• Journal of the Korean earth science society
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• v.27 no.7
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• pp.787-803
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• 2006

The drought index has been developed, based on a $8.6{\mu}m$ surface emissivity in the $8-12{\mu}m$ MODIS channels over the African Sahel region (10-20 N, 13 W-35 W) and the Seoul Metropolitan Area (SMA: 37.2-37.7 N, 126.6-127.2 E). The emissivity indicates the $SiO_2$ strength and can vary interannually by vegetation, water vapor, and soil moisture, as a potential indicator of drought conditions. In a well-vegetated region close to 10 N of the Sahel, the Normalized Difference Vegetation Index (NDVI) showed high sensitivity, while the emissivity did not. On the other hand, the NDVI experienced negligible variability in a poorly vegetated region near 20 N, while the emissivity reflected sensitively the effects of atmospheric water vapor and soil moisture conditions. Seasonal variations of the emissivity (0.94-0.97) have been examined over the SMA during the 2003-2004 period compared to NDVI (or Enhanced Vegetation Index; EVI). Here, the dryness was more severe in urban area with less vegetation than in suburban area; the two areas corresponded to the north and south of the Han river, respectively. The emissivity exhibiting a significant spatial correlation of ${\sim}0.8$ with the two indices can supplement their information.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.329-332
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• 2007

Annual vegetation growth patterns are determined by the intrinsic phenological characteristics of each land cover types. So, if typical growth patterns of each land cover types are well-estimated, and a NDVI time-series data of a certain area is compared to those estimated patterns, we can implement more advanced analyses such as a land surface-type classification or a land surface type change detection. In this study, we utilized Terra MODIS NDVI 250m data and compressed full annual NDVI time series data into several indices using the Harmonic Analysis of Time Series(HANTS) algorithm which extracts the most significant frequencies expected to be presented in the original NDVI time-series data. Then, we found these frequencies patterns, described by amplitude and phase data, were significantly different from each other according to vegetation types and these could be used for land cover classification. However, in spite of the capabilities of the HANTS algorithm for detecting and interpolating cloud-contaminated NDVI values, some distorted NDVI pixels of June, July and August, as well as the long rainy season in Korea, are not properly corrected. In particular, in the case of two or three successive NDVI time-series data, which are severely affected by clouds, the HANTS algorithm outputted wrong results.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.3
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• pp.144-152
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• 2021

Sanankerto is one of pilot projects for tourism villages in Indonesia due to its natural tourism potential with a 24-ha bamboo forest located in Boon Pring Andeman area. However, the distribution of existing bamboo has never been identified or mapped. Thus, the mana gement is facing difficulty in planning and developing tourism potential as well as spatial management in the area. Therefore, the objectives of this study were to identify and analyze the structure of bamboo vegetation in the Boon Pring Tourism village an d to perform vegetation mapping. The type of research was descriptive exploratory with a cluster sampling technique (i.e., a two-stage cluster) covering an area of ± 10 ha. Bamboo vegetation analysis was performed by calculating diversity index (H'), evenness index (E), and Species Richness index (R). Data were collected through observation and interviews with local people and the manager to determine zonation division. Mapping of bamboo vegetation based on zoning was processed into thematic maps using ArcG is 10.3. Micro climatic factors were measured with three replications for each sub -cluster. Data were analyzed descriptively and quantitatively. Nine species of bamboo identified. Diversity, evenness, and species richness indices differed at each location. Activities of local communities, tourists, and manager determined the presence, number, and distribution of bamboo species. These bamboo distribution maps in three zoning (utilization, buffer, and core) can be used by manager for planning and developing natural tourism potential.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.561-564
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• 2008

Pinus densiflora(red pine) stands in Korea have been faced with the serious threat by pine wilt disease caused by Bursaphelenchus xylophilus (nematodes). It is not easy to early detect and prevent the infected trees because those cannot be visually identified during the initial phase of infection. Red pine is usually infected by B. xylophilus from May to July and can be just visually detected in October or November. While the infected trees are wilted, the spectral value of Near Infrared (NIR) is supposed to be decreased. Based on this phenomena, in this paper, the vegetation vitality change of infected trees was analyzed using vegetation indices. Spectral values of Red, Green and NIR had been acquired monthly by a portable NIR camera in the same place of red pine stands infected by pine wilt disease. It could be proven that the vegetation index, or vegetation vitality of damaged trees starts to decrease from June, in the early infecting phase.

