• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.27-41
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• 2017

The purpose of this study is to diagnose the possibility of future drought expression by late March dryness in rice paddy areas using Terra MODIS NDVI (Normalized Difference Vegetation Index). We tested the degree of dryness by comparing the 2000-2015 average NDVI with yearly NDVI, which we name DCI (Dry Condition Index). The 16-day interval DCIs from March 6 to May 25 were evaluated with spatio-temporal expression of South Korea. In particular, we find that the DCI for April 7 (March 23 to April 7) offered reasonable prediction of paddy dryness during drought years. The April 7 DCI value for dry conditions ranged from 0.04 to 0.08 while the DCI for normal conditions ranged from -0.04 to 0.01. The DCI can be one of the indicators used to evaluate the dryness of rice paddy areas at the beginning of the spring season.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.80-86
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• 2014

In this study, we the estimated surface normalized difference vegetation index by using the KOrea Multi-Purpose SATellite-3 (KOMPSAT-3) multi-spectral images for comparative analysis. The estimated NDVI from KOMPSAT-3 is used as for comparison with the high resolution GeoEye products. The geometry conditions for atmospheric effects are selected from meta files of KOMPSAT-3 bundle data. The used geometry conditions are consist of solar zenith angle, solar azimuth angle, viewing zenith angle, viewing azimuth angle, and date. And, Atmospheric effects such as attenuation, scattering and absorption were physically simulated from water vapor, ozone and aerosol information. Generally, although ground measurements are important for accurate information, in this study, MODIS atmospheric products are used as atmospheric constituents. The surface reflectance from radiative transfer model is utilized for estimating vegetation index. The present study, to reduce atmospheric and geometry conditions between KOMPSAT-3 and GeoEye having difference observation characteristics, data acquisition time is carefully determined for reliable vegetation spectral characteristics.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.2
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• pp.92-103
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• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal 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.31 no.1
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• pp.11-20
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• 2015

This study aimed to investigate the canopy growth conditions and the accuracy of phenological stages of paddy rice using ground-based remote sensing data. Plant growth variables including Leaf Area Index (LAI) and canopy reflectance of paddy rice were measured at the experimental fields of Chonnam National University, Gwangju, Republic of Korea during the crop seasons of 2011, 2012, and 2013. LAI values were also determined based on correlations with Vegetation Indices (VIs) obtained from the canopy reflectance. Three phenological stages (tillering, booting, and grain filling) of paddy rice could be identified using VIs and a spatial index (NIR versus red). We found that exponential relationships could be applied between LAI and the VIs of interest. This information, as well as the relationships between LAI and VIs obtained in the present study, could be used to estimate and monitor the relative growth and development of rice canopies during the growing season.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.429-432
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• 1999

Vegetation cover classification is examined based on a time series NOAA/AVHRR data. Time series data analysis methods including Fourier transform, Auto-Regressive (AR) model and temporal signature similarity matching are developed to extract phenological features of vegetation from a time series NDVI data from NOAA/AVHRR and to classify vegetation types. In the Fourier transform method, typical three spectral components expressing the phenological features of vegetation are selected for classification, and also in the AR model method AR coefficients are selected. In the temporal signature similarity matching method a new index evaluating the similarity of temporal pattern of the NDVI is introduced for classification.

• The Korean Journal of Ecology
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• v.10 no.1
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• pp.33-42
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• 1987

The forest vegetation of Mt. Chil-gab was studied from 1983 to 1984. By Z-M method, the actual vegetation was classified into 8 communities and 1 plantation; Quercus variabilis, Q. variabilis-Styrax obassia, Q variabilis-Q. dentata, Q. varisbilid-Q. mongolica, Q. acutissima-Q. variabilis, Zelkova serrata-Styrax japonica, Capinus laxiflora, Pinus densiflora community and Larix leptolepts plantation (on the mountain foot) community. The plant communities of Q. variabilis and S. japonica as edaphic climax, in terms of the isopleth line of warmth index. Based on the data of vegetation survey and environmental analysis, the actual vegetation map and potential natural vegetation map were perpared with scale of 1/25, 000.

• Spatial Information Research
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• v.23 no.6
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• pp.31-41
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• 2015

This research is primarily intended to explore a novel way to monitor desiccation of inland wetland by combining MNDWI (Modified Normalized Difference Water Index) and NDVI (Normalized Difference Vegetation Index). The changes for vegetation and water condition on Upo Wetland located at southeastern Korea were investigated by MNDWI and NDVI derived from 2002, 2010 and 2015 Landsat data. The integrated use of MNDWI and NDVI made it possible to identify area-wide vegetation cover changes and to assess water storage changes on multi-annual time scales simultaneously. Comparing MNDWI with NDVI reveals the quantitative evidences for anthropogenic and environmental influences (such as road, building, water) causing an accelerated wetland desiccation. In fact, our monitoring approach raises critical issues regarding the hydrological cycle and its inter-annual changes for inland wetland under threat of drying up and highlights the important role of MNDWI and NDVI integration for any urgent or long-term treatment plan. This research presents scientific and objective evidences to support integrated approach of NDVI and MNDWI in exploring drying up trends of wetlands.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.709-720
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• 2017

In this study, we tried to analyze the correlation between corn yield and, satellite-based vegetation index, NDVI (Normalized Difference Vegetation Index) and various climatic factors in the three provinces of Northeast China during the past 20 years (1996-2015). The corn yields in the corn cultivation area of all three provinces showed a statistically significant positive correlation with the NDVI of the harvest period. Also, these have significant negative correlation with the daily maximum temperature in August and September and the occurrence frequency of above $30^{\circ}C$ for the summer season. The correlation between the corn yields and the precipitation showed a significant positive coefficient in only Liaoning Province in July, but the correlation was not found in Jilin and Heilongjiang Provinces. In this study, the NDVI and the daily maximum temperature data are suitable to be used as predictors of corn yield in the three provinces of Northeast China provinces.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.845-853
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• 2015

The objective of this study was to predict the timing of nitrogen (N) demand through analyzing chlorophyll fluorescence (ChlF), soil-plant analysis development (SPAD), and normalized difference vegetation index (NDVI), which are positively correlated with foliar N concentration in star cluster (Pentas lanceolata). The plants were grown in potting soil under optimal conditions for 30 d, followed by weekly irrigation with five concentrations (0, 4, 8, 16, and 24 mM) of N for an additional 30 d. These five N application levels corresponded to leaf N concentrations of 2.62, 3.48, 4.00, 4.23, and 4.69%, respectively. We measured 13 morphological and physiological parameters, as well as the responses of these parameters to various N-fertilizer treatments. The general increases in Dickson's quality index (DQI), above-ground dry weight (DW), total DW, flowering rate, ${\Delta}F/Fm$', and qP in response to treatment with 0 to 8 mM N were similar to those of SPAD, NDVI, and Fv/Fm. Consistent and strong correlations ($R^2$= 0.60 to 0.85) were observed between leaf N concentration (%) and SPAD, NDVI, ${\Delta}F/Fm$', and above-ground DW. Validation of leaf S PAD, NDVI, and ${\Delta}F/Fm$' revealed that these vegetation indices are accurate predictors of leaf N concentration that can be used for non-destructive estimation of the proper timing for N-solution irrigation of P. lanceolata. Moreover, irrigation with 8 mM N-fertilizer i s recommended w hen leaf N concentration, SPAD, NVDI, and ${\Delta}F/Fm$' ratios are reduced from their saturation values of 4.00, 50.68, 0.64, and 0.137%, respectively.