• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.394-406
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• 2004

A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ${\lambda}l\;and\;{\lambda}2$ were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher $r^2$ (>10\%)$ than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.111-115
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• 2009

본 연구에서는 SWAT 모형에서 모의된 토양수분의 신뢰성을 판단하기 위해 MODIS NDVI의 활용성을 파악하고자 하였다 MODIS 위성영상을 이용하여 시간해상도 16일, 공간해상도 250m의 NDVI를 추출하였으며, 대상유역은 면적이 약 $6661.3km_2$ 이고 그 중 산림이 약 82.2%를 차지하고 있는 충주댐 유역으로 하였다. 보다 신뢰성 있는 자료를 얻기 위해 토양, 토지이용 등 유역의 특성이 다른 상류와 하류로 나누어 다지점 검보정을 수행하였으며, 2003년부터 2006년까지의 유출 자료를 이용하여 모형을 보정하고, 2000, 2001 그리고 2002년에 대하여 검증하였다. 검보정 결과 모형 효율성 계수는 상류와 하류에 대하여 각각 0.91, 0.87, 결정계수는 각각 0.90, 0.80으로 분석되었다. 분석 기간은 2000년부터 2006년까지이고, NDVI의 특성에 따라 봄기간과 가을기간으로 나누어 분석하였으며, 선형회귀 방적식과 결정계수를 이용하여 상관성을 판단하였다. 분석결과 SWAT에서 모의된 토양수분과 MODTS NDVI는 약 55%의 상관성을 나타내었고, 가뭄해인 2001년에 약 85%로 상관성이 매우 높고, 비가 많이 온 해인 2002년에 약 2%로 상관성이 매우 낮아 NDVI는 가뭄 기간 SWAT에서 모의된 토양수분의 신뢰성을 검증할 수 있는 자료로 사용될 수 있다고 판단되었다.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.116-120
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• 2009

원격탐사 기술은 사람이 직접 방문하여 조사하기 힘든 극지라든가 농업환경에 대한 자료 요구도가 높으면서도 직접 수집이 어려운 비접근 지역에 대한 정보를 추출하는데 유용한 관측수단이다. 본 연구는 MODIS(Moderate Resolution Imaging Spectroradiometer) 제공 산출물 중 16일 단위로 작성되는 NDVI(Normalized Difference Vegetation Index, MOD13)를 이용하여 북한의 벼 수량을 추정하는 것을 목적으로 하였고, 그 가능성과 한계에 대하여 알아보았다. 2000년부터 2008년까지 촬영된 MODIS MOD13 자료를 미국 NASA로부터 제공받아 좌표체계를 우리나라에 맞게 투영하고 NDVI를 추출하여 자료분석에 사용하였다. 통계청에서 발표한 벼 수량 및 생산량 통계자료를 이용하였다. 농촌진흥청 국립농업과학원에서 작성한 북한의 토지피복분류도를 이용하여 서해안 평야지대에 위치한 논을 위도별로 네군데 정하여 관심지역(area of interest)으로 설정하였다. 이 관심지역에 대한 시계열 값을 추출하여 연중 연간 변화를 분석하고 2000년부터 2007년까지 수잉기의 NDVI 값을 이용하여 수량에 대한 상관계수(r)는 $0.77^*$로 5%에서 유의하여 NDVI 값에 따라 벼 수량에 큰 영향을 주는 것으로 나타났다. 수잉기의 NDVI 값과 벼 수량에 대해 회귀분석한 결과($R^2=0.591^*$), NDVI에 따른 벼 수량의 변이를 59.1% 설명할 수 있었다. 이와 같이 회귀식을 이용하여 2008년 북한의 벼 수량은 약 2.80 ton/ha로 추정되었다.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.25-38
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• 2016

