• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.285-293
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• 2010

Soil moisture is a key factor to control the exchange of water and energy between the surface and the atmosphere. In recent, many researches for spatial and temporal variability analyses of soil moisture have been conducted. In this study, we analyzed the spatio-temporal variability of soil moisture in Walnut Gulch Experimental Watershed, Arizona, U.S. during the Soil Moisture Experiment 2004 (SMEX04). The spatio-temporal variability analyses were performed to understand sensitivity of five observation sites with precipitation and relationship between mean soil moisture, and its standard deviation and coefficient of variation at the sites, respectively. It was identified that log-normal distribution was superior to replicate soil moisture spatial patterns. In addition, precipitation was identified as a key physical factor to understand spatio-temporal variability of soil moisure based on the temporal stability analysis. Based on current results, higher spatial variability was also observed which was agreed with the results of previous studies. The results from this study should be essential for improvement of the remotely sensed soil moisture retrieval algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.34-44
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• 2024

Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.187-197
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• 2024

In this study, we aimed to identify the factors influencing post-fire mortality in Korean red pine (Pinus densiflora) using Cox's proportional hazards model and analyze the impact of these factors. We monitored the mortality rate of fire-damaged pine trees for seven years after a forest fire. Our survival analysis revealed that the risk of mortality increased with higher values of the delta normalized difference vegetation index (dNDVI), delat normalized burn ratio (dNBR), bark scorch index (BSI), bark scorch height (BSH) and slope. Conversely, the risk of mortality decreased with higher elevation, greater diameter at breast height (DBH), and higher value of delta moisture stress index (dMSI) (p < 0.01). Verification of the proportional hazards assumption for each variable showed that all factors, except slope aspect, were suitable for the model and significantly influenced fire occurrence. Among the variables, BSI caused the greatest change in the survival curves (p < 0.0001). The environmental change factors determined through remote sensing also significantly influenced the survival rates (p < 0.0001). These results will be useful in establishing restoration plans considering the potential mortality risk of Korean red pine after a forest fire.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.263-270
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• 2024

As unmanned aerial vehicles(UAVs) and sensors have been developed in a variety of ways, it has become possible to update information on the ground faster than existing aerial photography or remote sensing. However, acquisition and input of ground control points(GCPs) UAV photogrammetry takes a lot of time, and geometric distortion occurs if measurement and input of GCPs are incorrect. In this study, RGB-based orthophotos were generated to reduce GCPs measurment and input time, and comparison and evaluation were performed by applying feature point algorithms to target orthophotos from various sensors. Four feature point extraction algorithms were applied to the two study sites, and as a result, speeded up robust features(SURF) was the best in terms of the ratio of matching pairs to feature points. When compared overall, the accelerated-KAZE(AKAZE) method extracted the most feature points and matching pairs, and the binary robust invariant scalable keypoints(BRISK) method extracted the fewest feature points and matching pairs. Through these results, it was confirmed that the AKAZE method is superior when performing geometric correction of the objective orthophoto for each sensor.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.233-241
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• 2024

In this study, finite element analyses of coated steel pipes were conducted to research the development of sensing-based monitoring smart pipes. The coated steel pipes underwent a chemical coating pretreatment process that used modified polyethylene on both the inside and outside surfaces. Furthermore, the steel pipes were designed to minimize damage during the expansion process by incorporating connecting parts. To evaluate structural performance under various loads, four loading conditions were established: static structural analysis by earth pressure, fatigue life evaluation by vehicle load, and resistance to water leakage under both tensile and compressive loads. The analysis estimated a higher fatigue life for the developed steel pipe, compared with that of a steel pipe using ready-made epoxy coatings and joints. In addition, an average maximum displacement reduction of 56.1% and a maximum stress reduction of 61.2% were confirmed under identical conditions and diameters, thereby verifying the safety of the connecting parts of the developed coated steel pipe. Furthermore, the results of stress distribution contour analyses revealed superior water leakage resistance at the fastening parts, compared with the centers of the pipes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• 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.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.161-170
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• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.399-408
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• 2021

Natural soil was artificially contaminated with heavy metals (Cd, Pb, and Zn), and the movement of earthworm was characterized in real time using the ViSSET system composed of vibration sensor and the other components. The manifestation mechanism of ecological toxicity of heavy metals was interpreted based on the accumulative frequency of earthworm movement obtained from the real-time monitoring as well as the conventional indices of earthworm behavior, such as the change in body weight before and after tests and biocumulative concentrations of each contaminant. The results showed the difference in the earthworm movement according to the species of heavy metal contaminants. In the case of Cd, the earthworm movement was decreased with increasing its concentration and then tended to be increased. The activity of earthworm was severely increased with increasing Pb concentration, but the movement of earthworm was gradually decreased with increasing Zn concentration. The body weight of earthworm was proved to be greatly decreased in the Zn-contaminated soil, but it was similarly decreased in Cd- and Pb-contaminated soils. The bioaccumulation factor (BAF) was higher in the sequence of Cd > Zn > Pb, and particularly the biocumulative concentration of Pb did not show a clear tendency according to the Pb concentrations in soil. It was speculated that Cd is accumulated as a metallothionein-bound form in the interior of earthworm for a long time. In particular, Cd has a bad influence on the earthworm through the critical effect at its higher concentrations. Pb was likely to reveal its ecotoxicity via skin irritation or injury of sensory organs rather than ingestion pathway. The ecotoxicity of Zn seemed to be manifested by damaging the cell membranes of digestive organs or inordinately activating metabolism. Based on the results of real-time monitoring of earthworm movement, the half maximal effective concentration (EC50) of Pb was estimated to be 751.2 mg/kg, and it was similar to previously-reported ones. The study confirmed that if the conventional indices of earthworm behavior are combined with the results of newly-proposed method, the mechanism of toxicity manifestation of heavy metal contaminants in soils is more clearly interpreted.