• Title/Summary/Keyword: 지상 반사도

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Classification and Mapping of Forest Type Using Landsat TM Data and B/W Infrared Aerial Photograph (Landsat TM Data와 흑백적외선(黑白赤外線) 항공사진(航空寫眞)을 이용(利用)한 임상구분(林相區分)에 관(關)한 연구(硏究))

  • Kim, Kap Duk;Lee, Seung Ho;Kim, Cheol Min
    • Journal of Korean Society of Forest Science
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    • v.78 no.3
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    • pp.263-273
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    • 1989
  • Accurate and cost-effective classification of forest vegetation is the primary goal for forest management and utilization of forest resources. Aerial photograph and remote sensing are the most frequent and effective method in forest resources inventories. TM and MSS are the principal observing instruments on the Landsat-4 and -5 earth observing satellite. Especially TM has considerably greater spatial, spectral, and radiometric resolution power than MSS, that is, the IFOV of TM at a nadir is 30m compared to 80m for MSS. In this study, we used TM data to classify forest types and compared the result with forest type map manufactured by interpretation of B/W infrared photographs. As a result, land use types were well defined with TM data. But classifying forest types was a little difficult and indistinct. However, the spectral signatures of forest in every season and growing stages remained as problems to be solved, and also the most effective selection and combination method of bands for differentiating the spectral plots among classes.

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Studies on the Light Organ of the Firefly, Luciola lateralis Motschulsky (애반딧불이의 발광기관 구조)

  • 이대우;부경생
    • Korean journal of applied entomology
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    • v.30 no.1
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    • pp.29-36
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    • 1991
  • Studies were carried out to investigate structural characteristics of the larval and adult light organs of Luciola lateralis Mot. and to observe the relation between the light organ and nerve. The larval light organs, (LLO)existed at a paired dorsal lateral positions of the 8th abdominal segment. The organ was spherical or sub-spherical in shape. There were many vacuoles around the LLO. As larva grew, the number of vacuoles increased. LLO had the muscles in its interior part and their role seemed to fix the LLO position in space. Also, there were the tracheae and tracheoles in LLO. The Adult light organs (ALO) were at the ventral portions of the 5th and 6th abdominal segments in the male, but only on the 5th abdominal segment in the female. ALO had two functional layers, i.e., photocyte and dorsal layer. Tracheal end organs existed in both layers but their arrangements were irregular. Rod-shaped photocytes and spherical photocytes were observed in the ALO of male and female, but the rod-shaped types were rarely found in the female. In the ALO of the 5th abdominal segment, two paired peripheral nerves were originated from the anterior part of the last abdominal compound ganglion. A pair of peripheral nerves were originated from the posterior part of the compound ganglion to innervate the 6th abdominal segment ALO. And LLO was innervated by a paired peripheral nerves from the last abdominal ganglion.

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Cavity-Backed Slot Array Antenna for a Repeater System of a Satellite Digital Multimedia Broadcasting (위성 DMB 중계기용 Cavity-Backed슬롯 배열 안테나)

  • Jung Hee-Chul;Lee Hak-Yong;Jung Byungwoon;Kang Gi-Cho;Park Myun-Joo;Lee Byungje
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.4 s.95
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    • pp.366-372
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    • 2005
  • This paper presents analysis of a slot array antenna having a low side lobe level and high front-to-back ratio for a repeater system of a satellite DMB(Digital Multimedia Broadcasting) service. Antennas for this repeater system require a high gain and enough isolation to reduce interferences between signals in system. Therefore, it is necessary to suppress a side lobe level and to increase front-to-back ratio. Unlike a structure 134 by lossy microstrip lines, in this work a single cavity-backed slot antenna array using a single waveguide feed is proposed to obtain the reliability for high power handling and high radiation efficiency. The side lobe level and front-to-back ratio are enhanced with tapered array technique and an optimized vertical reflector. The measured side lobe levels in H- and E-plane are under $-33.24\;\cal{dB}$ and $-35.78\;\cal{dB}$, respectively. The front-to-back ratio over $37.84\;\cal{dB}$, and the peak gain of over $17\;\cal{dBi}$ are measured.