• The Korean Journal of Ecology
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• v.21 no.5_1
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• pp.465-473
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• 1998

This study was carried out to investigate the developmental process of plant community during the secondary succession and changes of soil properties in the burned areas lapsed 28 years after the forest fire in Mt.Palgong. The forest fire occurred on March, 1969 and the red pine (pinus densiflora) forest and its floor vegetation were burned down. The results are summarized as follows: the floristic composition of burned and unburned areas were composed of 49 and 48 species of vascular plants, respectively. The dominant species based on SDR4 of the burned sites were Lespedeza maximowicxii(87.75), Carex humilis (62.94), Rhododendron schippenbachii(55.78) and Miscanthus sinensis var.purpurascens (51.94). In contrast, Pinus densiflora (81.17), Quercus serrata (53.58)m Carex humilis (53.11) and Miscanthus sinenis var. purpuracens (52.42) were dominant in the unburned area. The biological spectra showed the $H-D_1-R_5-e$ type in both areas. The indices of similarity (CCs) between the two areas were 0.80. Degree of succession (DS) was 734 in the burned area and 809 in the unburned area. The species diversity (H) and evenness indices (e) in the burned and unburned areas were 2.05, 2.13 and 0.53, 0.55, respectively. Dominance index (C) in the burned and unburned areas were 0.30 and 0.32, respectively. Soil properties such as soil pH, content of organic matter, total nitrogen, total carbon, exchangeable potassium, sodium, calcium, and magnesium in burned area were comparatively higher than those of unburned area. Monthly changes of soil properties were of little significance except for some cases. These results suggest that there was relationship between trend of vegetation recovery and the changes of soil properties after the forest fire. Mixed forestation of fire-resistant species and nitrogen fixation species will be effective for reforestation after the forest fire.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.2
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• pp.50-67
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• 1993

This study analyzed the distribution and structure of the vegetation landscape in Naejangsan National Park. The plant distribution was investigated using a field survey. There were 72 sites sampled using the clumpled sampling method. The data derived from the investigation was analyzed using the quantitative analysis of Bray-Curtis method. The analysis was performed by the classification of TWINSPAN. The ordination of DCA and RA was used for the species composition and successional trends. The results are as follows; 1. Quercus. serrata-Q. variabilis community as 21.76(16.49$\textrm{km}^2$), was the largest community in the actual vegetation of the Naejangsan National Park. The degree of green naturality index 8 area covered 64.8% of the study area and the index 6 area did 16%. 2. Classified by the ordination of DCA and environmental variables, such as the plant community was divided into seven groups according to the altitude and forming groups; Chamaecy Paris. pisifera-P.densiflora community, P.densiflora community, Q.variailis community, T.nuciofera-A.palmatum community. 3. Ther species diversity and evenness indices of C.pisifera-P.densiflora community, P.densiflora community appeared low but C.laxiflora communitywhich was the most stable community in the study area. 4. The similarity indices between Q.variabilis community and Q.serrata-Q.variabilis community were calculated 58.84%, but those between other communities were comparatively low level. 5. The successional trends of DBH class seem to be from C. pisifera-P.densiflora community, P.densiflora community to Quercus species community and from Q.variabilis community, Q.serrata-Q.variabilis community to Carpinus species community. 6. Results suggested that the successional trends in Naejangsan National Park; P.densiflora community\longrightarrowQ.variablilis community, Q.serrata-Q.variabilis community\longrightarrowC.laxiflora community in sequence.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.1-10
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• 2019

Unmanned aerial vehicle(UAV) can acquire images with lower cost than conventional manned aircraft and commercial satellites. It has the advantage of acquiring high-resolution aerial images covering in the field area more than 50 ha. The purposes of this study is to develop the rice grain yield distribution using UAV. In order to develop a technology for estimating the rice yield using UAV images, time series UAV aerial images were taken at the paddy fields and the data were compared with the rice yield of the harvesting area for two rice varieties(Singdongjin, Dongjinchal). Correlations between the vegetation indices and rice yield were ranged from 0.8 to 0.95 in booting period. Accordingly, rice yield was estimated using UAV-derived vegetation indices($R^2=0.70$ in Sindongjin, $R^2=0.92$ in Donjinchal). It means that the rice yield estimation using UAV imagery can provide less cost and higher accuracy than other methods using combine with yield monitoring system and satellite imagery. In the future, it will be necessary to study a variety of information convergence and integration systems such as image, weather, and soil for efficient use of these information, along with research on preparing management practice work standards such as pest control and nutrient use based on UAV image information.

