• Title/Summary/Keyword: 근적외선

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Application of Spectral Indices to Drone-based Multispectral Remote Sensing for Algal Bloom Monitoring in the River (하천 녹조 모니터링을 위한 드론 다중분광영상의 분광지수 적용성 평가)

  • Choe, Eunyoung;Jung, Kyung Mi;Yoon, Jong-Su;Jang, Jong Hee;Kim, Mi-Jung;Lee, Ho Joong
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.419-430
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    • 2021
  • Remote sensing techniques using drone-based multispectral image were studied for fast and two-dimensional monitoring of algal blooms in the river. Drone is anticipated to be useful for algal bloom monitoring because of easy access to the field, high spatial resolution, and lowering atmospheric light scattering. In addition, application of multispectral sensors could make image processing and analysis procedures simple, fast, and standardized. Spectral indices derived from the active spectrum of photosynthetic pigments in terrestrial plants and phytoplankton were tested for estimating chlorophyll-a concentrations (Chl-a conc.) from drone-based multispectral image. Spectral indices containing the red-edge band showed high relationships with Chl-a conc. and especially, 3-band model (3BM) and normalized difference chlorophyll index (NDCI) were performed well (R2=0.86, RMSE=7.5). NDCI uses just two spectral bands, red and red-edge, and provides normalized values, so that data processing becomes simple and rapid. The 3BM which was tuned for accurate prediction of Chl-a conc. in productive water bodies adopts originally two spectral bands in the red-edge range, 720 and 760 nm, but here, the near-infrared band replaced the longer red-edge band because the multispectral sensor in this study had only one shorter red-edge band. This index is expected to predict more accurately Chl-a conc. using the sensor specialized with the red-edge range.

Observation of Ice Gradient in Cheonji, Baekdu Mountain Using Modified U-Net from Landsat -5/-7/-8 Images (Landsat 위성 영상으로부터 Modified U-Net을 이용한 백두산 천지 얼음변화도 관측)

  • Lee, Eu-Ru;Lee, Ha-Seong;Park, Sun-Cheon;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1691-1707
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    • 2022
  • Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

Statistical Analysis of Amylose and Protein Content in Breeding Line Rice Germplasm Collected from East Asian Countries Based on Near-infrared reflectance spectroscopy (근적외선분광분석에 의한 육성계통 벼 유전자원의 아밀로스 및 단백질 성분함량에 관한 통계분석)

  • Oh, Sejong;Choi, Yu Mi;Yoon, Hyemyeong;Lee, Sukyeung;Lee, Myung Chul;Shin, Myoung-Jae;Yoo, Eunae;Hyun, Do Yoon;Chae, Byungsoo
    • Korean Journal of Breeding Science
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    • v.51 no.4
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    • pp.298-317
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    • 2019
  • A statistical analysis of 9,771 non-glutinous rice in breeding line germplasm collected from Korea (2,836), China (2,136), Japan (1,219), and the Philippines (1,213) was conducted using normal distribution, variability index value (VIV), analysis of variation (ANOVA) and Ducan's multiple range test (DMRT) based on the data obtained from NIRS analysis. According to the normal distribution, the average protein content was 7.9%, and non-glutinous rice ranging over 10% amylose had 23.6% average content. Most resources were between 5.3 and 10.5% in protein content, and 15.7 and 31.5% in amylose content. The VIV was 0.54 for protein, and 0.83 for amylose. The average amylose content was 25.18%, 24.54%, 22.08%, and 21.47% in Filipino, Chinese, Korean, and Japanese resources, respectively, wheereas the average protein content was found to be 8.19%, 7.79%, 7.58%, and 7.42% in Filipino, Chinese, Korean, and Japanese resources, respectively. The ANOVA of amylose and protein content showed significant differences at the level of 0.01. The F-test value was 412.2 for amylose content, and 108.4 for protein when compared with the critical value of 3.78. The DMRT of amylose and protein content showed significant differences (p<0.01) among resources from different countries. The Filipino resources had the highest level of amylose and protein content, whereas; the lowest level of amylose and protein content were found in Japanese when compared with resources of other origins. These results are recommended as helpful materials in the field of breeding.