• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.461-470
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• 2019

This study was carried out to quantify the drought stress in grafted watermelon seedlings non-destructively by using chlorophyll fluorescence (CF) imaging technique rather than the visual judgment. Six-day old watermelon seedlings were grown under uniform irrigation for 3 days, and then given drought stress. Afterward, the sensor for the measurement of water content in plug tray cell unit was used to classify the drought-stress level into nine groups from D1 (53.0%, sufficient moisture state) to D9 (15.7%, extremely dry stress), and the 16 CF parameters were measured. In addition, re-irrigation was performed on the drought stressed seedlings(D5 - D9) to determine the growth and photosynthesis recovery level, which was not confirmed by visual judgment. The kinetic curve patterns of CF in three different drought stressed seedling groups were found to be different for the early detection of drought stress. All the 16 CF parameters decreased continuously with exposure to drought stress and drastically decreased from D5 (32.1%) where the visual judgment was possible. The fluorescence decline ratio (Rfd_Lss) started to decrease from the initial drought stress level (D5 - D6), and the Maximum PSII quantum yield (Fv/Fm) was significantly decreased in the later extreme drought stress range (D7 - D9) by re-irrigation recovery test. Thus, Rfd_Lss and Fv/Fm parameters were finally selected as potent indicators of growth and photosynthesis recovery in the initial and later stages of drought stress. Also, to the differences in the numerical values of the individual chlorophyll fluorescence parameters, the drought stress level was intuitively confirmed through the image. These results indicate that Rfd and Fv/Fm can be considered as potential CF parameters for the detection of low and extremely high drought stress, respectively. Furthermore, Fv/Fm can be considered as the best CF parameters for recovery at re-irrigation.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.804-811
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• 2010

The lower portion of sloping paddy fields normally contains excessive moisture and the higher water table caused by the inflow of ground water from the upper part of the field resulting in non-uniform water content distribution. Four drainage methods namely Open Ditch, Vinyl Barrier, Pipe Drainage and Tube Bundle for multiple land use were installed within 1-m position from the lower edge of the upper embankment of sloping alluvial paddy fields. Knowledge of the spatial variability of soil water properties is of primary importance for management of agricultural lands. This study was conducted to evaluate the effect of drainage in the soil on spatial variability of soil water content using the geostatistical analysis. The soil water content was collected by a TDR (Time Domain Reflectometry) sensor after the installation of subsurface drainage on regular square grid of 80 m at 20 m paddy field located at Oesan-ri, Buk-myeon, Changwon-si in alluvial slopping paddy fields ($35^{\circ}22^{\prime}$ N, $128^{\circ}35^{\prime}$). In order to obtain the most accurate field information, the sampling grid was divided 3 m by 3 m unit mesh by four drainage types. The results showed that spatial variance of soil water content by subsurface drainage was reduced, though yield of soybean showed the same trends. Value of "sill" of soil water content with semivariogram was 9.7 in Pipe Drainage, 86.2 in Open Ditch, and 66.8 in Vinyl Barrier and 15.7 in Tube Bundle.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1859-1867
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• 2021

This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM₁₀ concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na⁺, Mg²⁺, K⁺, Ca²⁺, and NH₄⁺), and anions(Cl^-, NO₃^-, and SO₄^2-). The concentration of PM₁₀ in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM₁₀ in the atmosphere and rainwater quality. In spring, the daily average concentration of PM₁₀ (34.11 ㎍/m³) and PM_2.5 (19.23 ㎍/m³) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM₁₀ in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM₁₀ (27.79 ㎍/m³) and PM_2.5 (17.41 ㎍/m³) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM₁₀ in the atmosphere and rainwater quality in summer.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.265-271
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• 2021

The pattern of the tree's internal swelling depends on many causes. Since it is difficult to detect these various causes of swelling with a general method, if the state of swelling for a long time cannot be confirmed, serious damage to the trees may occur due to enlargement of the swelling area. In the method of acquiring a tree tomography image, an impulse passing through the tree is generated by tapping the sensor with a rubber mallet, and the moving speed is recorded. In this paper, to measure cracks, cavities, and swelling due to physical damage, we developed a 3D viewer that can know the internal state of a tree using a tree cross-section image acquired from Arbotom to determine the degree of swelling inside the tree. Based on this, we tried to present data that can be referred to when surgical operation of trees is required. In order to acquire a tomographic image of a tree, 6 sensors were attached to the three Yangpala and Maple trees, and a 1 m-long tree was measured using the Arbotom program, and a 3D image was implemented through the 3D Viewer created using MATLAB. In addition to simply acquiring images, the cross-sectional length and volume of the tree were measured. In the actually produced 3D Viewer, the length of the part where the swelling of the maple tree occurred was 33.12 cm, and the swelling of the yangpala tree was measured as 21.41 cm. The volume of the maple tree was measured to be 78.832 ㎤. As a result of comparing the cross-sectional image of the Arbotom and the 3D image, the same result as the real aspect of the tree was obtained, so it can be judged that the reliability of the manufactured software is also secured, and data to be applied to the surgical tree operation through the created Viewer is provided. It is believed that the damage will be minimized.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

