• Proceedings of the KSRS Conference
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• v.2
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• pp.848-851
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• 2006

Green vegetation is one of the most critical factors for environment conditions thorough modulating evapotranspiration and absorption of solar radiation. Thus, fractional green vegetation cover (FVC) plays an important role in observing and managing environment. Remote sensing provides a seemingly obvious data source for quantifying FVC over large area. Therefore we compared a set of methods for estimating FVC using hyperspectral remote sensing data. For our study, we used Hyperion imagery acquired in April, 2002. In order to achieve our efforts, we analyzed simple NDVI-based method and spectral mixture analysis (SMA) models that were applied a variety of combinations of possible endmembers.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.2
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• pp.37-45
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• 2022

In-situ pilot experiment was carried out to establish a countermeasure on the soil loss from the hill side uplands that was rehabilitated by soil remediation method nearby abandoned mine sites for 2 years. It was considered that the affect of an inclination of cover surface, a stabilization treatment of cover layer by lime and steel refining slag (SRS) and a vegetation of soil surface as an effect factors in the experiment. It was constructed 4 lysimeters (plots, 22 m long, 4 m width) on the hilly side (37% inclination). One plot was control and two plots was treated by 1% lime and SRS. A remind one plot was modified a inclination to 27% to compare the affect of inclination on the amount of cover soil loss. It was attached a reservior tank and water level gauge in the end of lysimeters to measure the amount of the surface water flow and soil loss. It was also installed the automated sensors that could be collect the precipitation, soil moisture content, tension of cover layer in each plots. It was observed that the event of precipitation were caused the soil loss and it were related the physical and chemical properties of cover soil and inclination of surface layer of plots. During the experiment, it was exceeded the national regulation (50 t/ha/yr) in 37% inclination plots even though it was vegetated on the cover soil surface. However, in 27% inclination plot, it was shown that the amount of soil loss was maintained below the national regulation and, more ever, vegetation could reduce the the amount of soil loss. Therefore it was expected that such results could be applied to the future design of rehabilitation projects on the polluted farmland nearby abandoned mine sites.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.343-343
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• 2023

식생피복(Vegetation cover)은 대기 중의 강우와 토양 사이에서 침식으로부터 표토를 보호하는 역할을 한다. 자유 낙하하는 강우의 물방울은 식생을 통과하면서 차단(interception), 수관통과(throughfall), 수간유하(stemflow)의 형태로 변화한다. 식생은 강우입자의 운동에너지와 수량을 감소시키고, 지표면에 도달하는 시간을 지연시킴에 따라 지표유출(overland flow) 저감에 기여한다. 유출수의 흐름과정에서 식물의 줄기, 낙엽, 뿌리 등은 유속을 감소시키는 장애물로 작용하여 궁극적으로 토양침식은 감소한다. 토양침식은 식생피복이 증가함에 따라 일반적으로 감소하며, 지수함수의 관계를 갖는다. 식생의 종류와 구조 그리고 잎의 모양 등에 따라 수문물리적인 반응이 달라진다. 캐노피를 갖는 지상식물(canopy cover plant)은 물방울의 운동에너지를 갖는 반면, 지피식물(ground cover plant)은 낙하고가 작기 때문에 운동에너지는 적으며, 특히 낙엽층은 지표면을 보호하여 토양침식의 저감효과가 더욱 크다. 산불지역의 식생피복에 따른 토양침식 측정 자료에 따르면, 강우운동에너지는 식생피복이 증가함에 따라 지상피복(canopy cover)에 의한 감소보다는 지면피복(ground cover)과 낙엽피복(litter cover)에 의한 감소효과가 상대적으로 컸다. 식생피복에 의해 차단되는 강우의 손실량보다 침투량 증가에 의한 손실량이 상대적으로 많았다. 낙엽피복에 대한 강우모의 실험 결과에 따르면, 낙엽의 피복율이 증가함에 따라 지수적으로 토양침식량은 감소하였다. 낙엽 피복율의 40% 이상은 토양침식량을 현격이 감소시킨 반면, 피복율의 70% 이상은 지표유출량을 현저히 감소시켰다. 낙엽 피복율이 70%이상이면, 유출계수가 33%가 감소하였으나, 토양침식민감도는 94%로 크게 감소하였다.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.661-670
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• 2012

Urban forests provide great ecosystem services to population in metropolitan areas even though they occupy little green space in a huge gray landscape. Unfortunately, urbanization inherently results in threatening the green infrastructure, and the recent urbanization trends drew great attention of scientists and policy makers on how to preserve or restore green infrastructure in metropolitan area. For this reason, mapping the spatial distribution of the green infrastructure is important in urban environments since the resulting map helps us identify hot green spots and set up long term plan on how to preserve or restore green infrastructure in urban environments. As a preliminary step for mapping green infrastructure utilizing multi-source remote sensing data in urban environments, the objective of this study is to map vegetation volume by fusing LiDAR and multispectral data in urban environments. Multispectral imageries are used to identify the two dimensional distribution of green infrastructure, while LiDAR data are utilized to characterize the vertical structure of the identified green structure. Vegetation volume was calculated over the metropolitan Chicago city area, and the vegetation volume was summarized over 16 NLCD classes. The experimental results indicated that vegetation volume varies greatly even in the same land cover class, and traditional land cover map based above ground biomass estimation approach may introduce bias in the estimation results.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.101-110
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• 2006

