• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.313-318
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• 2016

Purpose: This study measured and analyzed the PTO (power take off) torque of a transplanter according to the planting conditions during field operation. Methods: A torque measurement system was constructed with torque sensors to measure the torque of a PTO shaft, a measurement device to acquire sensor signals, and a power controller to provide power for a laptop computer. The field operation was conducted at four planting distances (26, 35, 43, and 80 cm) and two planting depths using the transplanter on a field with similar soil conditions. One-way ANOVA with planting distance and Duncan's multiple range test at a significance level of 0.05 were used to analyze the PTO torque. The torque ratio was calculated based on the minimum torque using the average PTO torque measured under each planting condition. Results: The average torques on the PTO shaft for planting distances of 26, 35, 43, and 80 cm at a low planting depth were 11.05, 9.07, 7.04, and 3.75 Nm, respectively; the same for planting distances of 26, 35, 43, and 80 cm at a middle planting depth were 12.20, 9.86, 7.94, and 4.32 Nm, respectively. When the planting distance decreased by 43, 35, and 26 cm, the torque ratio at a low planting depth increased by 88, 142, and 195%, respectively. When the planting distance decreased by 43, 35, and 26 cm, the torque ratio at the middle planting depth increased by 84, 128, and 182%, respectively. Conclusions: PTO torque fluctuated by planting distance and depth. Moreover, the PTO torque increased for short planting distances. Therefore, farmers should determine the planting conditions of the transplanter by considering the load and durability of the machine. The results of this study provide useful information pertaining to the optimum PTO design of the transplanter considering the field load.

• Ecology and Resilient Infrastructure
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• v.5 no.4
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• pp.257-263
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• 2018

This study is to develop a GSTM (Green infrastructure Surface Temperature Measurment) equipment for reducing the surface temperature of GI by using LID Method. The tests were conducted including GI products such as Greening block, Pervious Block, Soil Block and so on. The GSTM equipment developed by considering the literature surveys are characterized as follows. The non-contact infrared temperature sensor was used to measure the surface temperature, and it was improved to measure the overall average temperature including the center and the corner temperature of the specimen. The developed GSTM equipment was used to compare performance of asphalt and GI products. As a result, the Greening Block show a high difference of $18.4^{\circ}C$ and it contributes to the decrease of surface temperature.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.169-169
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• 2022

Over the past 100 years, the global average temperature has risen by 0.75 ℃. The Korean Peninsula has risen by 1.8 ℃, more than twice the global average. According to the RCP 8.5 scenario, the CO₂ concentration in 2100 will be 940 ppm, about twice as high as current. The National Institute of Crop Science(NICS) is using the SPAR (Soil-Plant Atmosphere Research) facility that can precisely control the environment, such as temperature, humidity, and CO₂. A Python-based colony photosynthesis algorithm has been developed, and the carbon and nitrogen absorption rate of rice is evaluated by setting climate change conditions. In this experiment, Oryza Sativa cv. Shindongjin were planted at the SPAR facility on June 10 and cultivated according to the standard cultivation method. The temperature and CO₂ settings are high temperature and high CO₂ (current temperature+4.7℃ temperature+4.7℃·CO₂ 800ppm), high temperature single condition (current temperature+4.7℃·CO₂ 400ppm) according to the RCP8.5 scenario, Current climate is set as (current temperature·CO₂400ppm). For colony photosynthesis measurement, a LI-820 CO₂ sensor was installed in each chamber for setting the CO₂ concentration and for measuring photosynthesis, respectively. The colony photosynthetic rate in the booting stage was greatest in a high temperature and CO₂ environment, and the higher the nitrogen fertilization level, the higher the colony photosynthetic rate tends to be. The amount of photosynthesis tended to decrease under high temperature. In the high temperature and high CO₂ environment, seed yields, the number of an ear, and 1000 seed weights tended to decrease compared to the current climate. The number of an ear also decreased under the high temperature. But yield tended to increase a little bit under the high temperature and high CO₂ condition than under the high temperature. In addition, In addition to this study, it seems necessary to comprehensively consider the relationship between colony photosynthetic ability, metabolite reaction, and rice yield according to climate change.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.469-477
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• 2020

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s^-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.344-352
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• 2019

