• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.191-201
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• 2021

Rivers have been damaged due to rapid urbanization, and river management has been carried out focusing on flow and flood control functions. Recently, interest in river restoration, emphasizing the environmental aspects of rivers, is increasing, but the beginning of river restoration requires an appropriate evaluation of the environmental flow required for the ecosystem. This study analyzed the effects on the habitat of the river ecosystem by estimating the changes in flow regime and environmental flow following the construction of the Buhang dam in Gamcheon, the first tributary of the Nakdong River. To evaluate the environmental flow, the dominant species of Gamcheon, Zacco Platypus, and the protected species Squalidus gracilis majime, and riparian vegetation were selected, and the environmental flow was calculated using the HEC-EFM (Ecosystem Function Model). The evaluated environmental flow was linked with hydraulic analysis and GIS platform, and habitat area change and habitat connectivity analysis before and after dam construction were performed by spatial habitat analysis in the river. Based on the results of this study, it can be used as a river restoration project and a dam operation plan considering the river environment through the calculation of environmental flow and habitat connectivity analysis to improve the habitat of the river ecosystem.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.181-190
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• 2021

In this study, a large-scale levee breach experiment from lateral overflow was conducted to verify the effect of the new reinforcement method applied to the levee's surface. The new method could prevent levee failure and minimize damage caused by overflow in rivers. The levee was designed at the height of 2.5 m, a length of 12 m, and a slope of 1:2. A new material mixed with biopolymer powder, water, weathered granite, and loess in an appropriate ratio was sprayed on the levee body's surface at a thickness of about 5 cm, and vegetation recruitment was also monitored. At the Andong River Experiment Center, a flow (4 ㎥/s) was introduced from the upstream of the A3 channel to induce the lateral overflow. The change of lateral overflow was measured using an acoustic doppler current profiler in the upstream and downstream. Additionally, cameras and drones were used to analyze the process of the levee breach. Also, a new method using 3D point cloud for calculating the surface loss rate of the levee over time was suggested to evaluate the performance of the levee reinforcement method. It was compared to existing method based on image analysis and the result was reasonable. The proposed 3D point cloud methodology could be a solution for evaluating the performance of levee reinforcement methods.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.35-43
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• 2021

The application of nature-based solutions, such as low impact development (LID) techniques and green infrastructures, for stormwater management continue to increase in urban areas. Plants are usually utilized in LID facilities to improve their pollutant removal efficiency through phytoremediation. Plants can also reduce maintenance costs and frequency by means of reducing the accumulation of pollutants inside the facility. Plants have long been used in different LID facilities; however, proper plant-selection should be considered since different species tend to exhibit varying pollutant uptake capabilities. This study was conducted to investigate the pollutant uptake capabilities of plants by comparing the dry matter and nutrient contents of different plant species in roadsides, LID facilities, and landscape areas. The dry matter content of the seven herbaceous plants, shrubs, and arboreal trees ranged from 60% to 90%. In terms of nutrient content, the total nitrogen (TN) concentration in the tissues of herbaceous plants continued to increase until the summer season, but gradually decreased in the succeeding periods. TN concentrations in shrubs and trees were observed to be high from early spring up to the late summer seasons. All plant samples collected from the LID facility exhibited high TP content, indicating that the vegetative components of LID systems are efficient in removing phosphorus. Overall, the nutrient content of different plant species was found to be highly influenced by the urban environment which affected the stormwater runoff quality. The results of this study can be beneficial for establishing plant selection criteria for LID facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.82-88
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• 2021

Sun-induced fluorescence (SIF) retrieval using remote sensing technique has been used in an effort to understand the photosynthetic efficiency and stress condition of vegetation. Although optical devices and SIF retrieval methodologies were established in order to retrieve SIF, the SIF measurements are domestically sparse. SIF data of paddy rice w as measured in Naju, South Korea from June 10, 2020 to October 5, 2020. The SIFs based red (O2A) and far-red (O2B) w ere retrieved using a spectral fitting method and an improved Fraunhofer line depth, and photosynthetically active radiation was also produced. In addition, the SIF data was filtered considering solar zenith angle, saturation conditions, the rapid and sudden change of solar irradiance, and sun glint. The provided SIF data can help to understand a SIF product and the filtering method of SIF data can contribute to producing high-quality SIF data.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.699-717
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• 2021

