• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.328-330
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• 2003

The land cover of burned area has changed dramatically since Daxinganling forest fire in Northeastern China during May 6 ? June 4, 1987. This research focused on determining the burn severity and assessment of forest recovery. Burned severity was classified into three levels from June 1987 Landsat TM data acquired just after the fire. A regression model was established between the forest canopy closure from 1999 forest stand map and the NDVI values from June 2000 Landsat ETM+ data. The map of canopy closure was got according to the regression model. And vegetation cover was classified into four types according to forest closure density. The change matrix was built using the classified map of burn severity and vegetation recovery. Then the change conversions of every forest type were analyzed. Results from this research indicate: forest recovery status is well in most of burned scars; and vegetation change detection can be accomplished using postclassification comparison method.

• Architectural research
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• v.25 no.4
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• pp.73-84
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• 2023

Indoor thermal conditions greatly affect the health and comfort of humans who occupy the space in it. The purpose of this research is to analyze the influence of water and vegetation elements as a microclimate modifier in buildings to obtain thermal comfort through the study of thermal environment models. This research covers two objects, namely public buildings and housing in Makassar City, South Sulawesi Prov-ince - Indonesia. Quantitative methods through field surveys and measurements based on thermal and personal variables. Data analysis based on ASHRAE 55 2020 standard. The data was processed with a parametric statistical approach and then simulated with the Computational Fluid Dynamics (CFD) simulation method to find a thermal prediction model. The model was made by increasing the ventilation area by 2.0 m2, adding 10% vegetation with shade plant characteristics, moving water features in the form of fountains and increasing the pool area by 15% to obtain PMV + 0.23, PPD + 8%, TSV-1 - +0, Ta_25.7℃, and relative humidity 63.5 - 66%. The evaluation shows that the operating temperature can analyze the visitor's comfort temperature range of >80% and comply with the ASHRAE 55-2020 standard. It is concluded that water elements and indoor vegetation can be microclimate modifiers in buildings to create desired comfort conditions and adaptive con-trols in buildings such as the arrangement of water elements and vegetation and ventilation systems to provide passive cooling effects in buildings.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.127-135
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• 2011

This study was carried out in each three study areas of Pinus densiflora community and Quercus mongolica community from March 5th, 2008 to October 15th, 2010 to analyze the relationship between seed bank and the actual vegetation of the lower layer. Based on the relationship between the lower layer of actual vegetation and the germination of seed bank, all of three study areas, the similarity of the actual vegetation of the lower layer and seed bank were high in Plot 1 (84.62%) and Plot 3 (89.91%). As for Quercus mongolica community, the similarity was high between the actual vegetation of the lower layer and seed bank in Plot 4 (82.24%) and Plot 6 (89.47%). Especially, the germination of the pine seed banks in the Pinus densiflora community compared to other tree species appeared in all. In Quercus mongolica community, Quercus mongolica did not appear among the seeds germinated in the seek bank, but the other tree species constituting the under layer of the community. In case of the restoration based on the actual vegetation, it is desirable to sue the lower layer of vegetation as the model for the making of its alternatives for restoration works of the species.

• 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 Korea Water Resources Association
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• v.56 no.9
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• pp.575-586
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• 2023

River vegetation has important functions such as providing a habitat for the river ecosystem and physical stability of the river bank. It also has adverse effects such as aggravating flood damages due to the increase in roughness coefficient and drag forces. River vegetation management is very important in finding a balance between flood and ecological management. There are still many uncertainties about the effect of vegetation on rivers. In this study, in order to analyze the effect of vegetated flow, the flow patterns according to the vegetation roughness are analyzed through a two-dimensional unsteady flow model for Chopyeong island of the Imjin River. According to the results of the 2D flow analysis using the HEC-RAS 2D model, the velocity distribution in the bend of the Imjin River was greatly affected by the vegetation roughness of Chopyeong Island. The formation of the main flow outside the bend of Chopyeong Island during flooding is presumed due to the influence of tree and grass on Chopyeong Island. If tree are distributed throughout Chopyeong Island, the velocity outside the bend is expected to be higher. River vegetation causes the effect of raising the water level, and could cause a change in the velocity distribution.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.3 no.3
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• pp.151-158
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• 1999

Biogenic source emissions refer to naturally occuring emissions from vegetation, microbial activities in soil, lightening, and so on. Vegetation is especially known to emit a considerable amout of volatile organic compounds into the atmosphere. Therefore, biogenic source emissions are an important input to photochemical air quality models. since most biogenic source emissions are calculated at the county-level, they should be geographically allocated to the computational grid cells of a photochemical air quality model prior to running the model. The traditional method for the spatial allocation for biogenic source emissions has been to use a "spatial surrogate indicator" such as a county area. In order to examine the applicability of such approximations, this study developed more detailed surrogate indicators to improve the spatial allocation method for biogenic source emissions. Due to the spatially variable nature of biogenic source emissions, Geographic Information Systems(GIS) were introduced as new tools to develop more detailed spatial surrogate indicators. Use of these newly developed spatial surrogate indicators for biogenic source emission allocation provides a better resolution than the standard spatial surrogate indicator.indicator.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.5
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• pp.25-34
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• 2009

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.887-899
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• 2022

Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.52-65
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• 2012

The net biomass accumulation (or net primary production, NPP) and gross primary production (GPP) have closely related with carbon accumulations(or carbon exchange) in vegetation. There are many approaches to estimate biomass using remote sensing techniques. The vegetation indices (VIs) can be a methodology to estimate biomass which assumes total chlorophyll contents. Various VIs were characterized with difference development conditions as vegetation species, input datasets. The hyperspectral data have also different spatial/spectral resolutions for aerial surveying. Additionally they need particular spectral bands selection difficulty to calculate the VIs. The objective of this study is to evaluate the correlations with airborne hyperspectral data (compact airborne spectrographic imager, CASI) and spectral unmixing model (or spectral mixture analysis, SMA) to characterize vegetation indices in forest area. The spectral mixture analysis was used to model the spectral purity of each pixel as an endmember. The endmembers are the fraction components derived from hyperspectral data through the SMA. In this study, we choose three endmembers represented vegetation pixels in the hyperspectral data. These endmembers were compared with 9 VIs by the Pearson's correlation coefficient. The results show MTVI1 and TVI have same correlation coefficient with 0.877. The MCARI, especially has very high relationship with vegetation endmembers as 0.9061 at less vegetation and soil distributed site. The MTVI1 and TVI have high correlations with the vegetation endmembers as 0.757 in whole test sites.