• 대한원격탐사학회지
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• 제40권4호
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• 한국산림과학회지
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• 제83권1호
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• pp.75-87
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• 1994

원격탐사(遠隔探査), 지리정보(地理情報)시스템 및 산림경영기술(山林經營技術)의 발달(發達)과 함께 산림조사(山林調査) 및 경영(經營)에 있어서 신경향(新傾向)이 대두(擡頭)되고 있다. 이러한 기술(技術)들은 서로간에 개별적(個別的)인 것은 아니다. 컴퓨터의 자료처리능력(資料處理能力)이 증대(增大)되고 가격(價格)이 감소(減少)함으로 해서 수치원격탐사(數値遠隔探査)는 보다 실질적(實質的)으로 응용(應用)되어질 수가 있다. 이러한 발달(發達)로 화상분석(畫像分析)시스템 및 지리정보(地理情報)시스템 등은 마이크로컴퓨터를 이용(利用)하여 처리(處理)할 수 있게 되었다. 뿐만 아니라, 이러한 원격탐사기술(遠隔探査技術)과 지리정보(地理情報)시스템은 점차적(漸次的)으로 접목(接木)되어져, 중앙기관(中央機關) 및 지방부서(地方部暑)에서도 이를 이용(利用)한 실질적(實質的)인 업무활용(業務活用)이 시도(試圖)되고 있다. 본교(本橋)에서는 원격탐사기술(遠隔探査技術)의 현황(現況)과 산림조사(山林調査) 및 경영(經營)에의 응용(應用)에 관하여 고찰(考察)하였다. 지역적(地域的) 생물다양성분석(生物多樣性分析)을 위해 가용(可用)한 원격탐사자료(遠隔探査資料)에 대한 상대적(相對的) 장단점(長短點)을 요약(要約)하였으며, 토지이용(土地利用) 및 피복도(被覆圖) 작성(作成)에 적합(適合)한 랜샛 MSS와 TM 그리고 SPOT 등의 자료(資料)에 국한(局限)하여 고찰(考察)하였다.

• 대한원격탐사학회지
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• 제33권5_3호
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• pp.763-771
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• 2017

본 사설은 대한원격탐사학회지의 환경공간정보 이해와 활용 특별호 발간의 배경과 목적 그리고 발간 논문의 의의 고찰을 목적으로 한다. 환경정보는 환경과 관련된 정보(문헌, 통계 및 이미지 등)를 포괄적으로 의미한다. 이러한 환경정보가 지역적으로 발생하는 환경의 변화나 이슈로써 공간적인 형태로 발전하여 환경공간정보로 정의된다. 원격탐사자료는 광역 국지적인 환경에 대한 정보를 포함하여 환경공간정보에 대한 직 간접적인 자료로 매우 높은 활용성을 지니고 있으며, 몇 가지 개선을 통하여 환경분야에 국한되지 않고 보다 다양한 활용이 가능할 것이다. 이를 위하여 첫째, 환경공간정보 구축 기반기술의 정밀화 및 과학화하여 활용을 증대할 수 있다. 둘째, 기존의 환경공간정보의 개념과 내용을 확대함으로써 활용분야를 넓힐 수 있다. 셋째, 기존 환경공간정보의 활용을 지속적으로 증가시키는 것이다. 본 논문에서는 환경공간정보의 최근 변화(데이터의 형식의 전환 및 ICT(Information and Communications Technologies)와 접목 등)를 반영한 발전방향을 고찰하였다. 특히, 환경공간정보 구축의 기본이 되는 기반기술이 정밀화 및 과학화를 다양한 논문을 통하여 고찰하였다. 위와 관련된 연구를 통해 국내 환경공간정보의 활용을 다각화시키고 이를 활용한 정책개발 및 환경요소의 효율적인 관리가 가능할 것이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.118-121
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• 2007

