• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.685-689
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• 2002

This study focused the relationship between the Normalized Difference Vegetation Index (NDVI) and the evapotranspiration (ET) temporal changes. Especially, the interannual change of the NDVI and ET from 1982 to 2000 at regional to continental scales was highlighted mainly over Asia. Monthly global NDVI data were acquired from Pathfinder AVHRR Land (PAL) data (1$\times$1 degree resolution). The monthly ET was estimated from assimilated atmospheric data provided from National Centers for Environmental Prediction (NCEP) (2.5$\times$2.5 degree resolution), and gridded global precipitation data of CPC Merged Analysis of Precipitation (CMAP) (2.5$\times$2.5 degree resolution). Significant positive correlations were found between the NDVI and ET interannual changes in May and June over western Siberia. Moreover, it was revealed that the most of area in Asia has positive correlation coefficient in May and June. These results delineate that the vegetation activity significantly contributes to the ET interannual change over extensive areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.1
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• pp.97-110
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• 2021

Vegetation index information is an important figure that is used in many fields such as landscape architecture, urban planning, and environment. Vegetation may vary slightly in vegetation vitality depending on photosynthesis and chlorophyll content. In this study, a range of vegetation worth preserving in the Taehwa River water system was determined, and hyperspectral images of drones were acquired (August, October), and the results were presented through DVI(Normalized Defference Vegetation Index), EVI(Enhanced Vegetation Index), PRI(Photochemical Reflectance Index), ARI (Anthocyanin Reflectance Index) index analysis. In addition, field spectral data and VRS-GPS(Virtual Reference System-GPS) surveys were performed to ensure the quality and location accuracy of the spectral band. As a result of the analysis, NDVI and EVI showed low vegetation vitality in October, -0.165 and -0.085, respectively, and PRI and ARI increased to 0.011 and 7.588 in October, respectively. For general vegetation vitality, it was suggested that NDVI and EVI analysis were effectively performed, and PRI and ARI were thought to be effective in analyzing detailed characteristics of plants by spectral band. It is expected that it can be widely used for park design and landscape information modeling by using drone image information construction and vegetation information.

• Journal of Ecology and Environment
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• v.37 no.2
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• pp.53-60
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• 2014

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.78-81
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• 2003

The present study illustrates a method for monitoring the urban vegetation around Shaoxing city, Monitoring spatiotemporal changes in urban areas will become increasingly important as the number and proportion of urban residents continues to increase. The synoptic view of urban land cover provided by satellite and airborne sensors is an important complement to in situ measurements of physical, environmental and socioeconomic variables in urban settings. The results obtained have revealed a notable change in the vegetation cover in and around the City premises. In this study, we discussed methodology for measurement of urban vegetation and vegetation distributions based on band ratioing in Shaoxing city using Land sat TM imageries. A systematic analysis of the spatiotemporal dynamics of vegetation in urban areas is required to ensure a healthy sustainable environment.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.665-673
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• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.

• 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.

• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.335-357
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• 2014

This study aims at classifying and interpreting on the vegetation structure and the vegetation transition over 25 years (between 1986 and 2010), and the correlation with the change of some conditions (the vegetation height and coverage on each layer and the climate factors as WI, CI, mean annual temperature, mean annual total precipitation etc.) in the Evergreen Broad-Leaved Forest,, Hong-Do island. The EBLF is classified into five units of vegetation (Hedera rhombea-Machilus thunbergii community (M-M comm.), Castanopsis sieboldii forest (Machilus japonica-Castanopsis sieboldii community; Raphiolepis indica var. umbellata-C. sieboldii community), community (Qa comm.), Carpinus turczaninovii community (Ct comm.), Camellia japonica stand (Cj stand)). The vegetation transition by CCA had high correlation with the height and coverage on each layer and the climate factors, and it did the succession (transition) that the M-M comm. (2010) from Mallotus japonicus community Machilus thunbergii community Carpinus coreana community (Cc comm.) Aucuba japonica community (Aj comm.) Trachelos permum asiaticum var. intermedium-Quercus acuta community (TQ comm.) (1986), the communities of C. sieboldii forest (2010) from Aj comm. TQ comm. Raphiolepis umbellata-Camellia japonica community (RC comm.) (1986), the Qa comm. (2010) from Ardisia japonica-Castanopsis sieboldii community (AC comm.) and TQ comm. (1986), the Ct comm. (2010) from Cc comm. RC comm. Aj comm. Quercus serrata community and the Cj stand (2010) from AC comm. (1986). the height and coverage on each layer are also changed.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.16-22
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• 1999

The various spatial structure of biological habitat has tighten relationship with biodiversity. Due to increasing of population, development of agriculture and urban structure, various change of landscape has became these days. These change of landscape has raised the decrease of habitat and landscape fragmentation. This paper summarizes research to analysis vegetation index according to P/A ratio, Shape Index, and Fractal dimension using Landsat Thematic Mapper(TM). The analysis of landscape fragmentation using NDVI(Normalized Difference Vegetation Index) 0.5~1 has the most profitable for detection of vegetation fragmentation. The analysis of vegetation index of Seoul and Kyunggi province has also showed that Fractal dimension has the most fragmentation index. In near future, time series analysis is needed for fragmentation of vegetation on the same area, and for various landuse of fragmentation analysis. These researches were carried out for preservation strategy of vegetation and biodiversity.

• Journal of Korean Society on Water Environment
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• v.32 no.2
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• pp.135-141
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• 2016

This study investigated changes of hydrology, soil characteristics, riparian vegetation communities, and geomorphology in sandbars before and after sand-mining to determine the effect of sand-mining at upstream of Guemgang and Bochungcheon streams in Korea. Sand-mining events affected the mining area. They supplied organic matters and nutrients during flood. Sediment deposition caused soil texture change and expansion of vegetation area. However, riverbeds were stabilized after the disturbance. According to the analyses of aerial photographs, the vegetation area was significantly expanded in both dam-regulated streams and dam-unregulated streams after sand-mining. Willow shrubs advanced in disturbed area at an average of 10 years after sand-mining. It took willows trees 10.6 years to become dominant communities. Therefore, it took a total of 20.6 years for new riparian forest to form in sandbar after sand-mining. Our results confirmed that stream flow condition were dependent on vegetation recruitment in dam-regulated streams and dam-unregulated streams. For willow recruitment in unregulated streams, calculation of water level below dimensionless bed shear stress is important because low water level variation is a limiting factor of vegetation recruitment.