• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.409-414
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• 1998

To examine the detectability of the aerosol and/or Yellow dust from China crossing over the Yellow sea, three works carried out as follows , Firstly, a comparison was made of the visible(VIS), water vapor(WV), and Infrared(IR) images of the GMS-5 and NOAA/AVHRR on the cases of yellow sand event over Korea. Secondly, the spectral radiance and reflectance(%) was observed during the yellow sand phenomena on April, 1998 in Seoul using the GER-2600 spectroradiometer, which observed the reflected radiance from 350 to 2500 nm in the atmosphere. We selected the optimum wavelength for detecting of the yellow sand from this observation, considering the effects of atmospheric absorption. Finally, the atmospheric radiance emerging from the LOWTRAN-7 radiative transfer model was simulated with and without yellow sand, where we used the estimated aerosol column optical depth ($\tau$ 673 nm) in the Meteorological Research Institute and the d'Almeida's statistical atmospheric aerosol radiative characteristics. The image analysis showed that it was very difficult to detect the yellow sand region only by the image processing because the albedo characteristics of the sand vary irregularly according to the density, size, components and depth of the yellow sand clouds. We found that the 670-680 nm band was useful to simulate aerosol characteristics considering the absorption band from the radiance observation. We are now processing the simulation of atmospheric radiance distribution in the range of 400-900 nm. The purpose of this study is to present the preliminary results of the aerosol and/or Yellow dust detectability using the Ocean Scanning Multispectral Imager(OSMI), which will be mounted on KOMPSAT-1 as the ocean color monitoring sensor with the range of 400-900 nm wavelength.

• 한국농공학회논문집
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• 제62권6호
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• 한국콘텐츠학회논문지
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• 제9권6호
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• pp.436-443
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• 2009

사회 전 분야에 걸쳐 다양하고 복잡한 공간의 현상을 모델링하여 컴퓨터를 통해 공간 데이터를 사용하고자 하는 요구가 급격하게 증가하면서 원격탐사와 GIS의 중요성과 활용도가 증대되고 있다. 원격탐사영상자료를 GIS의 분석기술과 연계하여 사용함으로써 높은 정확도와 가치를 지닌 수치자료의 생성이 가능하며, 토지피복 분류와 분석 등을 수행함으로써 다양한 주제도의 제공이 가능하다. 대상 지역에 대한 이러한 지도의 구축이 가능케 되면, 이 지도를 기초로 하여 모델링 및 지속적인 모니터링이 용이하며, 데이터베이스의 수정을 쉽게 함으로써 지형공간정보의 갱신이 효율적으로 수행되어 질 수 있다. 이 연구에서는 원격탐사 기술과 GIS의 통합을 통하여 도로변의 토지피복변화를 분석하기 위해 두시기의 영상에 대한 토지피복분류를 수행하고 6개의 분류항목별 10년간의 변화탐지를 수행하여 대상지역에 대한 정량적 변화면적 통계값을 추출함으로써 도시계획 수립 및 개발을 위한 기초 의사결정 자료를 획득하는 것이다. 도로주변의 이용형태분석을 통하여 주변 도심과의 상호 보완된 계획의 수립을 가능하게 할 것이다.

• 대한원격탐사학회지
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• 제17권4호
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• pp.285-295
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• 2001

We developed a CASE-II water model that will enable the simulation of remote sensing reflectance($R_{rs}$) at the coastal waters for the retrieval of suspended sediments (SS) concentrations from satellite imagery. The model has six components which are: water, chlorophyll, dissolved organic matter (DOM), non-chlorophyllous particles (NC), heterotrophic microorganisms and an unknown component, possibly represented by bubbles or other particulates unrelated to the five first components. We measured $R_{rs}$, concentration of SS and chlorophyll, and absorption of DOM during our field campaigns in Korea. In addition, we generated $R_{rs}$ from different concentrations of SS and chlorophyll, and various absorptions of DOM by random number functions to create a large database to test the model. We assimilated both the computer generated parameters as well as the in-situ measurements in order to reconstruct the reflectance spectra. We validated the model by comparing model-reconstructed spectra with observed spectra. The estimated $R_{rs}$ spectra were used to (1) evaluate the performance of four wavelengths and wavelengths ratios for accurate retrieval of SS. 2) identify the optimum band for SS retrieval, and 3) assess the influence of the SS on the chlorophyll algorithm. The results indicate that single bands at longer wavelengths in visible better results than commonly used channel ratios. The wavelength of 625nm is suggested as a new and optimal wavelength for SS retrieval. Because this wavelength is not available from SeaWiFS, 555nm is offered as an alternative. The presence of SS in coastal areas can lead to overestimation chlorophyll concentrations greater than 20-500%.

