• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.699-717
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• 2021

South Korea is pushing for the advancement of crop production technology to achieve food self-sufficiency and meet the demand for safe food. A medium-sized satellite for agriculture is being launched in 2023 with the aim of collecting and providing information on agriculture, not only in Korea but also in neighboring countries. The satellite is to be equipped with various sensors, though reference data for ground information are lacking. Hyperspectral remote sensing combined with 1st derivative is an efficient tool for the identification of agricultural crops. In our study, we develop a system for hyperspectral analysis of the ground-based reflectance spectrum, which is monitored seven times during the cultivation period of three soybean crops using a PSR-2500 hyperspectral sensor. In the reflection spectrum of soybean canopy, wavelength variations correspond with stages of soybean growths. The spectral reflection characteristics of soybeans can be divided according to growth into the vegetative (V)stage and the reproductive (R)stage. As a result of the first derivative analysis of the spectral reflection characteristics, it is possible to identify the characteristics of each wavelength band. Using our developed monitoring system, we observed that the near-infrared (NIR) variation was largest during the vegetative (V1-V3) stage, followed by a similar variation pattern in the order of red-edge and visible. In the reproductive stage (R1-R8), the effect of the shape and color of the soybean leaf was reflected, and the pattern is different from that in the vegetative (V) stage. At the R1 to R6 stages, the variation in NIR was the largest, and red-edge and green showed similar variation patterns, but red showed little change. In particular, the reflectance characteristics of the R1 stage provides information that could help us distinguish between the three varieties of soybean that were studied. In the R7-R8 stage, close to the harvest period, the red-edge and NIR variation patterns and the visible variation patterns changed. These results are interpreted as a result of the large effects of pigments such as chlorophyll for each of the three soybean varieties, as well as from the formation and color of the leaf and stem. The results obtained in this study provide useful information that helps us to determine the wavelength width and range of the optimal band for monitoring and acquiring vegetation information on crops using satellites and unmanned aerial vehicles (UAVs)

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1207-1217
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• 2022

Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.485-491
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• 2022

Intravenous injection is the most frequent invasive treatment for inpatients and is widely used for parenteral nutrition administration and blood products, and more than 1 billion procedures are used for peripheral catheter insertion, blood collection, and other IV therapy per year. Intravenous injection is one of the difficult procedures to be performed only by trained nurses with intravenous injection training, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Accordingly, studies on auxiliary equipment capable of visualizing the vein structure of the back of the hand or arm are being published to reduce errors during intravenous injection. This study is a study on the performance difference according to the number of LEDs irradiating the 850nm wavelength band on a vein detector that visualizes the vein during intravenous injection. Four LED PCBs were produced by attaching NIR filters to CCD and CMOS camera lenses irradiated on the skin to acquire images, sharpen the acquired images using image processing algorithms, and project the sharpened images onto the skin. After that, each PCB was attached to the front end of the vein detector to detect the vein image and create a performance comparison questionnaire based on the vein image obtained for performance evaluation. The survey was conducted on 20 nurses working at K Hospital.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.1
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• pp.5-14
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• 2023

In this study, LiDAR-reflective black hollow-structured silica/titania(B-HST) materials are successfully synthesized by employing the NaBH₄ reduction and etching method on silica/titania core/shell(STCS) materials, which also effectively enhance near-infrared(NIR) reflectance. Moreover, core-etched supernatant solutions are collected and recycled for the synthesis of extracted silica(e-SiO₂) process, which successfully applies as filler materials for semiconductor epoxy molding compound(EMC). In detail, B-HST materials, fabricated by the sequential experimental steps of sol-gel, reduction, and sonication-mediated etching method, manifest blackness(L^*) of 13.2 similar to black paint and excellent NIR reflectance(31.1%). Consequently, B-HST materials are successfully prepared as LiDAR-reflective black materials. Additionally, core-etched supernatant solution with silanol precursors are employed for synthesis of homogeneous silica filler materials via sol-gel method. As-synthesized silica fillers are incorporated with epoxy resin and carbon black for the preparation of semiconductor EMC. Experimentally synthesized EMC exhibits comparable mechanical-chemical properties to commercial EMC. Conclusively, this study successfully proposes designing procedure and practical experimental method for simultaneously synthesizing the NIR-reflective black materials for self-driving vehicles and EMC materials for semiconductors, which are materials suitable for the industrial 4.0 era, and presented their applicability in future industries.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.145-156
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• 2023

In this study, Fourier-transform near-infrared (FT-NIR) spectra of Korean red pine seeds stored at -18℃ and 4℃ for 18 years were analyzed. To develop seed-germination prediction models, the performance of seven machine learning methods, namely XGBoost, Boosted Tree, Bootstrap Forest, Neural Networks, Decision Tree, Support Vector Machine, PLS-DA, were compared. The predictive performance, assessed by accuracy, misclassification, and area under the curve (0.9722, 0.0278, and 0.9735 for XGBoost, and 0.9653, 0.0347, and 0.9647 for Boosted Tree), was better for the XGBoost and decision tree models when compared with other models. The 54 wave-number variables of the two models were of high relative importance in seed-germination prediction and were grouped into six spectral ranges (811~1,088 nm, 1,137~1,273 nm, 1,336~1,453 nm, 1,666~1,671 nm, 1,879~2,045 nm, and 2,058~2,409 nm) for aromatic amino acids, cellulose, lignin, starch, fatty acids, and moisture, respectively. Use of the NIR spectral data and two machine learning models developed in this study gave >96% accuracy for the prediction of pine-seed germination after long-term storage, indicating this approach could be useful for non-destructive viability testing of stored seed genetic resources.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.4
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• pp.229-236
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• 2023