• Korean Journal of Environment and Ecology
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• v.29 no.6
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• pp.907-916
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• 2015

The purpose of this study was to identify characteristics of vegetation structure, vegetation succession, and species diversity of artificially planted Chamaecyparis obtusa (CO) stands. The study was carried out by performing vegetation survey for eight CO stands located in Jeollanam-do Province, Korea. Analysis on vegetation classification and ordinations of the stands was conducted using the data from the vegetation survey, and as a result, the stands were classified into five types of communities. Community I showed a considerably lower index of species diversity when compared to other communities because the canopy of the dominant CO was so highly dense that the low-height vegetation was not able to develop or the low-height vegetation almost disappeared due to elimination of weed trees. Meanwhile, the Community II - IV had relatively higher indices of species diversity because various native tree species mixed with the low-height vegetation and competed with each other in the understory and shrub layers to some degree of stability or in their early stage of vegetation development. Community V, lastly, showed higher use intensity as a recreational forest, thus developing simpler vegetation structure on account of artificial intervention. There was positive correlation between photosynthetically active radiation entering the forest floor, number of observed species and index of species diversity. Such characteristics of vegetation structure in CO stands are closely associated with forest management and prescription for planting reforestation, thinning, and brush cutting in the past. There was a slight difference in vegetation structure and species diversity by communities, based on rotation time of the vegetational succession, process of disturbance frequency and disturbance, development, and maturity by planting CO stands. However, when compared to natural forests, the CO stands showed simpler vegetation structure. Because artificial forests are vulnerable in ecosystem service with lower species diversity, a drive for ecological management is needed for such forests to change into healthy ecosystems that can display functions of public benefit.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.267-282
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• 2018

Despite the continuous development of phenology detection studies using satellite imagery, verification through comparison with the field observed data is insufficient. Especially, in the case of Korean forests patching in various forms, it is difficult to estimate the start of season (SOS) by using only satellite images due to resolution difference. To improve the accuracy of vegetation phenology estimation, this study reconstructed the large scaled forest type map (1:5,000) with MODIS pixel resolution and produced time series vegetation phenology curves from Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from MODIS images. Based on the field observed data, extraction methods for the vegetation indices and SOS for Korean forests were compared and evaluated. We also analyzed the correlation between the composition ratio of forest types in each pixel and phenology extraction from the vegetation indices. When we compared NDVI and EVI with the field observed SOS data from the Korea National Arboretum, EVI was more accurate for Korean forests, and the first derivative was most suitable for extracting SOS in the phenology curve from the vegetation index. When the eight pixels neighboring the pixels of 7 broadleaved trees with field SOS data (center pixel) were compared to field SOS, the forest types of the best pixels with the highest correlation with the field data were deciduous forest by 67.9%, coniferous forest by 14.3%, and mixed forest by 7.7%, and the mean coefficient of determination ($R^2$) was 0.64. The average national SOS extracted from MODIS EVI were DOY 112.9 in 2014 at the earliest and DOY 129.1 in 2010 at the latest, which is about 0.16 days faster since 2003. In future research, it is necessary to expand the analysis of deciduous and mixed forests' SOS into the extraction of coniferous forest's SOS in order to understand the various climate and geomorphic factors. As such, comprehensive study should be carried out considering the diversity of forest ecosystems in Korea.

• Journal of Korean Society of Forest Science
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• v.96 no.5
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• pp.591-601
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• 2007

Spatial information on forest biomass is an important factor to evaluate the capability of forest as a carbon sequestrator and is a core independent variable required to drive models which describe ecological processes such as carbon budget, hydrological budget, and energy flow. The objective of this study is to understand the relationship between satellite image and field data, and to quantitatively estimate and map the spatial distribution of forest biomass. Landsat Enhanced Thematic Mapper (ETM+) derived vegetation indices and field survey data were applied to estimate the biomass distribution of mountainous forest located in Gwangneung Experimental Forest (230 ha). Field survey data collected from the ground plots were used as the dependent variable, forest biomass, while satellite image reflectance data (Band 1~5 and Band 7), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and RVI (Ratio Vegetation Index) were used as the independent variables. The mean and total biomass of Gwangneung catchment area were estimated to be about 229.5 ton/ha and $52.8{\times}10^3$ tons respectively. Regression analysis revealed significant relationships between the measured biomass and Landsat derived variables in both of deciduous forest ($R^2=0.76$, P < 0.05) and coniferous forest ($R^2=0.75$, P < 0.05). However, there still exist many uncertainties in the estimation of forest ecosystem parameters based on vegetation remote sensing. Developing remote sensing techniques with adequate filed survey data over a long period are expected to increase the estimation accuracy of spatial information of the forest ecosystem.