• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.39-49
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• 1999

Urban streams have, recently, been straightened and widened to alleviate flooding problem. As a result, the stream have been modified inadvertently for ecological functions and microtopography. In this study, we investigated riparian vegetation and microtopography of the tributaries of Han River before and after the monsoon rain in summer. The purpose of this study was to relate the stream microtopography to the distribution of riparian vegetation. The stream microtopography was investigated for its scale and pattern. Vegetation was investigated from 131 plots by Braun-Blanquet method. The distribution of riparian vegetation was significantly correlated with the stream microtopography. Various herbaceous species occurred at stream bank slop, high terrace and channel side. However, at channel side and concave part of terrace where soils were in high moisture level, only a few wetland species were dominated. The complexity of the microtopography in the stream corridors led to heterogeneous riparian vegetation. The vegetation showed more stability against flooding at the stream corridors with natural and complex microtopography than at the urban-type stream corridors with simple topographical features. The results showed that the development of riparian vegetation was influenced by the changes in microtopography, which was primarily determined by the shape and characteristics of channel. It seemed that a close-to-nature river system would be restored more readily with an understanding of microtopographical features affecting the distribution of riparian vegetation.

• Korean Journal of Agricultural Science
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• v.38 no.2
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• pp.315-324
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• 2011

Riparian vegetation distribution patterns and diversity relative to various fluvial geomorphic channel patterns, stream bank stabilization methods, and stream flow processes are described and interpreted for selected nature-friendly small stream bank protection of Goesan, central Korea. Idong Stream Pilot Project, which began in May 2003 and finished in December 2003, was selected to develop effective methods which was nature-friendly stream bank protection. The project aim to maintain or increase stream bank stabilization ecosystem goods and services while protecting downstream and stream bank ecosystem. A number of protecting methods which were a Flight of fieldstone, Vegetation block, Green river block, Stone net, Green environment block, Eco friendly cobble, Vegetation mat and Geo-green cell and Firefly block were applied on the bank of Idong stream. The stream sites have been monitored about vegetation conditions each method in 2007. We selected six points to separately investigate in left and right bank. The main purpose of this study was to find out suitable methods and to improve stream restoration techniques for ecosystem. On the stream bank, H environment block method (9.7) was the highest average of vegetation coverage and Firefly block method (3.87) was the lowest average in applied methods.

• Korean Journal of Plant Resources
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• v.20 no.3
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• pp.234-241
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• 2007

The present study was undertaken to classify and describe the riparian vegetation of the 6 river${\cdot}$stream of Korea Peninsula. As a result the vegetation was divided into nineteen communities. The vegetation units obtained in the present study were as follow: A: Salix koreensis community, B: Salix gracilistyla community, C: Robinia pseudo-acacia community, D: Amorpha fluticosa community, E: Brousonnetia papyrifera community, F: Phyllostachys bambusoides community, G: Rubus corchorifolius community, H: Phramities japonica community, I: Phramites communis community, J: Miscanthus sacchariflorus community, K: Miscanthus sinesis var. purpurascens community, L: Artemisia princeps var. orientalis community, M: Humulus japonicus community, N: Zoysia japonica community, O: Inperata cylindrica var. koenigii community, P: Agropyron tsukushiense var. transiens community, Q: Juncos effusus var. decipiens community, R: Rumex crispus community, S: Persicaria hydropiper community. The vegetation characteristics of riversides was recovered in the surveyed results according to river${\cdot}$stream basin, in other words, 10 communities in the upper river${\cdot}$stream riparian, 15 communities in the middle river${\cdot}$stream riparian, 10 communities in the down river${\cdot}$stream riparian. The Phragmites japonica community in the upper and Phragmites communis community in the down was analyzed by common community of the 6 river${\cdot}$stream riparian, respectively, but none in the middle. The standing profile of vegetation across 6 river${\cdot}$stream was seen stepwise Phragmites japonica community, Salix gracilistyla community, Miscanthus sinensis var. purpurascens community, shrub community by natural waterway in the upper, Salix gracilistyla community, Phragmites communis community, Rumex crispus community, Miscanthus sacchariflorus community, Humulus japonicus community in the middle, Phragmites communis community in the down. The differences of distributional featurs of vegetation emerged from the riparian of the 6 river${\cdot}$stream, but don't from the 6 river${\cdot}$stream.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.3
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• pp.73-85
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• 2002

