• Ocean Science Journal
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• 제42권1호
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• pp.49-59
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• 2007

Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyll-a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

• Advances in aircraft and spacecraft science
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• 제10권1호
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• pp.67-82
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• 2023

Linear array imaging sensors are widely used in remote sensing satellites. The final products of an imaging sensor can only be used when they are geometrically, radiometrically, and spectrally calibrated. Therefore, at the first stages of sensor design, a detailed calibration procedure must be carefully planned based on the accuracy requirements. In this paper, focusing on inherent optical distortion, a step-by-step procedure for laboratory geometric calibration of a typical push-broom satellite imaging sensor is simulated. The basis of this work is the simulation of a laboratory procedure in which a linear imager mounted on a rotary table captures images of a pin-hole pattern at different angles. By these images and their corresponding pinhole approximation, the correction function is extracted and applied to the raw images to give the corrected ones. The simulation results illustrate that using this approach, the nonlinear effects of distortion can be minimized and therefore the accuracy of the geometric position of this method on the image screen can be improved to better than the order of sub-pixel. On the other hand, the analyses can be used to proper laboratory facility selection based on the imaging sensor specifications and the accuracy.

• 대한원격탐사학회지
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• 제39권6_3호
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• pp.1671-1678
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• 2023

다중 센서로 구성된 다목적실용위성 시리즈는 1999년 1호 발사 후 현재까지 국토 및 환경 모니터링, 재난 분석 등 다양한 분야에서 활용되어 왔다. 최근 빠르게 발전하고 있는 각종 정보처리기술(고속 컴퓨팅 기술, 컴퓨터 비전, 인공지능 등)들이 원격탐사 분야에서도 활용됨에 따라 보다 다양한 위성영상 처리 및 분석 알고리즘 개발이 가능하게 되었다. 본 특별호에서는 최근 연구된 다목적실용위성 영상 활용 관련 기술과 2023 위성정보활용 경진대회에 참여한 연구주제에 관하여 소개하고자 한다.

• 대한원격탐사학회지
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• 제37권5_3호
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• pp.1341-1347
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• 2021

대규모 피해를 유발하는 재난의 발생 횟수가 증가하면서 효과적인 재난 대응 체계를 수립하여 국민의 안전 사회를 구현하기 위한 노력이 지속되고 있다. 재난에 의한 피해는 다양한 양상으로 발전할 수 있으므로 신속하고 정확한 대응 방안을 마련해야 하며, 이를 지원할 수 있는 유용한 기술로 원격탐사 기술과 GIS(Geographic Information System) 분석 기술에 관한 다양한 연구가 수행되고 있다. 본 특별호에서는 우주-항공-지상을 아우르는 다양한 시공간 도메인을 가진 원격탐사 센서를 이용한 재난 예측 및 감시 연구와 이로부터 취득된 정보와 기존의 공간정보를 융합한 GIS 재난관리에 관한 연구성과를 기술하였다. 소개된 기술은 풍수해, 산불 등 다양한 유형의 재난관리 기술로, 각 기술 간 연계를 통해 최근 필요성이 대두되고 있는 종합적 재난상황관리체계 구축이 가능할 것으로 기대된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.1011-1014
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• 2006

Coarse resolution (9 - 50 km pixels) Sea Surface Temperature satellite data are frequently considered adequate for open ocean research. However, coastal regions, including coral reef, estuarine and mesoscale upwelling regions require high-resolution (1-km pixel) SST data. The AVHRR SST data often suffer from navigation errors of several kilometres and still require manual navigation adjustments. The second serious problem is faulty and ineffective cloud-detection algorithms used operationally; many of these are based on radiance thresholds and moving window tests. With these methods, increasing sensitivity leads to masking of valid pixels. These errors lead to significant cold pixel biases and hamper image compositing, anomaly detection, and time-series analysis. Here, after manual navigation of over 40,000 AVHRR images, we implemented a new cloud filter that differs from other published methods. The filter first compares a pixel value with a climatological value built from the historical database, and then tests it against a time-based median value derived for that pixel from all satellite passes collected within ${\pm}3$ days. If the difference is larger than a predefined threshold, the pixel is flagged as cloud. We tested the method and compared to in situ SST from several shallow water buoys in the Florida Keys. Cloud statistics from all satellite sensors (AVHRR, MODIS) shows that a climatology filter with a $4^{\circ}C$ threshold and a median filter threshold of $2^{\circ}C$ are effective and accurate to filter clouds without masking good data. RMS difference between concurrent in situ and satellite SST data for the shallow waters (< 10 m bottom depth) is < $1^{\circ}C$, with only a small bias. The filter has been applied to the entire series of high-resolution SST data since1993 (including MODIS SST data since 2003), and a climatology is constructed to serve as the baseline to detect anomaly events.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.450-453
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• 2005

