• The korean journal of orthodontics
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• v.36 no.5
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• pp.324-330
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• 2006

Objective: The purposes of this study were to evaluate the differences between sand blasted, large grit and acid-etched (SLA) treated mini-implants and smooth surface orthodontic mini-implants in relation to the removal torque as well as the histologic analysis. Methods: Custom-made, screw-shaped, titanium implants with a length of 9.5 mm and an outer diameter of 1.8 mm were divided into 2 groups; the SLA group (20 SLA treated orthodontic mini-implants) and the smooth surface group (20 smooth surface mini-implants), and placed In the tibia metaphysis of 10 rabbits. Each rabbit had 4 mini-implants placed, 2 in each tibia. The right tibia were implanted with the SLA group mini-implants and the left tibia had the smooth group mini-implants placed. Each mini-implant group were immediately applied with a continuous traction force of 150 g using a Ni-Ti coil spring. The rabbits were sacrificed 6 weeks post-surgically. Subsequently, the legs were stabilized, the Ni-Ti coil springs were removed and the mini-implants were removed under reverse torque rotation with a digital torque gauge. Results: 6 weeks after placement, the SIA group presented a higher mean removal torque value (8.29 Ncm) than the smooth group (3.34 Ncm) and histologic analysis revealed a higher new bone formation aspect along the screw in the SLA group. Conclusion: Results of this study indicates that SLA treated mini-implants may endure higher orthodontic forces without loosening.

• Environmental and Resource Economics Review
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• v.14 no.1
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• pp.101-134
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• 2005

Economic feasibility analysis for the public projects such as sewer improvement project differs from the one for the project by profit organization in that the former has to take into consideration the public benefit that cannot be priced in the market. This study presents a model case study for the economic feasibility analysis for the sewer improvement project by the City of Gumi, Korea. The project is planned for the period of 2003~2021. It utilized Contingent Valuation Method(CVM) to assess the public benefits such as improvement of environmental quality and quality of life that can not be priced in the market. WTP(Willing-to-pay) of a household of the Gumi was estimated at 2,865 Korean Won on average. The result of an economic feasibility test including the estimated WTP indicates that B/C ratio of the project turned out to be 0.97, slightly less than 1. This study is the first application of WTP estimated by CVM to the economic feasibility analysis of public project in Korea. It is expected to contribute to the decision makings in the public policy domain as well as academic development.

• Journal of Engineering Education Research
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• v.13 no.6
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• pp.33-48
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• 2010

This paper is aimed to design for qualification structure and criteria for preparation of qualification test of the environmental impact assessor qualifications. In this study, a DACUM(Development A curriculum) method job analysis to extract contents such as task range, eligibility, examination standards, selection criteria of examination questions, examination methods, etc was done by an job analysis committee composed of 9 specialists in the industry and academia. In the first place, this report presents job analysis models by procedures for developing selection criteria of examination questions of the environmental impact assessor. The first step is preparation for job analysis(data research, interviews and selection of experts), the second step the establishment of job models(first expert council and site study), the third step the drawn-out of knowledge, skills, and tools(the second expert council and site study), the fourth step the selection of courses and an examination subject(the third expert council), the fifth step the establishment of guidelines for making questions(the third site study).

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1951-1963
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• 2021

Remote sensing data using earth observation satellites in agricultural environment monitoring has many advantages over other methods in terms of time, space, and efficiency. Since the sensor mounted on the satellite measures the energy that sunlight is reflected back to the ground, noise is generated in the process of being scattered, absorbed, and reflected by the Earth's atmosphere. Therefore, in order to accurately measure the energy reflected on the ground (radiance), atmospheric correction, which must remove noise caused by the effect of the atmosphere, should be preceded. In this study, atmospheric correction sensitivity analysis, inter-satellite cross-analysis, and comparative analysis with ground observation data were performed to evaluate the application of KOMPSAT-3 satellite's atmospheric correction for agricultural application. As a result, in all cases, the surface reflectance after atmospheric correction showed a higher mutual agreement than the TOA reflectance before atmospheric correction, and it is possible to produce the time series vegetation index of the same standard. However, additional research is needed for quantitative analysis of the sensitivity of atmospheric input parameters and the tilt angle.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.833-845
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• 2021

Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.250-257
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• 2020

It is difficult for farmers to select new crops for cultivation to increase income. So we conducted land suitability assessment of grapes with soil and climate information related to crop growth. At first, land suitabilities for grapes were classified into three categories (most suitable, suitable, low productive & not suitable areas) according to soil and climate conditions, respectively. In details, land suitability with respect to soil was assessed by soil morphological and physical properties including soil texture, drainage class, available soil depth, slope and gravel content, whereas one in accordance with climate was evaluated by average annual temperature, temperature during the growing season, temperature during maturation, the lowest temperature, chilling requirement and precipitation during the growing season. Secondly, we combined both soil and climate classification results using a most-limiting characteristic method. Maps showing the suitable land for grapes cultivation were drawn. The results indicate that the most suitable area of cultivation for grapes in south Korea was 3.43% and suitable (possible) area was 10.61%. This study may help to preserve land and increase the productivity through providing valuable information regarding where more suitable areas for grapes are located.

• Korean Journal of Environmental Agriculture
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• v.39 no.4
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• pp.334-342
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• 2020

BACKGROUND: To quantify carbon exchange at agricultural ecosystems in South Korea, net ecosystem exchange (NEE) at three croplands including a rice paddy, a bean field and an apple orchard was measured on the basis of the eddy covariance technique. METHODS AND RESULTS: NEE of CO2 during the growing season (June to September) averaged over the recent two years (2018-2019) was the highest at rice (-4.49 g C m-2 day-1), followed by the bean (-3.12 g C m-2 day-1) and apple (-0.93 g C m-2 day-1). The diurnal variation of NEE was the highest at the rice, while the seasonal variation of it was the highest at the bean than others. In terms of yearly variation, the rice paddy and the bean field absorbed more CO2 in 2019 compared to 2018, while the apple orchard absorbed less. CONCLUSION: Our results confirmed that these croplands consistently acted as net sinks for CO2 during the growing season because an amount of CO2 uptake from photosynthesis was larger than one of its emissions from respiration. The quantification of net CO2 exchange at agricultural ecosystems may help to better understand the local carbon cycle over various time scales.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.