Detection of Artificial Displacement of a Reflector by using GB-SAR Interferometry and Atmospheric Humidity Correction (GB-SAR 간섭기법을 이용한 반사체의 인위적 변위탐지 및 대기습도보정)

  • Lee, Jae-Hee;Lee, Hoon-Yol;Cho, Seong-Jun;Sung, Nak-Hun;Kim, Jung-Ho
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.123-131
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    • 2010
  • In this paper we applied Ground-Based Synthetic Aperture Radar(GB-SAR) interferometry to detect artificial displacement of a reflector and performed an atmospheric humidity correction to improve the accuracy. A series of GB-SAR images were obtained using a center frequency of 5.3 GHz with a range resolution of 25 cm and a azimuth resolution of $0.324^{\circ}$, all in full-polarization (HH, VV, VH, HV) modes. A triangular trihedral corner reflector was located 160 m away from the system, and the artificial displacements of 0-40 mm was implemented during the GB-SAR image acquisition. The result showed that the RMS error between the actual and measured displacements, averaged in all polarization data, was 1.22 mm, while the maximum error in case of the 40 mm displacement was 2.72 mm at HH-polarization. After the atmospheric correction with respect to the humidity, the RMS error was reduced to 0.52 mm. We conclude that a GB-SAR system can be used to monitor the possible displacement of artificial/natural scatterers and the stability assessment with sub-millimeter accuracy.

Crop Monitoring Technique Using Spectral Reflectance Sensor Data and Standard Growth Information (지상 고정형 작물 원격탐사 센서 자료와 표준 생육정보를 융합한 작물 모니터링 기법)

  • Kim, Hyunki;Moon, Hyun-Dong;Ryu, Jae-Hyun;Kwon, Dong-Won;Baek, Jae-Kyeong;Seo, Myung-Chul;Cho, Jaeil
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1199-1206
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    • 2021
  • Accordingly, attention is also being paid to the agricultural use of remote sensing technique that non-destructively and continuously detects the growth and physiological status of crops. However, when remote sensing techniques are used for crop monitoring, it is possible to continuously monitor the abnormality of crops in real time. For this, standard growth information of crops is required and relative growth considering the cultivation environment must be identified. With the relationship between GDD (Growing Degree Days), which is the cumulative temperature related to crop growth obtained from ideal cultivation management, and the vegetation index as standard growth information, compared with the vegetation index observed with the spectralreflectance sensor(SRSNDVI & SRSPRI) in each rice paddy treated with standard cultivation management and non-fertilized, it was quantitatively identified as a time series. In the future, it is necessary to accumulate a database targeting various climatic conditions and varieties in the standard cultivation management area to establish a more reliable standard growth information.

Change Analysis of Aboveground Forest Carbon Stocks According to the Land Cover Change Using Multi-Temporal Landsat TM Images and Machine Learning Algorithms (다시기 Landsat TM 영상과 기계학습을 이용한 토지피복변화에 따른 산림탄소저장량 변화 분석)

  • LEE, Jung-Hee;IM, Jung-Ho;KIM, Kyoung-Min;HEO, Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.4
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    • pp.81-99
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    • 2015
  • The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

A Study on Daytime Transparent Cloud Detection through Machine Learning: Using GK-2A/AMI (기계학습을 통한 주간 반투명 구름탐지 연구: GK-2A/AMI를 이용하여)

  • Byeon, Yugyeong;Jin, Donghyun;Seong, Noh-hun;Woo, Jongho;Jeon, Uujin;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1181-1189
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    • 2022
  • Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.

Geophysical Evidence Indicating the Presence of Gas Hydrates in a Mud Volcano(MV420) in the Canadian Beaufort Sea (캐나다 보퍼트해 진흙화산(MV420) 내 가스하이드레이트 부존을 지시하는 지구물리학적 증거)

  • Yeonjin Choi;Young-Gyun Kim;Seung-Goo Kang;Young Keun Jin;Jong Kuk Hong;Wookeen Chung;Sung-Ryul Shin
    • Geophysics and Geophysical Exploration
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    • v.26 no.1
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    • pp.18-30
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    • 2023
  • Submarine mud volcanos are topographic features that resemble volcanoes, and are formed due to eruptions of fluidized or gasified sediment material. They have gained attention as a source of subsurface heat, sediment, or hydrocarbons supplied to the surface. In the continental slope of the Canadian Beaufort Sea, mud volcano exists at various water depths. The MV420, is an active mud volcano erupting at a water depth of 420 meters, and it has been the subject of extensive study. The Korea Polar Research Institute(KOPRI) collected high-resolution seismic data and heat flow data around the caldera of the mud volcano. By analyzing the multi-channel seismic data, we confirmed the reverse-polarity reflector assumed by a gas hydrate-related bottom simulating reflector(BSR). To further elucidate the relationship between the BSR and gas hydrates, as well as the thermal structure of the mud volcano, a numerical geothermal model was developed based on the steady-state heat equation. Using this model, we estimated the base of the gas hydrate stability zone and found that the BSR depth estimated by multi-channel seismic data and the bottom of the gas hydrate stability zone were in good agreement., This suggests the presence of gas hydrates, and it was determined that the depth of the gas hydrate was likely up to 50 m, depending on the distance from the mud conduit. Thus, this depth estimate slightly differs from previous studies.

