• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.1-14
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• 2019

The 1st Forest Health Management survey was conducted to examine the health of the forests in Korea. However, in order to understand the health of the forests, which account for 63.7% of the total land area in South Korea, it is necessary to comprehensively spatialize the results of the survey beyond the sampling points. In this regard, out of the sample points of the 1st Forest Health Management survey in Gyeongbuk area, 78 spots were selected. For these spots, the species diversity index was selected from the survey sections, and the spatial interpolation method was applied. Inverse distance weighted (IDW), Ordinary Kriging and Ordinary Cokriging were applied as spatial interpolation methods. Ordinary Cokriging was performed by selecting vegetation indices which are highly correlated with species diversity index as a secondary variable. The vegetation indices - Normalized Differential Vegetation Index(NDVI), Leaf Area Index(LAI), Sample Ratio(SR) and Soil Adjusted Vegetation Index(SAVI) - were extracted from Landsat 8 OLI. Verification was performed by the spatial interpolation method with Mean Error(ME) and Root Mean Square Error(RMSE). As a result, Ordinary Cokriging using SR showed the most accurate result with ME value of 0.0000218 and RMSE value of 0.63983. Ordinary Cokriging using SR was proven to be more accurate than Ordinary Kriging, IDW, using one variable. This indicates that the spatial interpolation method using the vegetation indices is more suitable for spatialization of the biodiversity index sample points of 1st Forest Health Management survey.

• Korean Journal of Environment and Ecology
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• v.32 no.3
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• pp.289-302
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• 2018

The study investigated the forest vegetation in 59 plots between June 2017 and August 2017 to understand the forest vegetation structure of the protected zone for forest genetic resource conservation (forest genetic resource reserve area) in Heuksando Island. We classified the vegetation using the Z-M phytosociological method analyzed the importance value and species diversity of each vegetation classification. The analysis showed the Camellia japonica community group at a top level of forest vegetation hierarchy. In the level of community, it was classified into Dendropanax morbiferus community (Vegetation unit 1; VU 1), Carpinus turczaninowii community, and C. japonica typical community (VU 6). C. turczaninowii community was subdivided into Buxus koreana group (VU 2), Rhododendron mucronulatum group (VU 3), Vitis amurensis group (VU 4) and C. turczaninowii typical group (VU 5). Therefore, it was classified into a total of six vegetation units (one community group, three communities, and four groups). The analysis of the mean codominant value of each VU show that Quercus acuta was the highest in VU 1, C. turczaninowii in VU 2, Pinus thunbergii in VU 3, Pinus densiflora in VU 4, and Castanopsis sieboldii in VU 5 and VU 6. The analysis of species diversity showed that VU 2 was the highest among six units in species richness index, species diversity index, and species evenness index. VU 6 showed the highest among six units in species dominance index. In conclusion, a synecology approach to manage six units and twelve species groups was needed for the forest vegetation of Heuksando Island protected area for forest genetic resource conservation.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Journal of Forest and Environmental Science
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• v.37 no.4
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• pp.292-303
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• 2021

Studies that relate the structure of tropical regrowth vegetation to soil properties are generally lacking in the literature. This study proposes three indices for assessing the structural regeneration of secondary forests. They are: (1) the tree diameter class, (2) the plant life form and (3) the woody/herbaceous plants ratio indices. They were applied to assess the regeneration status of forest regrowth vegetation (aged 1-10 years), derived savanna regrowth vegetation in south western Nigeria, and to secondary forests in different stages of succession in Columbia and Venezuela, Bolivia, Mexico in South and Central America and semi-arid savanna in Ethiopia and seasonal deciduous forest successional stages in India. In all the cases, the indices increased with increasing age of regrowth vegetation and hence, with increasing structural complexity of regenerating vegetation. The tree diameter class index increased from 32.1% in a 9-year secondary forest to 69.0% in an 80-year-old secondary forest in Columbia and Venezuela and from 0.4% in a 1-year fallow to 20.9% in 10-year regrowth vegetation in southwestern Nigeria. In semi-arid savanna in northern Ethiopia, the woody/herbaceous plants ratio index increased from 18.1% in a 5-year protected grazing enclosure to 75.1% in 15-year protected enclosure, relative to the status of 20-year enclosure. The indices generally had correlations of 0.6-0.90 with species richness and Simpson's/Margalef's species diversity, implying that they are appropriate measures of ecosystem development over time. The proposed indices also had strong and positive correlations with soil organic carbon and nutrients. They are therefore, significant indicators of fertility status.

• Korean Journal of Remote Sensing
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• v.12 no.1
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• pp.60-80
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• 1996

AVHRR(Advanced Very High Resolution Radiometer) on NOAA satellite provides data in five spectral, one in visible range, one in near infrared and three in thermal range. In this paper, application of NOAA/AVHRR data is studied for environment monitoring such as cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index, forest fire, flood, snow cover and so on. The analyses for cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index and forest fire showed reasonable agreement. But monitoring for flood and snow cover was uneasy due to the limitations such as cloud contamination, low spatial resolution. So this research had only simple purpose to identify well-defined waterbody for dynamic monitoring of flood. Based on development of these basic algorithms, we have a plan to further reseach for environment monitoring using AVHRR data.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.

• Water for future
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• v.28 no.1
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• pp.71-80
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• 1995

The purpose of this study is to estimate evapotranspiration and its spatial distribution using NOAA-AVHRR data. Evapotranspiration phenomena are exceedingly complex. But, factors which control evapotranspiration can be considered that these are reflected by conditions of the vegetation. To evaluate the vegetation condition as a fixed quantity, the NDVI(Normalized Difference Vegetation Index) calculated from NOAA data is utilized. In this study, land cover classification of the Korean peninsula using property of NDVI is performed. Also, from the relationship between evapotranspiration and NDVI histograms, evapotranspiration and its distribution of the Han River basin are estimated.

• Journal of Environmental Science International
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• v.6 no.6
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• pp.605-612
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• 1997

This study is to evaluate the overall NPP(Net Primary Productions distribution in the Korean Peninsula from the satellite data(NOAA/AVHRR). This has been done using the linear relationship between the natural vegetation condition and the NPP. The NPP of natural vegetation increases proportional to the annual net radiation(Rn), where radiative dorless Index(RDI) is a proportional constant connecting Rn to NPP. Normalized Difference Vegetation Index(NDVI) Is used for monitoring vegetation change, and INDVI (Integrated NDVI) for annual analysis. The INDVI has a close relation to .Rn and NPP. which can be used effectively for estimating NPP distribution of where the meteorological data Is unavailable such as North Korea. The NPP distribution of the Korean Peninsula was estimated based on the model.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.37-42
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• 2009

This study extracted Near Infrared (NIR) band using Image Processing Technology (IPT), and calculated Normalized Difference Vegetation Index (NDVI). Aerial photography from Daum portal in combination with high resolution satellite image was employed to improve vegetation sensitivity by extracting NIR band and calculating NDVI with comparison to QuickBird result. The extracted NIR band and NDVI through IPT presented similar distribution pattern. In addition, a regression analysis by land cover character showed high correlation paddy and forest Therefore, this approach could be acceptable to acquire vegetation environment information.

• KCID journal
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• v.21 no.1
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• pp.78-88
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• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.