South Korea is pushing for the advancement of crop production technology to achieve food self-sufficiency and meet the demand for safe food. A medium-sized satellite for agriculture is being launched in 2023 with the aim of collecting and providing information on agriculture, not only in Korea but also in neighboring countries. The satellite is to be equipped with various sensors, though reference data for ground information are lacking. Hyperspectral remote sensing combined with 1st derivative is an efficient tool for the identification of agricultural crops. In our study, we develop a system for hyperspectral analysis of the ground-based reflectance spectrum, which is monitored seven times during the cultivation period of three soybean crops using a PSR-2500 hyperspectral sensor. In the reflection spectrum of soybean canopy, wavelength variations correspond with stages of soybean growths. The spectral reflection characteristics of soybeans can be divided according to growth into the vegetative (V)stage and the reproductive (R)stage. As a result of the first derivative analysis of the spectral reflection characteristics, it is possible to identify the characteristics of each wavelength band. Using our developed monitoring system, we observed that the near-infrared (NIR) variation was largest during the vegetative (V1-V3) stage, followed by a similar variation pattern in the order of red-edge and visible. In the reproductive stage (R1-R8), the effect of the shape and color of the soybean leaf was reflected, and the pattern is different from that in the vegetative (V) stage. At the R1 to R6 stages, the variation in NIR was the largest, and red-edge and green showed similar variation patterns, but red showed little change. In particular, the reflectance characteristics of the R1 stage provides information that could help us distinguish between the three varieties of soybean that were studied. In the R7-R8 stage, close to the harvest period, the red-edge and NIR variation patterns and the visible variation patterns changed. These results are interpreted as a result of the large effects of pigments such as chlorophyll for each of the three soybean varieties, as well as from the formation and color of the leaf and stem. The results obtained in this study provide useful information that helps us to determine the wavelength width and range of the optimal band for monitoring and acquiring vegetation information on crops using satellites and unmanned aerial vehicles (UAVs)

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.13-26
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• 2021

This study was conducted to identify various types of activities of payment contract for ecosystem services. As supporting services, 12 types of activities were derived: fallow, eco-friendly crop cultivation, shelter creation management, etc. As regulating services, 5 types of activities were derived: stream environment purification, creation and management of riparian vegetation, creation and management of forests for responding to climate change, etc. As cultural services, five types of activities were derived: creation and management of landscape forests, creation and management of ecological trails, managing ecosystem conservation, etc.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1357-1369
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• 2022

Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.1-18
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• 2022

Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.132-144
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• 2023

The use of constructed wetlands (CWs) to sequester carbon has been a topic of interest in recent studies. However, CWs have been found to be both carbon sinks and carbon sources, thus leaving uncertainties about their role in carbon neutrality initiatives. To address the uncertainties, a bibliometric and comprehensive review on carbon sequestration in CWs was conducted. Upon forming various scripts using CorText Manager, it was found that a majority of the studies focused on the effectiveness of CWs to remove nutrients, particularly nitrogen. The results of the comprehensive review revealed that high carbon concentrations and carbon sequestration rates in CW soils are dependent on the vegetation types used, the ages of the CWs, and the organic content of inflow water entering the CWs. The Typha genus was the most dominant plant genus used in the CWs from the reviewed studies and was associated with the highest carbon sequestration rates documented in this review study. Furthermore, the relatively high ability of tree species, in comparison to emergent plants, to sequester carbon was observed. Therefore, incorporating tree species into CW designs and adding them to emergent plants is seen as a potential breakthrough approach to improve the ability of CWs to sequester carbon and ultimately contribute to mitigating climate change.