• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.3
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• pp.65-77
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• 2015

The urban park has important functions as a habitat for wildlife as well as open space of rest and community for people. This study was carried out to find what factors of structure and vegetation of urban parks could affect forest bird species diversity in Cheonan city. The study surveyed bird and vegetation species in 26 urban parks, Cheonan city. A correlation analysis and multiple linear regressions were performed to test whether habitat structure and vegetation were the major correlate with species diversity. The results showed the Dujeong park was the most high bird species diversity (H' = 2.13), and the Dujeong-8 park (H' = 2.02) and the Cheongsa park (H' = 1.73) were considerably higher than the other urban parks. The variables that were strongly correlated with bird species diversity were park area, number of subtree species, canopy of shrub, number of shrub species, shape index, canopy of subtree, canopy of tree, and impervious surface ratio. The regression of bird species diversity against the environmental variables showed that 3 variables of park area, canopy of subtree, and canopy of tree were included in the best model. Model variable selection was broadly similar for the 5 optimal models. It means park area and multi-layer vegetation were the most consistent and significant predictor of bird species diversity, because urban parks were isolated by built-up areas. Especially the subtree coverage that provides shelter and food for forest birds was an important variable. Therefore, to make parks circular-shaped and abundant multi-layer vegetation, which could be a buffer to external disturbances and improve the quality of habitats, may be used to enhance species diversity in creation and management of urban parks.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.25-34
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• 2020

Land use in watersheds has been shown to be a major driving factor in determining the status of the water quality of streams. In this light, scientists have been investigating the roles of riparian vegetation on the relationships between land use in watersheds and the associated stream water quality. Numerous studies reported that riparian vegetation could alleviate the adverse effects caused by land use in watersheds and on stream water quality through various hydrological, biochemical and ecological mechanisms. However, this concept has been criticized as the true effects of riparian vegetation must be assessed by comprehensive models that mimic real environmental settings. This study aimed to estimate a comprehensive structural equation model integrating topography, land use, and characteristics of riparian vegetation. We used water quality data from the Nakdong River system monitored under the National Aquatic Ecosystem Monitoring Program (NAEMP) of the Korean Ministry of Environment (MOE). Also, riparian vegetation data and land use data were extracted from the Land Use/Land Cover map (LULC) produced by the MOE. The number of structural equation models (SEMs) were estimated in Amos of IBM SPSS. Study results revealed that land use was determined by elevation, and developed areas within a watershed significantly increased the concentration of Total Nitrogen (TN) in streams and LDI in riparian vegetation. On the contrary, developed areas significantly reduced LPI and PLAND. At the same time, PLAND and LDI significantly reduced the concentration of TN in streams. Thus, it was clear that developed areas in watersheds had both a direct and an indirect impact on the concentration of TN in streams, and spatial pattern and the amount of vegetation of riparian vegetation could significantly alleviate the negative impacts of developed areas on TN concentration in streams. To enhance stream water quality, reducing developed areas in a watershed is critical for long-term watershed management plans, restoration patterns for riparian vegetation could be immediately implemented since riparian areas were less developed than most other watersheds.

• Environmental Analysis Health and Toxicology
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• v.30
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• pp.10.1-10.14
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• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.471-479
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• 2011

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

• Journal of Ecology and Environment
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• v.36 no.4
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• pp.235-243
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• 2013

In Korea, where the plain land is greatly deficient as a mountainous nation, most of riparian zones were transformed into agricultural fields and urban areas. Excessive use of the land, which is close to river, makes the rivers enduring severe pollution stresses. Disappearance of riparian buffer, which plays a function of filter in the riverside, appears as a main factor aggravating water pollution of rivers. In this respect, it is imperative to restore the lost riparian vegetation. This study found out restoration models of riparian vegetation from the Bongseonsa stream, which has remnant riparian vegetation patches as a conservation reserve. Feasible reference information applicable for restoration of riparian vegetation was shown in the species level in the order of herb, shrub, and tree and sub-tree zones as far away from the waterway. Those information could contribute to restoring integrate and healthy rivers and streams beyond simple landscaping differently from the other restoration projects when they will be applied to the restoration project to be carried out in the future. In addition, the spatial range of river and stream, background that riparian zone disappeared in Korea, and application plan of the obtained reference information were discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.153-153
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• 2019