With the increasing need for high temporal resolution satellite imagery for monitoring land surfaces, this study evaluated the temporal resolution of the NDVI composites from Geostationary Ocean Color Imager (GOCI) data. The GOCI is the first geostationary satellite sensor designed to provide continuous images over a $2,500{\times}2,500km^2$ area of the northeast Asian region with relatively high spatial resolution of 500 m. We used total 2,944 hourly images of the GOCI level 1B radiance data obtained during the one-year period from April 2011 to March 2012. A daily NDVI composite was produced by maximum value compositing of eight hourly images captured during day-time. Further NDVI composites were created with different compositing periods ranging from two to five days. The cloud coverage of each composite was estimated by the cloud detection method developed in study and then compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud product and 16-day NDVI composite. The GOCI NDVI composites showed much higher temporal resolution with less cloud coverage than the MODIS NDVI products. The average of cloud coverage for the five-day GOCI composites during the one year was only 2.5%, which is a significant improvement compared to the 8.9%~19.3% cloud coverage in the MODIS 16-day NDVI composites.

• Journal of the Korean GEO-environmental Society
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• v.9 no.6
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• pp.43-51
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• 2008

This study is to evaluate the NPP (Net Primary Production) distribution in the Geum River basin from NOAA/AVHRR satellite imagery data. It is supposed that the natural vegetation condition and the NPP has the linear relationship. The NPP from natural vegetation increases proportional to the annual net radiation (Rn), where radiative dryness index (RDI) is a proportional constant connecting net radiation 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. The purpose of this study is to propose a simple method to get NPP in the Geum river basin.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.83-89
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• 2012

Natural Vegetation cover, which is very important earth resource, has been significantly altered by humans in some manner. Since this has currently resulted in a significant effect on global climate, various studies on vegetation environment including forest have been performed and the results are utilized in policy decision making. Remotely sensed data can detect, identify and map vegetation cover change based on the analysis of spectral characteristics and thus are vigorously utilized for monitoring vegetation resources. Among various vegetation indices extracted from spectral reponses of remotely sensed data, NDVI is the most popular index which provides a measure of how much photosynthetically active vegetation is present in the scene. In this study, for change detection in vegetation cover, a Multi-layer Perceptron Network (MLPN) as a nonparametric approach has been designed and applied to MODIS/Aqua vegetation indices 16-day L3 global 250m SIN Grid(v005) (MYD13Q1) data. The feature vector for change detection is constructed with the direct NDVI diffenrence at a pixel as well as the differences in some subset of NDVI series data. The research covered 5 years (2006-20110) over Korean peninsular.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.981-996
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• 2018

In agriculture, remote sensing data using earth observation satellites have many advantages over other methods in terms of time, space, and efficiency. This study analyzed the changes of reflectance and vegetation index according to atmospheric correction of images before using satellite images in agriculture. Top OF Atmosphere (TOA) reflectance and surface reflectance through atmospheric correction were calculated to compare the reflectance of each band and Normalized Vegetation difference Index (NDVI). As a result, the NDVI observed from field measurement sensors and satellites showed a higher agreement and correlation than the TOA reflectance calculated from surface reflectance using atmospheric correction. Comparing NDVI before and after atmospheric correction for multi-temporal images, NDVI increased after atmospheric corrected in all images. garlic and onion cultivation area and forest where the vegetation health was high area NDVI increased more 0.1. Because the NIR images are included in the water vapor band, atmospheric correction is greatly affected. Therefore, atmospheric correction is a very important process for NDVI time-series analysis in applying image to agricultural field.

• 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.

• Proceedings of the KSRS Conference
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• 2005.10a
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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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.166-169
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• 2004

NDVI has been used to estimate several ecological variables including leaf area index (LAI). Global MODIS LAI data are partially produced by empirical model that is based on the assumption of high correlation between NDVI and LAI. This study attempts to evaluate the MODIS empirical model by comparing with the result obtained from field LAI measurement and Landsat ETM+ reflectance. MODIS LAI product and ancillary data were analyzed over a small forest watershed near the Seoul metropolitan area. The relationship between NDVI of ETM+ and field measured LAI did not correspond to MODIS LAI estimation. Since the study area is mostly covered by very dense and fully closed forest, the correlation between NDVI and LAI might not be high. Although MODIS LAI product has great potential for global environment studies, it needs to be cautious to use them in regional and local area in particular for the forest of dense canopy situation.