Background: Local anesthesia has been reliably used to control pain during dental procedures and is important in pediatric dentistry. However, children occasionally complain of prolonged numbness after dental treatment, leading to several problems. Studies conducted to reverse the effect of local anesthesia using phentolamine mesylate and photobiomodulation therapy (PBM) are encouraging but limited. PBM is a type of light therapy that utilizes visible and near-infrared non-ionizing electromagnetic spectral light sources. Hence, this study used this modality to compare the reversal of local anesthesia at two different wavelengths. This study compared the effect of PBM at 660 and 810 nm wavelengths on the reversal of soft tissue local anesthesia using a diode LASER in pediatric dentistry. Method: Informed consent and assent were obtained, and the participants were then divided randomly into three groups of 20 children each: control group-without LASER irradiation, LASER irradiation at 660 nm, and LASER irradiation at 810 nm. Sixty children aged 4-8 years with deciduous mandibular molars indicated for pulp therapy were administered an inferior alveolar nerve block. After 45 min of injection, a duration that was similar to the approximate duration of treatment, they were exposed to 660- and 810-nm LASER irradiation according to their groups until reversal of local anesthesia was achieved. The control group did not undergo LASER irradiation. The reversal of the soft tissue local anesthetic effect was evaluated using palpation and pin prick tests every 15 min, and the LASER irradiation cycle continued until reversal of the soft tissue local anesthesia was achieved. Results: A significant reduction of 55.5 min (27.6%) in the mean soft tissue local anesthesia reversal time was observed after the application of 810 nm wavelength PBM and 69 min (34.7%) after 660 nm wavelength LASER irradiation. Conclusion: PBM with a 660 nm wavelength was more effective in reducing the mean soft tissue local anesthesia reversal duration, and thus can be used as a reversal agent for soft tissue local anesthesia in pediatric dentistry.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.523-528
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• 2023

The applicability as a material to improve solar cell performance was reviewed by synthesizing a phosphor that emits red wavelengths by a liquid synthesis method using a metal salt aqueous solution and a polymer medium as a starting material. An aqueous solution was prepared using nitrate of metals such as Ca, Zn, Al, and Eu, and a precursor impregnated with starch, a natural polymer, was sintered to synthesize CaZnAlO:Eu phosphor powder. The surface structure and composition analysis of the synthesized CaZnAlO:Eu phosphor powder were analyzed by scanning electron microscope(SEM) and energy-dispersed X-ray spectroscopy(EDS). The crystal structure of CaZnAlO:Eu phosphor particles was analyzed by an X-ray diffraction analyzer (XRD). As a result of measuring the photoluminescence(PL) characteristics of the phosphor, it was confirmed that a red phosphor with a light emitting wavelength of 650-780nm was successfully synthesized. According to SEM and EDS analysis, the synthesized Ca₁₄Zn₆Al_9.93O₃₅:Eu³⁺_0.07 phosphor powder has a uniform particle size, and Eu ions used as an activator are present. The synthesized CZA:Eu³⁺ phosphor can be used as a material that can increase the light absorption efficiency of the solar cell by converting ultraviolet or visible light down conversion into a wavelength in the near-infrared region.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.135-142
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• 2023

A various technology of remote sensing and image analysis are applied to study landscape changes and their influencing factors in stream corridors. We developed a method to detect landscape changes over time by calculating the optical index using multispectral images taken from satellites at various time points, calculating the threshold to delineate the boundaries of water bodies, and creating binarized maps into land and water areas. This method was applied to the upstream reach of the weirs in the Geumgang River to track changes in the sandbar formed by the opening of the weir gate. First, we collected multispectral images with a resolution of 10 m × 10 m taken from the Sentinel-2 satellite at various times before and after the opening of the dam in the Geumgang River. The normalized difference water index (NDWI) was calculated using the green light and near-infrared bands from the collected images. The Otsu's threshold of NDWI calculated to delineate the boundary of the water body ranged from -0.0573 to 0.1367. The boundary of the water area determined by remote sensing matched the boundary in the actual image. A map binarized into water and land areas was created using NDWI and the Otsu's threshold. According to these results of the developed method, it was estimated that a total of 379.7 ha of new sandbar was formed by opening the three weir floodgates from 2017 to 2021 in the longitudinal range from Baekje Weir to Daecheong Dam on the Geumgang River. The landscape detection method developed in this study is evaluated as a useful method that can obtain objective results with few resources over a wide spatial and temporal range.