An Analysis on the Episodes of Large-scale Transport of Natural Airborne Particles and Anthropogenically Affected Particles from Different Sources in the East Asian Continent in 2008 (2008년 동아시아 대륙으로부터 기원이 다른 먼지와 인위적 오염 입자의 광역적 이동 사례에 대한 분석)

  • Kim, Hak-Sung;Yoon, Ma-Byong;Sohn, Jung-Joo
    • Journal of the Korean earth science society
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    • v.31 no.6
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    • pp.600-607
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    • 2010
  • In 2008, multiple episodes of large-scale transport of natural airborne particles and anthropogenically affected particles from different sources in the East Asian continent were identified in the National Oceanic and Atmospheric Administration (NOAA) satellite RGB-composite images and the mass concentrations of ground level particulate matters. To analyze the aerosol size distribution during the large-scale transport of atmospheric aerosols, both aerosol optical depth (AOD; proportional to the aerosol total loading in the vertical column) and fine aerosol weighting (FW; fractional contribution of fine aerosol to the total AOD) of Moderate resolution Imaging Spectroradiometer (MODIS) aerosol products were used over the East Asian region. The six episodes of massive natural airborne particles were observed at Cheongwon, originating from sandstorms in northern China, Mongolia and the loess plateau of China. The $PM_{10}$ and $PM_{2.5}$ stood at 70% and 16% of the total mass concentration of TSP, respectively. However, the mass concentration of $PM_{2.5}$ among TSP increased as high as 23% in the episode in which they were flowing in by way f the industrial area in east China. In the other five episodes of anthropogenically affected particles that flowed into the Korean Peninsula from east China, the mass concentrations of $PM_{10}$ and $PM_{2.5}$ among TSP reached 82% and 65%, respectively. The average AOD for the large-scale transport of anthropogenically affected particle episodes in the East Asian region was measured at $0.42{\pm}0.17$ compared with AOD ($0.36{\pm}0.13$) for the natural airborne particle episodes. Particularly, the regions covering east China, the Yellow Sea, the Korean Peninsula, and the east Korean sea were characterized by high levels of AOD. The average FW values observed during the event of anthropogenically affected aerosols ($0.63{\pm}0.16$) were moderately higher than those of natural airborne particles ($0.52{\pm}0.13$). This observation suggests that anthropogenically affected particles contribute greatly to the atmospheric aerosols in East Asia.

Estimation of Rice Grain Protein Contents Using Ground Optical Remote Sensors (지상광학센서를 이용한 쌀 단백질함량 예측)

  • Kim, Yi-Hyun;Hong, Suk-Young
    • Korean Journal of Remote Sensing
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    • v.24 no.6
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    • pp.551-558
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    • 2008
  • It is well known that the protein content of rice grain is an indicator of taste of cooked rice in the countries where people as the staple food. Ground-based optical sensing over the crop canopy would provide information not only on the mass of plant body which reflects the light, but also on the crop nitrogen content which is closely related to the greenness of plant leaves. The vegetation index has been related to crop variables such as biomass, leaf nitrogen, plant cover, and chlorophyll in cereals. The objective of this study was to investigate the correlation between GNDVI and NDVI values, and grain protein content at different dates and to estimate the grain protein content using G(NDVI) values. We measured Green normalized difference vegetation index [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$] and [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$] by using two different active sensors. The study was conducted during the rice growing season for three years from 2005 through 2007 at the experimental plots of National Institute of Agricultural Science and Technology. The experiments were carried out by randomized complete block design with the application of four levels of nitrogen fertilizers(0, 70, 100, 130kg N/ha) and the same amount of phosphorous and potassium content of the fertilizers. After heading stage, relationships between GNDVI of rice canopy and grain protein content showed the highly positive correlation at different dates for three years. GNDVI values showed higher correlation coefficients than that of NDVI during growing season in 2005-07. The correlation between GNDVI values at different dates and grain protein contents was highly correlated at early July. We attempted to estimate the grain protein content at harvesting stage using GNDVI values from early July for three years. The determination coefficients of the linear model by GNDVI values were 0.9l and the measured and estimated grain protein content at harvesting stage using GNDVI values highly correlated($R^2=0.96^{***}$). Results from this study show that GNDVI appeared very effective to estimate leaf nitrogen and grain protein content of rice canopy.