The accuracy of rural land cover using airborne multispectral images and LEAR (Light Detection And Ranging) data was analyzed. Multispectral image consists of three bands in green, red and near infrared. Intensity image was derived from the first returns of LIDAR, and vegetation height image was calculated by difference between elevation of the first returns and DEM (Digital Elevation Model) derived from the last returns of LIDAR. Using maximum likelihood classification method, three bands of multispectral images, LIDAR vegetation height image, and intensity image were employed for land cover classification. Overall accuracy of classification using all the five images was improved to 85.6% about 10% higher than that using only the three bands of multispectral images. The classification accuracy of rural land cover map using multispectral images and LIDAR images, was improved with clear difference between heights of different crops and between heights of crop and tree by LIDAR data and use of LIDAR intensity for land cover classification.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.101-115
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• 2021

The purpose of this study is to evaluate the compatibility of the vegetation index between the two satellites and the applicability of agricultural monitoring by comparing and verifying NDVI (Normalized Difference Vegetation Index) based on Sentinel-2 and Terra MODIS (Moderate Resolution Imaging Spectroradiometer). Terra MODIS NDVI utilized 16-day MOD13Q1 data with 250 m spatial resolution, and Sentinel-2 NDVI utilized 10-day Level-2A BOA (Bottom Of Atmosphere) data with 10 m spatial resolution. To compare both NDVI, Sentinel-2 NDVIs were reproduced at 16-day intervals using the MVC (Maximum Value Composite) technique. As a result of time series NDVIs based on two satellites for 2019 and compare by land cover, the average R² (Coefficient of determination) and RMSE (Root Mean Square Error) of the entire land cover were 0.86 and 0.11, which indicates that Sentinel-2 NDVI and MODIS NDVI had a high correlation. MODIS NDVI is overestimated than Sentinel-2 NDVI for all land cover due to coarse spatial resolution. The high-resolution Sentinel-2 NDVI was found to reflect the characteristics of each land cover better than the MODIS NDVI because it has a higher discrimination ability for subdivided land cover and land cover with a small area range.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.537-547
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• 2010

The importance of vegetation in studies of global climate and biogeochemical cycles is well recognized. Especially. the FPAR (fraction of photosynthetically active radiation) is one of the important parameters in ecosystem productivity and carbon budget models. Therefore, accurate estimates of vegetation parameters are increasingly important in environmental impact assessment studies. In this study, optical FPAR using the Terra MODIS (MODerate resolution Imaging Spectroradiometer), SPOT VEGETATION and ECOCLIMAP data reproduced on the Korean peninsula. We applied the empirical method which is usually estimated as a linear or nonlinear function of vegetation indices. As results, we estimated the accurate expression which is 0.9039 of $R^2$ in cropland and 0.7901 of $R^2$ in forest. Finally, this study could be demonstrated to calibrate that produced FPAR while the overall pattern and random noise through the comparative analysis of FPAR on the reference data. Optimal use of input parameter on the Korean peninsula should be helping the accuracy of output as well as the improved quality of research.

• Journal of Life Science
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• v.27 no.3
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• pp.301-309
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• 2017

This study is examined river naturality and vegetative composition of river riparian zones to identify their most important sources of variation. Information on plant species cover and on physical characteristics that occur at upper, medium, and low areas was collected for 30 riparian plots located throughout the Youngjeong River in Korea. The riparian areas of river banks are dominated by mixed sediment and the vegetation is composed of herbs, shrub, and trees. The floristic characterization of riparian at this river during 2015 season was identified with a total of 28 families, 72 genera, 75 species, 13 varieties, 23 associations. The vegetations of low water's edge and flood way at upper region were naturally formed various vegetation communities by natural erosion. Forty plant species were identified around the upper region, where the dominant growth form was mostly trees. The flood way vegetation at middle region was both of natural vegetation and artificial vegetation. Land uses in riparian zones river levee at low region were bush or grassland as natural floodplain. The values of cover-abundance at upper, middle, and low region were total 9.26, 7.24, and 7.56, respectively. Grasses and forbs at the Youngjeong River have similar cover-abundance values. Recent, many riparian areas of this river have been lost or degraded for commercial and industrial developments. Thus, monitoring for biological diversity of plant species of this river is necessary for an adaptive management approach and the successful implementation of ecosystem management.

• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.55-66
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• 2004

The Hapchon Dam, located upstream of the Hwang River, Korea, was constructed in December, 1988. Due to the lack of storage of water, the dam gate has not been operated during last ten years. Thus, a new ecosystem has been established at the downstream part of the dam. This is not a common phenomenon which can be found elsewhere in the country. The present study investigates the effect of flow regime change on the river morphology and vegetation cover in the downstream river reach after the dam construction. The analysis of flow regime is carried out, and the changes in bed elevation and in channel cross sections are examined. Site investigations including tree ring tests are also performed. The increase in the vegetation cover is estimated by comparing aerial photographs taken before and after dam construction.

• 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.