The purpose of this study was to develop prediction models for plant species abundance by stream restoration. Generally the stream plant is affected by stream gemophology. So in this study, the relationship between the vegetation abundance and stream gemophology was developed by multiple regression analysis. The stream characteristics utilized in this study were longitudinal slope, transectional slope, micro-landforms through the longitudinal direction, riparian width and geometric mean diameter and biggest diameter of bed material, and cumulated coarse and fine sand weight portion. The Pyungchang River with mountainous watershed and the Kyungan stream and the Bokha stream in the agricultural region were selected and vegetation species abundance and stream characteristics were documented from the site at 2~3km intervals from the upper stream to the lower. The Models for predicting the vegetation abundance were developed by multiple regression analysis using SPSS statistics package. The linear relationship between the dependant(species abundance) and independant(stream characteristics) variables was tested by a graphical method. Longitudinal and transectional slope had a nonlinear relationship with species abundance. In the next step, the independance between the independant variables was tested and the correlation between independant and dependant variables was tested by the Pearson bivariate correlation test. The selected independant variables were transectional slope, riparian width, and cumulated fine sand weight portion. From the multiple regression analysis, the $R^2$for the Pyungchang river, Kyungan stream, Bokga stream were 0.651, 0.512 and 0.240 respectively. The natural stream configuration in the Pyungchang river had the best result and the lower $R^2$for Kyunan and Bokha stream were due to human impact which disturbed the natural ecosystem. The lowest $R^2$for the Bokha stream was due to the shifting sandy bed. If the stream bed is fugitive, the prediction model may not be valid. Using the multiple regression models, the vegetation abundance could be predicted with stream characteristics such as, transection slope, riaparian width, cumulated fine sand weigth portion, after stream restoration.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.753-762
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• 2002

In-stream vegetation is an essential element of a stream channel. Vegetation plays an important role in flood control and the natural environment in stream channels. This research investigates the relationship between in-stream vegetation and stream changes. This study investigates the distribution characteristic of vegetation in some rivers of Korea. Although there are many physical factors that cause changes to streams, this research verified that in-stream vegetation caused sediment deposition. A hydraulic model experiment was conducted. Tests were conducted in a simulated gravel bed stream (bed slope 1/200) with Phragmites japonica. The average diameter of the bed load used was 0.3 mm and 27 kg were uniformly supplied for 1 hour under same hydraulic conditions. The deposition and scouring as well as the change of flow differed according to the density and arrangement of the Phragmites japonica. In-stream vegetation and stream channel change are closely related because deposition and scouring affects the distribution of vegetation.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2078-2082
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• 2009

Riparian vegetation distribution patterns and diversity relative to various fluvial geomorphic channel patterns, stream bank stabilization methods, and stream flow processes are described and interpreted for selected stream of Goesan, Central Korea. Idong Stream Pilot Project, which began in May 2003 and finished in December 2003, was selected to develop effective methods. The project aim to maintain or increase stream bank stabilization ecosystem goods and services while protecting downstream and stream bank ecosystem. A number of protecting methods which are a Flight of fieldstone, Vegetation block, Green river block, Stone net, Green environment block, Eco friendly cobble, Vegetation mat and Geo green cell and Firefly block were applied on the bank of Idong stream. The stream sites have been monitored about flora conditions each method in 2007. We selected 12 points for summer seasons to separately investigate in left bank, right bank and river bed. The main purpose of this study was to find out suitable methods and to improve stream restoration techniques for ecosystem. On the stream bank, Eco friendly cobble method(9.57) was the highest average of vegetation cover and Firefly block method(3.87) was the lowest average in applied methods.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.462-466
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• 2006

Close-to-nature stream evaluation is one of the processing to make the streams over in order to keep them natural. It is integral to evaluate and make an accurate analysis of them on the purpose of maintaining streams healthy. For many instances, there are, stream organization evaluation for restoration by German government, evaluation for ecosystem protection in natural preserves by New Zealand government, and stream-view evaluation for restoration by Britain government so on. In case of the country there are analysis and evaluation of stream physical organization by Cho, Yong-hyun, Close-to-nature stream evaluation for restoration by Kim, Dong-chan, evaluation of stream properties in korea by Park, Bong-jin. Close-to-nature evaluation by Lim, Chan-uk, that is advanced version of Park, Bong-jin's, shows form of stream including waterway curve, sand bar, diversity of flow, river bed material, diversity of minor bed, minor bed bank protection works, bank protection material. It also does environment of stream including side of minor bed vegetation, width of surface of the water/width of the river etc.. By the way, this evaluation does not have free access to apply those details above in the field, it often happens that you get various outcome from the one spot. so you must need more realistic testing method to obtain more accurate data. Remote sensing method is highly recommended because this is very useful for collecting realistic data of vegetation index. what is more, it can not only scan even the minimum area within its resolving power but also do obtain data anytime. Vegetation index indicates Ratio vegetation index, Normalized difference vegetation index, Soil adjusted vegetation index, Atmospherically resistant vegetation index etc.. The research is focusing on Cheokgwa stream which is the branch of Taehwa river and shows 19 sectioned Close-to-nature stream performed according to the method by Lim, chan-uk. Besides let you know vegetation index came from image data of satellite landsat 7 with the variation of buffering area, of the day 9. may. 2003. Of all, the outcome 0.758 at 200m buffer-zone of NDVI was the best we have got so far.