Evapotranspiration (ET) is an important component of hydrological processes. Accurate estimates of ET variation are of vital importance for natural hazard adaptation and water resource management. This study first developed a soil water index (SWI)-based Priestley-Taylor algorithm (SWI-PT) based on the enhanced vegetation index (EVI), SWI, net radiation, and temperature. The algorithm was then compared with a modified satellite-based Priestley-Taylor ET model (MS-PT). After examining the performance of the two models at 10 flux tower sites in different land cover types over East Asia and Australia, the daily estimates from the SWI-PT model were closer to observations than those of the MS-PT model in each land cover type. The average correlation coefficient of the SWI-PT model was 0.81, compared with 0.66 in the original MS-PT model. The average value of the root mean square error decreased from $36.46W/m^2$ to $23.37W/m^2$ in the SWI-PT model, which used different variables of soil moisture and vegetation indices to capture soil evaporation and vegetative transpiration, respectively. By using the EVI and SWI, uncertainties involved in optimizing vegetation and water constraints were reduced. The estimated ET from the MS-PT model was most sensitive (to the normalized difference vegetation index (NDVI) in forests) to net radiation ($R_n$) in grassland and cropland. The estimated ET from the SWI-PT model was most sensitive to $R_n$, followed by SWI, air temperature ($T_a$), and the EVI in each land cover type. Overall, the results showed that the MS-PT model estimates of ET in forest and cropland were weak. By replacing the fraction of soil moisture ($f_{sm}$) with the SWI and the NDVI with the EVI, the newly developed SWI-PT model captured soil evaporation and vegetation transpiration more accurately than the MS-PT model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.85-96
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• 2023

This study proposes a method for forest vegetation monitoring using high-resolution aerial imagery captured by unmanned aerial vehicles(UAV) and deep learning technology. The research site was selected in the forested area of Mountain Dogo, Asan City, Chungcheongnam-do, and the target species for monitoring included Pinus densiflora, Quercus mongolica, and Quercus acutissima. To classify vegetation species at the pixel level in UAV imagery based on characteristics such as leaf shape, size, and color, the study employed the semantic segmentation method using the prominent U-net deep learning model. The research results indicated that it was possible to visually distinguish Pinus densiflora Siebold & Zucc, Quercus mongolica Fisch. ex Ledeb, and Quercus acutissima Carruth in 135 aerial images captured by UAV. Out of these, 104 images were used as training data for the deep learning model, while 31 images were used for inference. The optimization of the deep learning model resulted in an overall average pixel accuracy of 92.60, with mIoU at 0.80 and FIoU at 0.82, demonstrating the successful construction of a reliable deep learning model. This study is significant as a pilot case for the application of UAV and deep learning to monitor and manage representative species among climate-vulnerable vegetation, including Pinus densiflora, Quercus mongolica, and Quercus acutissima. It is expected that in the future, UAV and deep learning models can be applied to a variety of vegetation species to better address forest management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2453-2467
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• 2017

Wireless communication is a telecommunication technology, which enables wireless transmission between the portable devices to provide wireless access in all types of environments. In this research, the measurements and various empirical models are analysed and compared in order to find out a suitable propagation model to provide guidelines for cell planning of wireless communication systems. The measured data was taken in urban region with low vegetation and some trees at 900 MHz frequency band. Path loss models are useful planning tools, which permit the designers of cellular communication to obtain optimal levels for the base station deployment and meeting the expected service level requirements. Outcomes show that these empirical models tend to overestimate the propagation loss. As one of the key outputs, it was observed that the calculations of Weissberger model fit with the measured data in urban environment.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.320-329
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• 2022

Urban areas in watersheds increase the impervious surface, and agricultural areas deteriorate the water quality of rivers due to the use of fertilizers. As such, anthropogenic land use affects the type, intensity and quantity of land use and is closely related to the amount of substances and nutrients discharged to nearby streams. Riparian vegetation reduce the concentration of pollutants entering the watershed and mitigate the negative impacts of land use on rivers. This study analyzes the data through correlation analysis and regression analysis through point data measured twice a year in spring and autumn in 21 selected damaged tributary rivers within the Han River area, and then uses a structural equation model to determine the area land use. In the negative impact on water quality, the mitigation effect of riparian vegetation was estimated. As a result of the correlation analysis, the correlation between the agricultural area and water quality was stronger than that of the urban area, and the area ratio of riparian vegetation showed a negative correlation with water quality. As a result of the regression analysis, it was found that agricultural areas had a negative effect on water quality in all models, but the results were not statistically significant in the case of urban areas. As a result of the model estimated through the structural equation, BOD, COD, TN, and TP showed a mitigation effect due to the accumulation effect of river water quality through riparian vegetation in agricultural areas, but the effect of riparian vegetation through riparian vegetation was found in urban areas. There was no These results were interpreted as having a fairly low distribution rate in urban areas, and in the case of the study area, there was no impact due to riparian forests due to the form of scattered and distributed settlements rather than high-density urbanized areas. The results of this study were judged to be unreasonable to generalize by analyzing the rivers where most of the agricultural areas are distributed, and a follow-up to establish a structural equation model by expanding the watershed variables in urban areas and encompassing the variables of various factors affecting water quality research is required.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.15-25
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• 2015

The growth of impermeable layers in the city center due to today's urban development is emerging as a major cause of urban heat island effects as well as recurring inland flood damages. In order to cope with such disasters caused by climatic changes, an artificial ground afforestation system is suggested as a fundamental solution that addresses both water environment and heat environment. For the afforestation system to replace the current disaster prevention facilities, quantitative performance verification through related numerical analysis models and actual survey monitoring is necessary. Therefore, this study seeks to propose the performance predication method for the heat environment of the afforestation system by looking into correlations between measurements by physical vegetation indicators such as LAI and FVC and forecasts from FASST, a vegetation canopy model used by US Corps of Engineers.