A forest fire occurs mainly as natural factor such as wind, temperature or human factor such as light. Recently, the most of forest fire prevention is prediction or prevision against forest fire by using remote sensing technology. However in order to forest fire prevention, the remote sensing has many limitations such as high cost and advanced technologies and so on. Therefore, we need to multisensor integration system that utilize not only remote sensing but also in-situ sensing in order to reduce large damage of forest fire though analysis of happen cause and prediction routing of occurred forest fire. In this paper we propose a multisensor integration system that offers prediction information of factors and route of forest fire by integrates collected data from remote sensor and in-situ sensor for forest fire prevention. The proposed system is based on wireless sensor network for collect observed data from various sensors. The proposed system not only offers great quality information because firstly, raw data level fuse different format of collected data from remote and in-situ sensor but also accomplish information level fusion based on result of first stage. Offered information from our system can help early prevention of factor and early prevision against occurred forest fire which transfer to SMS service or alert service into monitoring interface of administrator.

• 대한원격탐사학회지
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• 제19권3호
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• 대한원격탐사학회지
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• 제34권6_2호
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• pp.1283-1298
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• 2018

온난화에 의한 이상기후의 징후가 직접적으로 감지되고 있는 북극권에 대한 연구 필요성이 사회적으로 강력히 요구되고 있다. 온난화의 추이를 가장 잘 보여주고 있는 해빙의 변화는 인공위성 원격탐사를 이용하여 추적 감시된다. 극지연구소에서 2017년부터 "북극해빙위성 관측을 위한 기술 개발" 연구를 진행하고 있다. 본 연구는 북극 해빙의 특성 정보를 위성자료로부터 추출하기 위한 다양한 접근법을 이용한 연구를 포함하고 있으며, 북극권 개발에 대비한 '북극 빙권 종합 위성 관측망' 구축에 필수적인 국제 공동 연구 협력도 포함하고 있다. 기후변화 연구와 더불어 북극항로 활용에 대한 기초정보를 제공하고 있는 극지연구소의 북극 원격탐사 연구 소개를 통해 국내 원격탐사 전문가들의 관심과 집중을 부탁하고자 한다. 북극연구에 대한 국제 동향과 국내 정책 배경을 소개하고, 극지연구소에서 연구 수행한 빙권 정보, 특히 한국항공우주연구원과 협동연구를 통해 아리랑위성을 활용한 북극 해빙 관측 연구를 소개한다.

• Smart Structures and Systems
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• 제5권4호
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• pp.381-395
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• 2009

The paper presents a case study in which the structural condition assessment of the East Bay bridge in Gibsonton, Florida is evaluated with the help of remote health monitoring techniques. The bridge is a four-span, continuous, deck-type reinforced concrete structure supported on prestressed pile bents, and is instrumented with smart Fiber Optic Sensors. The sensors used for remote health monitoring are the newly emerged Fabry-Perot (FP), and are both surface-mounted and embedded in the deck. The sensing system can be accessed remotely through fast Digital Subscriber Lines (DSL), which permits the evaluation of the bridge behavior under live traffic loads. The bridge was open to traffic since March 2005, and the collected structural data have been continuously analyzed since. The data revealed an increase in strain readings, which suggests a progression in damage. Recent visual observations also indicated the presence of longitudinal cracks along the bridge length. After the formation of these cracks, the sensors readings were analyzed and used to extrapolate the values of the maximum stresses at the crack location. The data obtained were also compared to initial design values of the bridge under factored gravity and live loads. The study showed that the proposed structural health monitoring technique proved to provide an efficient mean for condition assessment of bridge structures providing it is implemented and analyzed with care.

• 한국토양비료학회지
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• 제36권2호
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• pp.92-103
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• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.