In recent years, the hyperspectral instruments with high spatial and high spectral resolution have become an important component of wide variety of earth science applications. The primary mission of the proposed Compact Airborne Imaging Spectrometer System (CAISS) in this study is to acquire and provide full contiguous spectral information with high quality spectral and spatial resolution for advanced applications in the field of remote sensing. The CAISS will also be used as the vicarious calibration equipment for the cross-calibration of satellite image data. The CAISS consists of six physical units: the camera system, the Jig, the GPS/INS, the gyro-stabilized mount, the operating system, and the power inverter and distributor. Additionally, the calibration instruments such as the integrated sphere and spectral lamps are also prepared for the radiometric and spectral calibration of the CAISS. The CAISS will provide high quality calibrated image data that can support evaluation of satellite application products. This paper summarizes the design, development and major characteristic of the CAISS.

• 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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• 대한원격탐사학회지
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• 제36권5_3호
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• pp.1007-1011
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• 2020

오늘날 기후변화와 더불어 각종 기상/기후 자연재난 및 인재의 발생 빈도가 증가하는 추세이다. 원격탐사 기술은 재난 상황에서 연속적인 모니터링과 빠른 탐지를 가능하게 하며, 최근에는 군집 위성, 초소형 위성, 그리고 드론 등이 이용돼 그 활용도가 증가하고 있다. 본 특별 호에서는 재난 상황에서 위성을 활용하기 위한 기반 기술과 각종 자연재해를 모니터링, 분석 및 예측하는 활용 기술에 대한 9편의 논문을 소개하고 있다. 소개된 논문들은 향후 증가하는 위성 활용에 있어 재난 분야에서의 유용한 참조자료가 될 것으로 기대된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2009년도 춘계학술대회 논문집
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• pp.286-290
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• 2009

In recent years, LiDAR technology has been becoming more popular and important. Its applications are completely replacing the traditional remote sensing technique. One of these applications is creating Digital City Models in urban areas, which is essential for many others such as disaster management, cartographic mapping, simulation of new buildings, updating and keeping cadastral data. In most of these cases the building outlines is the primary feature of interest. In this paper, a method of extracting building outlines from LiDAR data will be performed.

• 대한원격탐사학회지
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• 제23권3호
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• pp.189-198
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• 2007

Introduction of lidar technology have contributed to a wide range of applications in generating quality surface models. Accordingly, because of the importance of terrain surface models in mapping applications, rigorous studies have been performed to extract ground points from a lidar data point cloud. Although most filters have been shown abilities to extract ground points with their parameters tuned, however, most experiments revealed that there are certain limitations in optimizing filter parameters and the correction of remaining misclassified points is not straightforward. In this study, therefore, a method to improve the quality of filtered lidar data is proposed, which exploits neighboring surface properties arising between immediate neighbors. The method comprises a sequence of procedures which can reduce commission and omission errors. Commission errors occurring in low-rise objects are reduced by utilizing morphological operations. On the other hand, omission errors are reduced by adding missing ground points around step edges. Experimental results show that the qualities of filtered data can be improved considerably by the proposed method.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2005년도 국제학술회의
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• pp.100-113
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• 2005

Leaf color and plant vigor are key indicators of crop health. These visual plant attributes are frequently used by greenhouse managers, producers, and consultants to make water, nutrient, and disease management decisions. Remote sensing techniques can quickly quantify soil and plant attributes, but it requires humans to translate such data into meaningful information. Over time, scientists have used reflectance data from individual wavebands to develop a series of indices that attempt to quantify things like soil organic matter content, leaf chlorophyll concentration, leaf area index, vegetative cover, amount of living biomass, and grain yield. The recent introduction of active sensors that function independent of natural light has greatly expanded the capabilities of scientists and managers to obtain useful information. Characteristics and limitations of active sensors need to be understood to optimize their use for making improved management decisions. Pot experiments involving sand culture were conducted in 2003 and 2004 in a green house to evaluate corn and red pepper biomass. The rNDVI, gNDVI and aNDVI by ground-based remote sensors were used for evaluation of corn and red pepper biomass. The result obtained from the case study was shown that ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season crop nitrogen management providing both spatial and temporal information.