• Korean Journal of Breeding Science
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• v.43 no.4
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• pp.233-240
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• 2011

Food security has been a main global issue due to climate changes and growing world population expected to 9 billion by 2050. While biodiversity is becoming more highlight, breeders are confronting shortage of various genetic materials needed for new variety to tackle food shortage challenge. Though biotechnology is still under debate on potential risk to human and environment, it is considered as one of alternative tools to address food supply issue for its potential to create a number of variations in genetic resource. The new technology, phenomics, is developing to improve efficiency of crop improvement. Phenomics is concerned with the measurement of phenomes which are the physical, morphological, physiological and/or biochemical traits of organisms as they change in response to genetic mutation and environmental influences. It can be served to provide better understanding of phenotypes at whole plant. For last decades, high-throughput screening (HTS) systems have been developed to measure phenomes, rapidly and quantitatively. Imaging technology such as thermal and chlorophyll fluorescence imaging systems is an area of HTS which has been used in agriculture. In this article, we review the current statues of high-throughput screening system in phenomics and its application for crop improvement.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1041-1053
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• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.289-298
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• 2019

In this present study, the effects of Signal to Noise Ratio (SNR), Full Width Half Maximum (FWHM), Aerosol Optical Depth (AOD), $O_3$ Vertical Column Density ($O_3$ VCD), and Solar Zenith Angle (SZA) on the accuracy of sulfur dioxide Vertical Column Density ($SO_2$ VCD) retrieval have been quantified using the Differential Optical Absorption Spectroscopy (DOAS) method with the ground-based direct-sun synthetic radiances. The synthetic radiances produced based on the Beer-Lambert-Bouguer law without consideration of the diffuse effect. In the SNR condition of 650 (1300) with FWHM = 0.6 nm, AOD = 0.2, $O_3$ VCD = 300 DU, and $SZA=30^{\circ}$, the Absolute Percentage Difference (APD) between the true $SO_2$ VCD values and those retrieved ranges from 80% (28%) to 16% (5%) for the $SO_2$ VCD of $8.1{\times}10^{15}$ and $2.7{\times}10^{16}molecules\;cm^{-2}$, respectively. For an FWHM of 0.2 nm (1.0 nm) with the $SO_2$ VCD values equal to or greater than $2.7{\times}10^{16}molecules\;cm^{-2}$, the APD ranges from 6.4% (29%) to 6.2% (10%). Additionally, when FWHM, SZA, AOD, and $O_3$ VCD values increase, APDs tend to be large. On the other hand, SNR values increase, APDs are found to decrease. Eventually, it is revealed that the effects of FWHM and SZA on $SO_2$ VCD retrieval accuracy are larger than those of $O_3$ VCD and AOD. The SZA effects on the reduction of $SO_2$ VCD retrieval accuracy is found to be dominant over the that of FWHM for the condition of $SO_2$ VCD larger than $2.7{\times}10^{16}molecules\;cm^{-2}$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.40-49
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• 2019

Coarse woody debris (CWD), which is a component of the forest ecosystem, plays a major role in forest energy flow and nutrient cycling. In particular, CWD isolates carbon for a long time and is important in terms of slowing the rate of carbon released from the forest to the atmosphere. Therefore, this study measured the physiochemical characteristics and respiration rate ($R_{CWD}$) of CWD for Larix kaempferi and Pinus rigida in temperate forests in central Korea. In summer 2018, CWD samples from decay class (DC) I to IV were collected in the 14 forest stands. $R_{CWD}$ and physiochemical characteristics were measured using a closed chamber with a portable carbon dioxide sensor in the laboratory. In both species, as CWD decomposition progressed, the density ($D_{CWD}$) of the CWD decreased while the water content ($WC_{CWD}$) increased. Furthermore, the carbon concentrations did not significantly differ by DC, whereas the nitrogen concentration significantly increased and the C/N ratio decreased. The respiration rate of L. kaempferi CWD increased significantly up to DC IV, but for P. rigida it increased to DC II and then unchanged for DC II-IV. Accordingly, except for carbon concentration, all the measured characteristics showed a significant correlation with $R_{CWD}$. Multiple linear regression showed that $WC_{CWD}$ was the most influential factor on $R_{CWD}$. $WC_{CWD}$ affects $R_{CWD}$ by increasing microbial activity and is closely related to complex environmental factors such as temperature and light conditions. Therefore, it is necessary to study their correlation and estimate the time-series pattern of CWD moisture.