• Journal of Ginseng Research
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• 제45권4호
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• pp.527-534
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• 2021

Background: Phenological studies are a prerequisite for accomplishing higher productivity and better crop quality in cultivated plants. However, there are no phenological studies on Panax ginseng that improve its production yield. This study aims to redefine the phenological growth stages of P. ginseng based on the existing Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale and proposes a disease control reference. Methods: This study was conducted at the Korea Ginseng Corporation Experiment Station in Gyeonggi province, South Korea. Phenological observations were performed once weekly or twice monthly, based on the developmental stages. The existing BBCH scale with a three-digit code was used to redefine and update P. ginseng's phenological growth codes. Results: The phenological description is divided into eight principal growth stages: three for vegetative growth (perennating bud, aerial shoot, and root development), four for reproductive growth (reproductive organ development, flowering, fruit development, and fruit maturation), and one for senescence according to the extended BBCH scale. A total of 58 secondary growth stages were described within the eight principal growth stages. Under each secondary growth stage, four mesostages are also taken into account, which contains the distinct patterns of the phenological characteristics in ginseng varieties and the process of transplanting seedlings. A practical management program for disease control was also proposed by using the BBCH code and the phenological data proposed in this work. Conclusion: The study introduces an extended BBCH scale for the phenological research of P. ginseng.

• 대한원격탐사학회지
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• 제37권4호
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• pp.789-802
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• 2021

Synthetic Aperture Radar (SAR) at C-band is an ideal remote sensing system for crop monitoring owing to its short wavelength, which interacts with the upper parts of the crop canopy. This study evaluated the potential of dual polarimetric Sentinel-1 at C-band for monitoring rice phenology. Rice phenological variations occur in a short period. Hence, the short revisit time of Sentinel-1 SAR system can facilitate the tracking of short-term temporal morphological variations in rice crop growth. The sensitivity of SAR backscattering coefficients, backscattering ratio, and polarimetric decomposition parameters on rice phenological stages were investigated through a time-series analysis of 33 Sentinel-1 Single Look Complex images collected from 10th April to 25th October 2020 in Gimhae, South Korea. Based on the observed temporal variations in SAR parameters, we could identify and distinguish the phenological stages of the Gimhae rice growth cycle. The backscattering coefficient in VH polarisation and polarimetric decomposition parameters showed high sensitivity to rice growth. However, amongst SAR parameters estimated in this study, the VH backscattering coefficient realistically identifies all phenological stages, and its temporal variation patterns are preserved in both Sentinel-1A (S1A) and Sentinel-1B (S1B). Polarimetric decomposition parameters exhibited some offsets in successive acquisitions from S1A and S1B. Further studies with data collected from various incidence angles are crucial to determine the impact of different incidence angles on polarimetric decomposition parameters in rice paddy fields.

• 대기
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• 제19권2호
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• Journal of Ecology and Environment
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• 제34권2호
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• pp.149-156
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• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• Journal of Plant Biology
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• 제26권2호
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• pp.101-117
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• 1983

The phenological phenomena in terms of year day index (YDI) in South Korea were studied. The YDI was proposed here, because the remainer index such as Nuttonson's index is unadequate for the interpretation on the phenological phenomena of early spring season in sourthern coastal area. The YDI was calculated by summing daily mean temperature of the year days (YD) above physical zero degree in centigrade, based on the data of the Monthly Weather Reports from 1967 to 1980 by the Central Meteorological Office. The pattern of YDI increase with the increase of YD was similar to that of the remainder index such as the Nuttonson's index. The some YDI distribution maps were made by Yim and Kira (1975), dividing into 30'$\times$40' meshes, in latitude and longtude, on the topographical map(1 : 500,000) of the Korea Peninsula. According to the year day of different localities flowering dates of Prunus yedoensis and other phenological phenomena in various species delayed about 3.5 day as the increase of 1 degree of latitude, which coincides with the Hopkins bioclimatic law. It was found that the YDI is useful to interprete the phenology of plant and animal species and to select the optimum range of cultivars in South Korea.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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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.

• 한국응용곤충학회지
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• 제21권4호
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• pp.200-206
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• 1982

Distributed Time Delay의 개념을 응용하여 이화명나방의 발생시기를 예측할 수 있는 Phenological System Model을 구성하고 이의 타당성검정을 위해 기존 병해충발생예찰자료 및 일별 기상관측자료를 이용하여 본 해충의 1세대 경과에 소요되는 유효적산온도(DEL)와 Delay의 차수 K치를 산출한 후 이화명나방의 누적우화율곡선을 전자계산기로 Simulation 하였다. 그 결과 Model에 의해 추정된 1978년의 6개 선정지점의 누적우화율곡선은 실측 누적유살수비율곡선과 매우 유사하였으나 우화 초기 및 후기에 다소 편재하는 경향이 있었다. 한편 실측 $50\%$ 유살일과 Model에 의해 추정된 $50\%$ 우화일 간에는 수원에서 6일, 춘천에서 $5\~6$일의 차이를 보였으나 이리, 대구, 보성 및 밀양지역에서는 $2\~3$일의 근소한 차이를 보였다. 이화명나방의 Phenological Simulation Model은 각 발육단계별 실측밀도조사자료와 월동후 유충집단의 발육 및 일령분포, 그리고 사망요인에 대한 고려 등이 연구 보완되어지므로 더욱 확장된 System으로서 구성되어 질 것으로 생각된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.18-21
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• 2005

The impact of the interannual climatic variability on the vegetation sensitively appears in the timing of phenological events such as green-up, mature, and senescence. Therefore, an accurate and temporally high-resolution NDVI dataset will be required for analysis on the interannual variability of the climate-vegetation relationship. We constructed a daily 8km NDVI dataset over Eurasia based on the 8km tiled data of Pathfinder A VHRR Land (PAL) Global daily product. Cloud contamination was successfully reduced by Temporal Window Operation (TWO), which is a method to find optimized upper envelop line of the NDVI seasonal change. Based on the daily NDVI time series from 1982 to 2000, an accurate (daily) interannual change of the phenological events will be analyzed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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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.

• 한국지역지리학회지
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• 제15권3호
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• pp.337-350
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• 2009

식물계절 시기의 변화는 지역의 기후변화를 파악하는 데 중요한 지표이며, 지구온난화로 인한 기온상승의 영향이 뚜렷하게 반영된다. 본 연구에서는 식물계절 관측 자료를 이용하여 식물계절 시기의 변화 경향 및 식물계절 시기의 변화와 기온변화의 관계를 분석하였다. 봄철의 발아와 개화시기는 -0.7${\sim}$-2.7일/10년의 변화율로 앞당겨지는 경향인 반면 가을철 단풍절정시기는 3.7${\sim}$4.2일/10년의 변화율로 늦어지는 추세이다. 한반도의 봄철 식물계절 시기는 2월에서 3월 평균기온과 높은 상관관계가 있으며, 2월에서 3월 동안의 평균기온이 $1^{\circ}C$ 상승함에 따라 봄철 식물계절은 3.8일씩 앞당겨지는 경향이다. 가을철 식물계절 시기는 10월 평균기온과 상관관계가 높고 10월 평균기온이 $1^{\circ}C$ 상승함에 따라 3.1일씩 늦어지는 추세이다.