• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.576-587
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• 2018

This study has focused on analysis factors affecting safety monitoring system at tailings sites, and the evaluation equipment to monitor the factors. Twenty sites at eighteen mines with unsafe conditions were selected to examine the equipment. There were three main factors influenced safety in the sites including surface erosion, piping, and slope instability. In detail, the surface erosion was divided into three sub-factors (planting, soil-topping layer, and tailings), piping into three sub-factors (liner, rain protection facility and leachate), and slop instability was also divided into three sub-factors (slop, concrete wall, and reinforcing wall). As results of in-field measurement, a CCTV was the most effective facility, and electrical resistivity survey, acoustic sensing, thermal liner sensor, structure inclinometer, rainfall meter, and flowmeter were also highly effective. According to applications of the facilities in the unstable tailings, structural defects were mainly found in the piping, which was the most important monitoring factor for safety management of tailings sites.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.681-692
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• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• Journal of Life Science
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• v.31 no.3
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• pp.280-286
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• 2021

Oryzalin is a herbicide that disrupts the arrangement of microtubules by binding to tubulin, thereby blocking the anisotropic growth of plant cells. Microtubules and microfilaments are cytoskeleton components that have been implicated in plant growth through their influence on the formation of cell walls. Microtubules also play roles in the sedimentation of amyloplasts in the root tip columella cells; this sedimentation is related to gravity sensing and results in downward root growth in the soil for absorption of water and minerals. However, the orientation of microtubules changes depending on the level of ethylene in plant cells. A recent study reported that oryzalin stimulated ethylene production via 1-aminocyclopropane-1-carboxylic acid (ACC) synthase and ACC oxidase and caused a concentration-dependent inhibition of root growth and gravitropic responses. The aim of the present study was to investigate the possibility that oryzalin-induced inhibition might be recovered by the application of inhibitors of ethylene production, such as 10-4 M cobalt ions and 10-8 M aminoethoxyvinylglycine (AVG). The inhibition of root growth and gravitropic response was overcome by 10-20% by an 8 hr treatment with cobalt ions or AVG. These results suggest that ethylene levels could regulate root growth and gravitropic responses in Arabidopsis.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.135-143
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• 2021

Aerospace and geospatial technologies have become more accessible by researchers and agricultural practitioners, and these technologies can play a pivotal role in transforming current pest management practices in agriculture and forestry. During the past 20 years, technologies including satellites, manned and unmanned aircraft, spectral sensors, information systems, and autonomous field equipment, have been used to detect pests and apply control measures site-specifically. Despite the availability of aerospace and geospatial technologies, along with big-data-driven artificial intelligence, applications of such technologies to apple IPM have not been realized yet. Using a case study conducted at the Korea Apple Research Institute, this article discusses the advances and limitations of current aerospace and geospatial technologies that can be used for improving apple IPM.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.105-105
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• 2023

Heavy metals, including lead (Pb) toxicity, are increasing in soil and are considered toxic in small amounts. Pb contamination is mainly caused by industrialization - smelting, mining. Agricultural practices - sewage sludge, pests and urban practices - lead paint. It can seriously damage and threaten crop growth. Pb can adversely affect plant growth and development by affecting the photosystem, cell membrane integrity, and excessive production of reactive oxygen species (ROS) such as hydrogen peroxide (H₂O₂)andsuperoxide(O₂.-). NO is produced via enzymatic and non-enzymatic antioxidants to scavenge ROS and lipid peroxidation substrates in terms of protecting cells from oxidative damage. Thus, NO improves ion homeostasis and confers resistance to metal stress. Our results here suggest that exogenous NO may aid in better growth under lead stress. These enhancements may be aided by NO's ability in sensing, signaling and stress tolerance in plants under heavy metal stress in combination with lead stress. Our results show that GSNO has a positive effect on soybean seedling growth in response to axillary pressure and that NO supplementation helps to reduce chlorophyll maturation and relative water content in leaves and roots following strong burst under lead stress. GSNO supplementation (200 µM and 100 µM) reduced compaction and approximated oxidative damage of MDA, proline and H₂O₂. Under plant tension, a distorted appearance was found in the relief of oxidative damage by ROS scavenging by GSNO application. In summary, modulation of these NO, PCS and prolongation of metal past reversing GSNO application confirms the detoxification of ROS induced by toxic metal rates in soybean. In summary, these NO, PCS and metal traditionally sustained rates of reverse GSNO application confirm the detoxification of ROS induced by toxic metal rates in soybean.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.954-961
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• 2010

