• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.80-88
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• 2020

With the issuance of one-week fine dust emergency reduction measures in March 2019, the public's anxiety about fine dust is increasingly growing. In order to assess the application of air purifying plant-based bio-filters to public facilities, this study presented a method for measuring pollutant reduction effects by creating an indoor environment for continuous discharge of particle pollutants and conducted basic studies to verify whether indoor air quality has improved through the system. In this study conducted in a lecture room in spring, the background concentration was created by using mosquito repellent incense as a pollutant one hour before monitoring. Then, according to the schedule, the fine dust reduction capacity was monitored by irrigating for two hours and venting air for one hour. PM₁₀, PM_2.5, and temperature & humidity sensors were installed two meters front of the bio-filters, and velocity probes were installed at the center of the three air vents to conduct time-series monitoring. The average face velocity of three air vents set up in the bio-filter was 0.38±0.16 m/s. Total air-conditioning air volume was calculated at 776.89±320.16㎥/h by applying an air vent area of 0.29m×0.65m after deducing damper area. With the system in operation, average temperature and average relative humidity were maintained at 21.5-22.3℃, and 63.79-73.6%, respectively, which indicates that it satisfies temperature and humidity range of various conditions of preceding studies. When the effects of raising relatively humidity rapidly by operating system's air-conditioning function are used efficiently, it would be possible to reduce indoor fine dust and maintain appropriate relative humidity seasonally. Concentration of fine dust increased the same in all cycles before operating the bio-filter system. After operating the system, in cycle 1 blast section (C-1, β=-3.83, β=-2.45), particulate matters (PM₁₀) were lowered by up to 28.8% or 560.3㎍/㎥ and fine particulate matters (PM_2.5) were reduced by up to 28.0% or 350.0㎍/㎥. Then, the concentration of find dust (PM₁₀, PM_2.5) was reduced by up to 32.6% or 647.0㎍/㎥ and 32.4% or 401.3㎍/㎥ respectively through reduction in cycle 2 blast section (C-2, β=-5.50, β=-3.30) and up to 30.8% or 732.7㎍/㎥ and 31.0% or 459.3㎍/㎥ respectively through reduction in cycle 3 blast section (C-3, β=5.48, β=-3.51). By referring to standards and regulations related to the installation of vegetation bio-filters in public facilities, this study provided plans on how to set up objective performance evaluation environment. By doing so, it was possible to create monitoring infrastructure more objective than a regular lecture room environment and secure relatively reliable data.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.2
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• pp.32-41
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• 2008

An empirical study and environmental and ecological analysis were conducted on Otgol Village(a village of the Gyeongju Choi's clan in Daegu) where an enclosed pond and groves are still observed. In particular, the enclosed pond and groves and village water system were investigated from an ecological perspective. The enclosed landscape is described based on feng shui principles and the environmental and ecological significance were examined. In general, the environmental and ecological significance is very broad; however, they were analyzed in terms of the quality of life as an empirical study as follows: First, water quality was measured to investigate the improvement of continuous water system functions. In other words, water quality was measured at East Valley(resting space), West Valley(living space), the enclosed pond where the two valleys merge, and the stream that flows out of the pond. Second, the climate functions of the enclosed groves that border the village were examined. In other words, temperature was measured in two places(200m distance from the center of the groves). Third, whether or not a sound ecosystem can be sustained was investigated. In other words, landscape ecological indicators were chosen and measured. The results are as follows: First, the enclosed pond played the role of purifying water quality. While the East Valley has been popular with men for its rock walls and torrents, the West Valley has been popular with women as a living space(ex: doing the laundry). Therefore, the difference of water quality can be explained. Second, since enclosed groves are in a small village forest, they are very weak in terms of being wind proof and temperature reduction effects. Instead, they play the role of the village boundary. Third, the groves are ecologically sound considering the landscape ecological indicators and are similar to ordinary traditional rural villages. In terms of the connection of the green zone, the village groves are well connected to the village boundary wood. If the village groves are restored, in particular, they would offer a decent habitat for grove creatures. According to this study, the traditional village space was formed upon the influence of Feng Shui theories that are based on environmental and ecological principles that focus on the harmony between humans and nature. From the environmental and ecological perspective, the enclosed pond and groves are important factors in building a sustainable village. The diverse water space would help to improve water quality and increase water volume by promoting the water circulation system. In addition, the village woods would surround the village and decrease the temperature and humidity difference between winter and summer. If the groves are small and badly damaged, however, they are meaningful only in dividing the region. The overall improvement of a forestation system and botanical composition may increase the biological diversity and promote the migration of species. Otgol Village has developed an enclosed landscape to improve the village environment. In other words, a sound and refreshing living environment can be developed when the natural ecological system is well understood and properly preserved. Additionally, this traditional village planning will be the environmental and ecological method. From the perspective of environmental ecology, therefore, a traditional village is recommended.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.188-194
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• 2007

