The civil engineering materials used to stabilize the slopes of new riverbanks have a great impact on the types and growth of vegetation introduced after the completion of construction procedure. Recently, microbial-derived, ${\beta}$-glucan- and xanthan gum-based biopolymers are attracting attention as an ecofriendly strengthening material of riverbanks that can possibly stimulate plant growth. This study aimed to assess ecological effects of biopolymer application on native plants in Korean riverbanks. In particular, since dominant plant species could shape characteristics of an ecosystem, we examined the effects of biopolymer on the dominant plant species in riverbanks. Overall, biopolymer did not affect seed germination rates of testing plant species. In contrast, plants grew more vigorously in the soil mixed with biopolymer compared to those in the control soil. The biomass of Echinochloa crus-galli especially increased around two times more in the biopolymer treatment. Plants produced heavier root biomass and leaves with larger specific leaf area, which possibly contributes to the tolerance of environmental stress like drought. These results suggest that biopolymers treated on river banks are expected to stimulate plant growth and increase stress tolerance of domestic dominant plant species.
This study was designed to comprehensively understand and separate the characteristics of recreation forests of Korea through the multi-variate analysis for the provision of fundamental materials for recreation forests development policies and planning, and attempted to evaluate on the validity of classification of recreation forests, which has never been performed before. According to analysis results, recreation forests could be divided into 4 types; type I(recreation forests whose ecological nature status is not good, but the risk of calamity is low and accessibility is good), type II(recreation forests whose the risk of calamity is low, but ecological nature status is not good, slope is steep, and accessibility is poor), type III(recreation forests that have charming vegetation and landscape, various rest opportunity, and a gentle slope, but poor accessibility), and type IV(recreation forests that ecological nature status is good, but have poor landscape, less rest opportunity, and a steep slope). Also, each type was adjusted as follows; type I($25{\rightarrow}24$ reviews), type II($25{\rightarrow}26$ reviews), type III($17{\rightarrow}16$ reviews), and type IV($25{\rightarrow}25$ reviews). This study can be said to show the usability of validation of classified types, which was not done before. It is clear that the classification of recreation forests increases the efficiency in policy making and performance. Furthermore, by validating the separated types, we could expect high efficiency in policy making and performance on planned recreation forests in the future.
The objective of this study is to evaluate the appropriateness of methodology for designing urban sewer system using a rational method-based model, Makesw and an urban runoff model, SWMM. The Gunja basin was selected as a study area and precipitation, runoff, vegetation, soil, imperviousness data were used to estimate floods. The appropriateness of methodology was evaluated based on comparison analysis between floods estimated from Makesw and SWMM. The comparison analysis was conducted between floods estimated from Makesw and SWMM, which were simulated using design rainfall and measured rainfall from past inundation events. The comparison results showed that in the case of design rainfall, the rational method-based floods were larger than that based on SWMM in all main lines. However in several branch lines, the rational method-based floods were smaller than thoes based on SWMM. In addition, for the case of measured rainfall from past inundation events, it was easily to find the main and branch lines where the rational method-based floods were smaller than SWMM based ones. Especially, the lines where rational method-based floods were underestimated, were mostly main, $1^{st}$, $2^{nd}$ lines. It was concluded that the rational method-based results were not conservative. Based on rational method (steady flow analysis) and SWMM (unsteady flow analysis), the more conservative results the method provides, the more highly it is recommended to use in designing an urban sewer system.
True color images display colors similar to natural colors. This has the advantage that it is possible to monitor rapidly the complex earth atmosphere phenomenon and the change of the surface type. Currently, various organizations are producing true color images. In Korea, it is necessary to produce true color images by replacing generations with next generation weather satellites. Therefore, in this study, visual enhancement for true color image production was performed using Top of Atmosphere (TOA) data of Advanced Himawari Imager (AHI) sensor mounted on Himawari-8 satellite. In order to improve the visualization, we performed two methods of Nonlinear enhancement and Histogram equalization. As a result, Histogram equalization showed a strong bluish image in the region over $70^{\circ}$ Solar Zenith Angle (SZA) compared to the Nonlinear enhancement and nonlinear enhancement technique showed a reddish vegetation area.
Open-pit mine development requires continuous management because of topographical changes and there is a risk of accidents if the current status survey is performed directly in the process of calculating the earthwork. In this study, the application of UAV photogrammetry, which can acquire spatial information without direct human access, was applied to open-pit mines development area and analyzed the accuracy, earthwork, and mountain restoration plan to determine its applicability. As a result of accuracy analysis at checkpoint using ortho image and Digital Surface Model(DSM) by UAV photogrammetry, Root Mean Square Error(RMSE) is 0.120 m in horizontal and 0.150 m in vertical coordinates. This satisfied the tolerance range of 1:1,000 digital map. As a result of the comparison of the earthwork, UAV photogrammetry yielded 11.7% more earthwork than the conventional survey method. It is because UAV photogrammetry shows more detailed topography. And result of monitoring mountain restoration showed possible to determine existence of rockfall prevention nets and vegetation. If the terrain changes are monitored by acquiring images periodically, the utility of UAV photogrammetry will be further useful to open-pit mine development.
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.
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)
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.
Kim, Suryeon;Choi, Jaeyeon;Seo, Jayoo;Kim, Sukyoung;Baek, Jiwon;Song, Wonkyong;Park, Chan
Journal of Environmental Impact Assessment
/
v.31
no.4
/
pp.241-249
/
2022
Humans and wild birds coexist in cities, where habitat fragmentation due to urbanization threatens the habitat and movement of birds. In this study, in order to identify landscape features associated with wild bird collide, we characterized landscape composition within a 500 m radius and points of wild bird carcasses in Suwon-city, South Korea. Dead birds were identified as having a Normalized Difference Vegetation Index (NDVI) of 0.3, Normalized Difference Built-up Index (NDBI) of -0.05, and Normalized Difference Water Index (NDWI) of -0.16 at the points of collide. And there were NDVI of 0.34, NDBI of -0.01, NDWI of -0.18, building height of 13.8 m, and soundproof wall length of 227.3 m within a radius of 500 m. Land cover type was dominated by grassland, used area, and bare land. In particular, the edges of urbanized areas, where apartments bordered forests, reservoirs, and golf courses, were identified as high-risk spaces. In order to minimize bird mortality risk in urban environments, the impact of changes to a vertical landscape should be reviewed from an environmental impact assessment approach. In addition, a preventive management plan that considers the temporal and spatial features that wild animals can safely avoid and adapt to in urbanized spaces should be prepared.
Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R2 =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.
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