시간 해상도 8일, 공간해상도 250 인 Level 3 영상이며, MODIS LST는 시간 해상도 1일, 공간해상도 1 km인 Level 3 영상을 사용하였다. 위성자료를 사용하기 위해 Korea TM 좌표체계로 변환한 뒤, 토양수분 관측지점이 속한 각 셀의 속성값을 추출하였다. 위성자료와 수집된 자료 및 토양수분자료와의 관계를 분석하기 위하여 입력자료를 다양한 방법으로 구성하여 입력 변수를 생성하였다. 생성된 입력 변수와 ANFIS 모형을 연계하여 각각의 토양수분 산정모형을 구축하고 대상지점에 대한 토양수분을 산정 및 비교 분석하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.126-126
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• 2012

기후변화는 전 세계적으로 다양한 영향을 미치고 있으며 특히, 홍수나 대설로 인한 수문변화에 영향을 준다. 본 연구는 준분포형 연속 모형인 SWAT (Soil and Water Assessment Tool)모형을 이용하여 우리나라 3대 대설지역에 속하는 다목적댐인 충주댐유역(6642.0 m)의 기후변화에 따른 융설이 수문과 수질에 미치는 영향을 분석하고자 한다. 먼저, 융설 모형의 매개변수인 적설분포면적감소곡선 (Snow Cover Depletion Curve; SCDC)을 구축하기 위하여 10년(2000-2010)동안의 Terra MODIS (MODerate resolution Imaging Spectroradiometer) 위성영상자료와 6개 기상관측소(충주, 제천, 원주, 영월, 대관령, 태백)의 최심적설자료를 이용하여 연도별 SCDC을 구축하였다. 구축 결과, 눈이 50% 피복 일 때 snow volume은 연 평균 0.47로 분석되었다. 이를 SWAT 모형에 적용하여 수문과 수질에 대한 적용성 평가를 실시한 결과, 유출의 경우 NSE는 융설기간 동안 평균 0.8, 전체기간은 평균 0.6으로 나타났으며 수질(Sediment, T-N, T-P)의 경우 각각 평균 0.72, 0.70, 0.85을 나타내었다. 미래 기후자료는 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 SRES(Special Report on Emission Scenarios) A1B, B1 기후변화시나리오의 HadCM3 모델의 결과 값을 이용하였으며 기간은 과거 30년 기후자료(1981-2010, baseline)를 바탕으로 2040s(2020-2059), 2080s(2060-2099)의 두 기간으로 나누어 각각 분석하였으며 기후변화 결과 값의 불확실성을 줄이고자 과거 자료와 GCM의 1981년에서 2000년까지의 값을 비교하여 온도와 강수량의 보정을 실시한 후 LARS-WG를 이용하여 온도와 강수량 자료를 구축하였다. SWAT 모형을 적용한 결과, 평균 1.92 증가한 것으로 나타났으며 유출은 융설기간(Nov-Apr)이 비융설기간(May-Oct)보다 10% 더 증가하였다. 본 연구에서는 SWAT 모형을 통한 유출 및 환경부하량 전망을 목표로 하여 미래 기후변화를 고려한 융설이 다목적댐에서의 유출과 수질 (Sediment, Total Nitrogen, Total Phosphorus)에 미치는 영향을 평가해 보고자 한다.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.373-377
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at $3.7{\mu}m\;(T_{3.7})$, the temperature at $11{\mu}m\;(T_{11}$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the seven airport areas except the Cheongju airport have revealed the accuracy of 50% in the daytime and 70% in the nighttime, based on statistical verification for the independent samples as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.165-181
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• 2001

Using a field spectrometer having a spectral range of 0.4$\mu\textrm{m}$~2.5$\mu\textrm{m}$ with a spectral resolution of 1nm, the researchers measured the reflectance of granite, andesitic rocks, sedimentary rocks, and pyrophyllite ore in the Ungsang area, Kyungsang Basin, South Korea. Spectral characteristics of the geological media were investigated from the analysis. The in-situ measured sites were selected in well exposed rock outcrops. In case of unfavorable weather conditions, rocks were sampled and remeasured under natural solar condition. The reflectance of field data was measurd at three sistes for granite, six sites for andesitic rock three sites for sedimentary rocks, and two sites for pyrophyllite ore. The vibrational absorption bands for pyrophyllite are detected in the spectral range of 2.0$\mu\textrm{m}$~2.5$\mu\textrm{m}$. The absorption band for granites in study area is not distinctive. The reflectance measured under normal field conditions showed strong absorption at wavelengths of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ due to the effect of moisture in the atmosphere. After the bands of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ were removed, Hull Quotient method was applied to characterize absorption bands. The reflectances of field data were calculated to estimate the band ratio corresponding to the Landsat TM and EOS Terra ASTER. The researchers suggest here that the TM band2, band3, band4, and band7 or ASTER band2, band3, band4, and band9 are the best combination for discriminating outcrops. The researchers tested and demonstrated using a Landsat TM image in the study area. For geologic applications, decorrelation stretch is also an effective tool to enhance the exposed rock mass in images.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.217-221
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• 2003