• 대한원격탐사학회지
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• 제25권6호
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• 대한원격탐사학회지
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• 제20권6호
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• pp.383-396
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• 2004

이 논문은 원격탐사 화상 분류에서 공간적 불확실성 분포를 얻기 위해 공간 통계를 적용하였다. 분류 항목 할당과 참조 자료와 연계된 각각의 불확실성 표현을 위해 2가지 정량적 방법을 제안하였다. 우선 분류 항목 할당에 따른 불확실성 표현을 위해 3가지 정량적 지수를 제안하였다. 그리고 참조 자료와 분류 결과를 결합하고 이와 연계된 불확실성 혹은 정확성 분포를 얼기 위해 지구통계학적 시뮬레이션 기법을 적용하였다. 다중 센서 원격탐사 화상을 이용한 감독 토지 피복 분류 실험을 수행하여 제안 방법을 예시하고, 적용시 제안점을 논의하였다. 실험 결과, 이 논문에서 제시한 방법론을 통해 분류 결과의 해석과 평가를 위한 부가적인 정보추출이 가능하였으며, 제시 방법론의 검증을 위한 다양한 자료에의 적용이 필요한 것으로 판단된다.

• 대한원격탐사학회지
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• 제22권3호
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• 대한원격탐사학회지
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• 제21권1호
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• pp.73-81
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• 2005

We construct improved geocentric digital elevation model (DEM), estimate tidal dynamics and ice stream velocity over Sulzberger Ice Shelf, West Antarctica employing differential interferograms from 12 ERS tandem mission Synthetic Aperture Radar (SAR) images acquired in austral fall of 1996. Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles acquired in the same season as the SAR scenes in 2004 are used as ground control points (GCPs) for Interferometric SAR (InSAR) DEM generation. 20 additional ICESat profiles acquired in 2003-2004 are then used to assess the accuracy of the DEM. The vertical accuracy of the OEM is estimated by comparing elevations with laser altimetry data from ICESat. The mean height difference between all ICESat data and DEM is -0.57m with a standard deviation of 5.88m. We demonstrate that ICESat elevations can be successfully used as GCPs to improve the accuracy of an InSAR derived DEM. In addition, the magnitude and the direction of tidal changes estimated from interferogram are compared with those predicted tidal differences from four ocean tide models. Tidal deformation measured in InSAR is -16.7cm and it agrees well within 3cm with predicted ones from tide models. Lastly, ice surface velocity is estimated by combining speckle matching technique and InSAR line-of-sight measurement. This study shows that the maximum speed and mean speed are 509 m/yr and 131 m/yr, respectively. Our results can be useful for the mass balance study in this area and sea level change.

• 대한원격탐사학회지
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• 제11권1호
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• pp.65-80
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• 1995

기상관측자료와 더불어 원격탐사자료를 이용함으로서 서로 다른 공간 및 시간스케일에 대한 에너지수직의 3성분을 추정할 수 있으며 결과적으로는 잠열의 추정을 가능하게 하였다. 이 러한 접근법을 응용하여 본 연구에서는 기상 및 위성자료를 바탕으로 지표에너지 관계식을 이용 한 광역증발산량 추정하는 방법에 대하여 검토하였다. 또한 토지이용의 변화에 따른 지표면열수 지의 변화를 평가하기 위하여 지리정보시스템분석 방법을 사용하여 검토하였다. 그 결과 연구지 역의 토지이용변화는 지역내의 열수지에 상당한 변화를 가져오는 것으로 나타났다. 본 연구의 결 과를 향상시키기 위해서는 열수지의 계산에 사용되는 각 추정식의 정확도 향상과 지표면의 상태 를 위성 원격탐사로서 정확하게 파악할 필요가 있다.

• 대한원격탐사학회지
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• 제37권6_2호
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• pp.1785-1791
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• 2021

최근 전세계적 자연재해는 도시화, 산업화 및 인구 증가로 인해 대형·복합화 되고있으며,특히 기후변화로 인한 대규모 자연재해의 발생 건수가 급속도로 증가하고 있다. 따라서, 심층 분석을 통한 과거 재해에 대한 이해와 향후 발생 가능한 재해의 피해 범위 감소 및 위해성 평가에 관한 연구가 절실히 필요한 실정이다. 본 특별호는 자연재해·재난분야를 대상으로 원격탐사와 GIS를 이용한 관측과 관리 기술에 관련한 연구들을 살펴보고, 최근 부경대학교 i-SEED 지구환경교육연구단에서 진행하고 있는 폭염, 미세먼지, 홍수, 가뭄, 지진에 관련한 연구 내용 및 결과를 소개하고자 한다. 이러한 연구결과는 자연재해로 인한 피해 완화 및 향후 자연재해를 대비한 사전 예방과 사후 관리에 도움을 줄 수 있을 것으로 판단된다.