Drought stress caused by global climate change is a serious problem for rice cultivation. Increasingly frequent abnormal weather occurrences could include severe drought, which could cause water stress to rice during the seedling stage. This experiment was conducted to clarify the effects of drought during the seedling period on yield and quality of rice. Drought conditions were created in a rain shelter house facility. The drought treatment was conducted at 3, 10, and 20 days after transplanting. Soil water content was measured by a soil moisture sensor during the whole growth stage. In this study, we have chosen 3 rice cultivars which are widely cultivated in Korea: 'Haedamssal' (Early maturing), 'Samkwang' (Medium maturing), and 'Saenuri' (Mid-late maturing). The decrease in yield due to drought treatment was most severe 3 days after transplanting because of the decrease in the number of effective tillers. The decrease in grain quality due to drought treatment was also most severe 3 days after transplanting because of the increased protein content and hardness of the grains. The cultivar 'Haedamssal' was the most severely damaged by water stress, resulting in about a 30% yield loss. Drought conditions diminished the early vigorous growth period and days to heading in early-maturing cultivars. The results show that drought stress affects yield components immediately after transplanting, which is a decisive factor in reducing yield and grain quality. This study can be used as basic data to calculate damage compensation for drought damage on actual rice farms.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.1-8
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• 2010

The purpose of the study was to evaluate the influence of landscaping pavements on WBGT(Wet-Bulb Globe Temperature) of outdoor spaces that lack ventilation and shade at summer midday. The relative humidity(RH), dry-bulb temperature(DT) and globe temperature(GT) were recorded every minute from June to October 2009 at a height of 1.2m above ten experimental beds with different pavements, by a measuring system consisting of an electric humidity sensor(GHM-15), resistance temperature detector(RTD, Pt-100), standard black globe(${\phi} 150mm$) and data acquisition systems(National Instrument's Labview and Compact FieldPoint). Additionally, the surface dry-bulb temperatures also were recorded and compared. The area of each experimental bed was 1.5m(W)${\times}$2.0m(L) and ten different kinds of pavement were used including grass, grass+cubic stone, grass+porous brick, brick, stone panels, cubic stone, interlocking blocks, clay brick, naked soil, gravel and concrete. To prevent interference from ventilation, a 1.5m height cubic steel frame was established around each bed and each vertical side of the frame was covered with transparent polyethylene film. Based on the records of the hottest period from noon to 3 PM on 26 days with a peak dry-bulb temperature over $30^{\circ}C$ at natural condition, the wet-bulb temperature(WT) and WBGT were calculated and compared. The major findings were as follows: 1. The average surface DT was $40.1^{\circ}C$, which is $9^{\circ}C$ higher than that of the natural condition. The surface DT of the pavements with grass were higher than those of concrete and interlocking block. The peak DT of the surface almost every pavement rose to above $50^{\circ}C$ during the hottest time. 2. The averages of DT, WT and GT were $40.1^{\circ}C$, $27.5^{\circ}C$ and $49.1^{\circ}C$, and the peak values rose to $48.1^{\circ}C$, $45.8^{\circ}C$ and $59.5^{\circ}C$, respectively. In spite of slight differences that resulted according to pavements, no coherent differentiating factor could be found. 3. The average WBGT of grass was the highest at $34.3^{\circ}C$ while the others were similar in the range of around $33{\pm}1^{\circ}C$. Meanwhile, the peak WBGT was highest with stone panel at $47.9^{\circ}C$. Though there were some differences according to pavements, and while grass seemed to be worst in terms of WBGT, it seems difficult to say ablolutely that grass was the worst because the measurement was conducted without ventilation and shade during summer daytime hours only, which had temperatures that rose to a dangerous degree(above $45^{\circ}C$ WBGT), withering the grass during the hottest period. The average WBGT resulted also showed that the thermal environment of the pavement without ventilation and shade were at an intolerable level for humans regardless of the pavement type. In summary, the results of this study show that ventilation and shade are more important factor than pavement type in terms of outdoor thermal comfort in summer daylight hours.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.69-78
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• 2011

Rice is one of the world's staple foods. Paddy rice fields have unique biophysical characteristics that the rice is grown on flooded soils unlike other crops. Information on the spatial distribution of paddy fields and the timing of irrigation are of importance to determine hydrological balance and efficiency of water resource management. In this paper, we detected the timing of irrigation and spatial distribution of paddy fields using the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Aqua satellite. The timing of irrigation was detected by the combined use of MODIS-based vegetation index and Land Surface Water Index (LSWI). The detected timing of irrigation showed good agreement with field observations from two flux sites in Korea and Japan. Based on the irrigation detection, a land cover map of paddy fields was generated with subsidiary information on seasonal patterns of MODIS enhanced vegetation index (EVI). When the MODISbased paddy field map was compared with a land cover map from the Ministry of Environment, Korea, it overestimated the regions with large paddies but underestimated those with small and fragmented paddies. Potential reasons for such spatial discrepancies may be attributed to coarse pixel resolution (500 m) of MODIS images, uncertainty in parameterization of threshold values for discarding forest and water pixels, and the application of LSWI threshold value developed for paddy fields in China. Nevertheless, this study showed that an improved utilization of seasonal patterns of MODIS vegetation and water-related indices could be applied in water resource management and enhanced estimation of evapotranspiration from paddy fields.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.