The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer that launched on the Earth Observing System (EOS) Terra spacecraft in 1999. Its main objectives are to measure carbon monoxide (CO) and methane (CH4) concentrations in the troposphere. This study analyzes tropospheric carbon monoxide distributions using MOPITT data and compare with ozone distributions in Northeast Asia. In general, seasonal CO variations are characterized by a peak in spring and decrease in summer. Also, this study revealed that the seasonal cycles of CO are maximum in spring and minimum in summer with average concentrations ranging from 118ppbv to 170ppbv. The monthly average of CO shows a similar profile to those of O3. This fact clearly indicates that the high concentration of CO in spring is caused by two possible causes: the photochemical CO production in the troposphere, or the transport of the CO in the northeast Asia. The CO and $O_3$ seasonal cycles in the Northeast Asia are influenced extensively by the seasonal exchange of the different types of air mass due to the Asian monsoon. The continental air masses contain high concentrations of $O_3$ and CO due to higher continental background concentrations and sometimes due to the contribution of regional pollution. In summer the transport pattern is reversed. The Pacific marine air masses prevail over Korea, so that the marine air masses bring low concentrations of CO and $O_3$, which tend to give the apparent minimum in summer.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.470-470
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• 2015

본 연구의 목적은 위성영상 기반의 SEBAL(Surface Energy Balance Algorithm for Land) 모형과 SWAT(Soil and Water Assessment Tool) 수문모형을 용담댐 유역($922.3km^2$)에 적용하여 증발산량을 산정하고 모형 간 공간 증발산량의 비교를 통해 각 모형의 적용성을 평가하는데 있다. 이를 위해 SEBAL모형의 입력자료로 Terra MODIS(Moderate Resolution Imaging Spectrometer) Product 중 Normalized Distribution Vegetation Index(NDVI), Albedo 영상을 2012년부터 2013년까지 월단위로 구축하고, 일단위의 Land Surface Temperature(LST) 영상을 구축하였다. 지형자료로는 Digital Elevation Model(DEM)과 Land use를 구축하였으며 SEBAL 모형의 구동을 위한 위성영상 및 지형자료는 500 m의 공간해상도로 재구축하였다. SWAT 모형의 모의를 위해 기상 및 유량 자료를 2000년부터 2013년까지 일단위로 구축하였고, DEM, Land use, 토양도의 지형자료를 30 m의 공간해상도로 구축하였다. SWAT 모형의 유출 검보정 후 수위관측소 지점에서 평균 $R^2$를 산정한 결과 도치(0.80), 동향(0.72), 석정(0.64), 주천(0.80), 천천(0.80), 용담댐(0.72)로 높은 상관성을 나타냈으며, 유출 검보정 후 SWAT 모형의 증발산량 모의 결과를 바탕으로 SEBAL 모형과의 공간 증발산량을 비교하였다. 두 모형의 증발산량은 SEBAL 모형의 경우 지형에 따라 SWAT 모형은 토양 특성에 따라 분포하는 경향이 다르게 나타났다. SEBAL 모형은 주로 저지대에서 증발산량이 높게 산정되며 고지대로 갈수록 감소하여 증발산량이 지형의 고저차에 따라 분포하는 모습을 보였다. SWAT 모형은 토양 특성에 따라 증발산량이 분포하며 유역 내에서 뚜렷한 차이를 나타내지는 않았다. 월별 총 증발산량은 SWAT 모형의 경우 7~8월에 약 90 mm/mon로 가장 높게 나타나고 1~2월은 0 mm/mon로 계절별 변화폭이 컸으나, SEBAL 모형의 경우 5~6월에 증발산량이 약 60 mm/mon로 가장 높게 나타났고 계절별 변화 폭이 SWAT 모형에 비해 적은 모습을 보였다. 이는 위성영상을 기반으로 하는 SEBAL 모형의 특성상 장마 기간에 해당하는 7~8월은 구름으로 인해 일사량이 적게 계산되고, 그 결과 5~6월에 비해 증발산량이 작게 산정되는 것으로 판단된다.

• Ocean and Polar Research
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• v.43 no.4
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• pp.321-334
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• 2021

'Marine mammals-based observations' refers to data acquisition activities from marine mammals by instrumenting CTD (Conductivity-Temperature-Depth) sensors on them for recording vertical profiles of ocean variables such as temperature and salinity during animal diving. It is a novel data collecting platform that significantly improves our abilities in observing extreme environments such as the Southern Ocean with low cost compared to the other conventional methods. Furthermore, the system continues to create valuable information until sensors are detached, expanding data coverage in both space and time. Owing to these practical advantages, the marine mammals-based observations become popular to investigate ocean circulation changes in the Southern Ocean. Although these merits may bring us more opportunities to understand ocean changes, the data should be carefully qualified before we interpret it incorporating shipboard/autonomous vehicles/moored CTD data. In particular, we need to pay more attention to salinity correction due to the usage of an unpumped-CTD sensor tagged on marine mammals. In this article, we introduce quality control methods for the marine mammals-based CTD profiles that have been developed in recent studies. In addition, we discuss strategies of quality control specifically for the seal-tagging CTD profiles, successfully having been obtained near Terra Nova Bay, Ross Sea, Antarctica since February 2021. It is the Korea Polar Research Institute's research initiative of animal-borne instruments monitoring in the region. We anticipate that this initiative would facilitate collaborative efforts among Polar physical oceanographers and even marine mammal behavior researchers to understand better rapid changes in marine environments in the warming world.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.30-44
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• 2022

The advent of deep learning-based algorithms has facilitated researches on target detection from synthetic aperture radar(SAR) imagery. While most of them concentrate on detection tasks for ships with open SAR ship datasets and for aircraft from SAR scenes of airports, there is relatively scarce researches on the detection of SAR ground vehicle targets where several adverse factors such as high false alarm rates, low signal-to-clutter ratios, and multiple targets in close proximity are predicted to degrade the performances. In this paper, a dataset of ground vehicle targets acquired from TerraSAR-X(TSX) satellite SAR images is presented. Then, both detection and instance segmentation are simultaneously carried out on this dataset based on the deep learning-based Mask R-CNN. Finally, this paper shows the future research directions to further improve the performances of detecting the SAR ground vehicle targets.