The relationships between pine mushroom emergence and meteorological factors were analyzed with three years (from 2003 to 2005) of measurement data at Yangyang site, in order to evaluate the effect of micrometeorological environment on pine mushroom production. fine mushroom was daily monitored and collected in the survey area during the its producing period (approximately one month). Pine mushroom production was highest in 2005 with the meteorological conditions of high temperature and frequent rainfalls in October. The production was lowest in 2004 due to dry conditions from mid September to late October, The meterological factors related to humidity (i.e., relative humidity, soil water content, and precipitation) were better correlated than those related to temperature (i.e., air and soil temperature, soil heat flux and solar radiation) with pine mushroom production. However, all of the correlation coefficients were statistically insignificant with values ranging from 0.15 to 0.46. Such poor correlations may be attributed to various other environmental conditions (e.g., topography, soil, vegetation, other fungi, the relationship between pine mushroom and pine forest) affecting pine mushroom production. We found that a mycelium requires a stimulation of low temperature (of three-day moving average) below $19.5^{\circ}C$, in order to farm a mushroom primordium which grows to pine mushroom after 16 days from the stimulation. We also found that the pine mushroom production ended when the soil temperature (of three-day moving average) fell below $14.0^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• 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.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.515-529
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• 2020

Constructed wetlands undergo biological and physical changes such as an increase in the proportion of arid plants due to the natural succession process after formation. It can adversely affect not only the purification function but also the habitat of species. As such, this study aims to identify environmental factors affecting biodiversity and propose management plans based on the monitoring results of physical environmental changes and the emergence of species in seven constructed wetlands selected based on the water depth and surrounding conditions among the lands purchased by the Nakdong River basin. We examined the environmental conditions and emergence of the Odonata, which is a wetland-dependent species, to predict the trend of changes in biodiversity and abundance. The results showed that the open water area decreased as the emergent plants spread to the deep water in 2015 compared to 2012 when they were initially restored to a depth of 0.2 to 1 m. While a total of 54 dragonfly species were observed, the habitat diversity, such as vegetation, water surface, and grassland, remained similar to the initial formation of the wetlands despite the expansion of the emergent plants. On the other hand, the number of Agrionidae species, which prefer areas with fewer aquatic plants, decreased between 2012 and 2015 due to the diminished water surface. The p-values of the differences in the number of species and population between wetlands by year were 2.568e-09 and 1.162e-08, respectively, indicating the statistically significant differences. The decrease in open water surface was found to have the greatest effect on the biodiversity and habitat density of dragonflies. The time-series survey of constructed wetlands confirmed that the spread of Phragmites communis, P. japonica, Typha orientalis, etc., caused a decrease in species diversity. It suggests that environmental management to maintain the open water surface area is necessary.

• Journal of Korean Society of Forest Science
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• v.84 no.4
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• pp.465-478
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• 1995

The objective of this study was to investigate the impacts of large-scale timber harvesting on the environment of a mature hardwood forest. To achieve the objective, the effects of harvesting on forest environmental factors were analyzed quantitatively using the field data measured in the study sites of Seoul National University Research Forests [(Mt.) Paekunsan] for two years(1993-1994) following timber harvesting. The field data include information on vegetation, soil mesofauna, physicochemical characteristics of soil, surface water runoff, water quality in the stream, and hillslope erosion. For comparison, field data for each environmental factor were collected in forest areas disturbed by logging and undisturbed, separately. The results of this study were as follows : The diversity of vegetational species increased in the harvested sites. However, the similarity index value of species between harvested and non-harvested sites was close to each other. Soil bulk density and soil hardness were increased after timber harvesting, respectively. The level of organic matter, total-N, avail $P_2O_5$, CEC($K^+$, $Na^+$, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$) in the harvested area were found decreased. While the population of Colembola spp., and Acari spp. among soil mesofauna in harvested sites increased by two to seven times compared to those of non-harvested sites during the first year, the rates of increment decreased in the second year. However, those members of soil mesofauna in harvested sites were still higher than those of non-harvested sites in the second year. The results of statistical analysis using the stepwise regression method indicated that the diversity of soil mesofauna were significantly affected by soil moisture, soil bulk density, $Mg^{{+}{+}}$, CEC, and soil temperature at soil depth of 5(0~10)cm in the order of importance. The amount of surface water runoff on harvested sites was larger than that of non-harvested sites by 28% in the first year and 24.5% in the second year after timber harvesting. The level of BOD, COD, and pH in the stream water on the harvested sites reached at the level of the domestic use for drinking in the first and second year after timber harvesting. Such heavy metals as Cd, Pb, Cu, and organic P were not found. Moreover, the level of eight factors of domestic use for drinking water designated by the Ministry of Health and Welfare of Korea were within the level of the first class in the quality of drinking water standard. The study also showed that the amount of hillslope erosion in harvested sites was 4.77 ton/ha/yr in the first year after timber harvesting. In the second year, the amount decreased rapidly to 1.0 ton/ha/yr. The impact of logging on hillslope erosion in the harvested sites was larger than that in non-harvested sites by seven times in the first year and two times in the second year. The above results indicate that the large-scale timber harvesting cause significant changes in the environmental factors. However, the results are based on only two-year field observation. We should take more field observation and analyses to increase understandings on the impacts of timber harvesting on environmental changes. With the understandings, we might be able to improve the technology of timber harvesting operations to reduce the environmental impacts of large-scale timber harvesting.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.