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for quantifying yield, biomass, and nitrogen (N) stress during growing season. This study was conducted to assess biomass and nitrogen (N) status of paddy rice (Oryza sativa L.) plants under N stress using passive and active ground-based remote sensors. Nitrogen application rates were 0, 70, 100, and 130 kg N $ha^{-1}$. At each growth stage, reflectance indices measured with active sensor showed higher correlation with DW, N uptake and N concentration than those with the passive sensor. NIR/Red and NIR/Amber indices measured with Crop Circle active sensors generally had a better correlation with dry weight (DW), N uptake and N content than vegetation indices from Crop Circle passive sensor and NDVIs from active sensors. Especially NIR/Red and NIR/amber ratios at the panicle initiation stage were most closely correlated with DW, N content, and N uptake. Rice grain yield, DW, N content and N uptake at harvest were highly positively correlated with canopy reflectance indices measured with active sensors at all sampling dates. N application rate explains about 91~92% of the variability in the SI calculated from NIR/Red or NIR/Amber indices measured with Crop Circle active sensors on 12 July. Therefore, the in-season sufficiency index (SI) by NIR/Red or NIR/Amber index from Crop Circle active sensors can be used for determination of N application rate.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.6
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• pp.435-441
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• 2007

Ground-based optical sensing over the crop canopy provides information on the mass of plant body which reflects the light, as well as crop nitrogen content which is closely related to the greenness of plant leaves. This method has the merits of being non-destructive real-time based, and thus can be conveniently used for decision making on application of nitrogen fertilizers for crops standing in fields. In the present study relationships among leaf nitrogen content of rice canopy, crop growth status, and Normalized Difference Vegetation Index (NDVI) values were investigated. 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 NDVI($({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$) were measured by using two different active sensors (Greenseeker, NTech Inc. USA). The study was conducted in the years 2005-06 during the rice growing season at the experimental plots of National Institute of Agricultural Science and Technology located at Suwon, Korea. The experiments carried out with randomized complete block design with the application of four levels of nitrogen fertilizers (0, 70, 100, 130kg N/ha) and same amount of phosphorous and potassium content of the fertilizers. gNDVI and rNDVI increased as growth advanced and reached to maximum values at around early August, G(NDVI) were a decrease in values of observed with the crop maturation. gNDVI values and leaf nitrogen content were highly correlated at early July in 2005 and 2006. On the basis of this finding we attempted to estimate the leaf N contents using gNDVI data obtained in 2005 and 2006. The determination coefficients of the linear model by gNDVI in the years 2005 and 2006 were 0.88 and 0.94, respectively. The measured and estimated leaf N contents using gNDVI values showed good agreement ($R^2=0.86^{***}$). Results from this study show that gNDVI values represent a significant positive correlation with leaf N contents and can be used to estimate leaf N before the panicle formation stage. gNDVI appeared to be a very effective parameter to estimate leaf N content the rice canopy.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.158-167
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• 2006

The object of this study is to detect of land-cover change in western DMZ and vicinity. This was performed as a basic study to construct a decision support system for the conservation or a sustainable development of the DMZ and Vicinity near future. DMZ is an is 4km wide and 250km long and it's one of the most highly fortified boundaries in the world and also a unique thin green line. Environmentalists want to declare the DMZ as a natural reserve and a biodiversity zone, but nowadays through the strengthening of the inter-Korean economic cooperation, some developers are trying to construct a new-town or an industrial complex inside of the DMZ. This study investigates the current environmental conditions, especially deforestation of the western DMZ adopting remote sensing and GIS techniques. The Land-covers were identified through the linear spectvral mixture analysis(LSMA) which was used to handle the spectral mixture problem of low spatial resolution imagery of Landsat TM and ETM+ imagery. To analyze quantitative and spatial change of vegetation-cover in western DMZ, GIS overlay method was used. In LSMA, to develop high-quality fraction images, three endmembers of green vegetation(GV), soil, water were driven from pure features in the imagery. Through 15 years, from 1987 to 2002, forest of western DMZ and vicinity was devastated and changed to urban, farmland or barren land. Northern part of western DMZ and vicinity was more deforested than that of southern part. ($52.37km^2$ of North Korean forest and $39.04km^2$ of South Korean were change to other land-covers.) In case of North Korean part, forest changed to barren land and farmland and in South Korean part, forest changed to farmland and urban area. Especially, In North Korean part of DMZ and vicinity, $56.15km^2$ of farmland changed to barren land through 15 years, which showed the failure of the 'Darakbat' (terrace filed) project which is one of food increase projects in North Korea.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.105-123
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• 2018

Currently, satellite images act as essential and important data in water resources, environment, and ecology as well as information of geographic information system. In this paper, we will investigate basic characteristics of satellite images, especially application examples in water resources. In recent years, researches on spatial and temporal characteristics of large-scale regions utilizing the advantages of satellite imagery have been actively conducted for fundamental hydrological components such as evapotranspiration, soil moisture and natural disasters such as drought, flood, and heavy snow. Furthermore, it is possible to analyze temporal and spatial characteristics such as vegetation characteristics, plant production, net primary production, turbidity of water bodies, chlorophyll concentration, and water quality by using various image information utilizing various sensor information of satellites. Korea is planning to launch a satellite for water resources and environment in the near future, so various researches are expected to be activated on this field.