• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1343-1356
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• 2022

Clouds or shadows are the most problematic when monitoring crops using optical satellite images. To reduce this effect, a composite algorithm was used to select the maximum Normalized Difference Vegetation Index (NDVI) for a certain period. This Maximum NDVI Composite (MNC) method reduces the influence of clouds, but since only the maximum NDVI value is used for a certain period, it is difficult to show the phenomenon immediately when the NDVI decreases. As a way to maintain the spectral information of crop as much as possible while minimizing the influence of clouds, a Score-Based Composite (SBC) algorithm was proposed, which is a method of selecting the most suitable pixels by defining various environmental factors and assigning scores to them when compositing. In this study, the Sentinel-2A/B Level 2A reflectance image and cloud, shadow, Aerosol Optical Thickness(AOT), obtainging date, sensor zenith angle provided as additional information were used for the SBC algorithm. As a result of applying the SBC algorithm with a 15-day and a monthly period for Dangjin rice fields and Taebaek highland cabbage fields in 2021, the 15-day period composited data showed faster detailed changes in NDVI than the monthly composited results, except for the rainy season affected by clouds. In certain images, a spatially heterogeneous part is seen due to partial date-by-date differences in the composited NDVI image, which is considered to be due to the inaccuracy of the cloud and shadow information used. In the future, we plan to improve the accuracy of input information and perform quantitative comparison with MNC-based composite algorithm.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.6
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• pp.1-12
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• 2006

Remote sensing cannot provide a direct measurement of vegetation index (VI) but it can provide a reasonably good estimate of vegetation index, defined as the ratio of satellite bands. The monitoring of vegetation in nearby urban regions is made difficult by the low spatial resolution and temporal resolution image captures. In this study, enhancing spatial resolution method is adapted as to improve a low spatial resolution. Recent studies have successfully estimated normalized difference vegetation index (NDVI) using improved resolution method such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra satellite. Image enhancing spatial resolution is an important tool in remote sensing, as many Earth observation satellites provide both high-resolution and low-resolution multi-spectral images. Examples of enhancement of a MODIS multi-spectral image and a MODIS NDVI image of Cheongju using a Landsat TM high-resolution multi-spectral image are presented. The results are compared with that of the IHS technique is presented for enhancing spatial resolution of multi-spectral bands using a higher resolution data set. To provide a continuous monitoring capability for NDVI, in situ measurements of NDVI from paddy field was carried out in 2004 for comparison with remotely sensed MODIS data. We compare and discuss NDVI estimates from MODIS sensors and in-situ spectroradiometer data over Ochang plain region. These results indicate that the MODIS NDVI is underestimated by approximately 50%.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.509-520
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• 2012

The objective of this study was to estimate rice yield in Korea using satellite and meteorological data such as sunshine hours or solar radiation, and rainfall. Terra and Aqua MODIS (The MOderate Resolution Imaging Spectroradiometer) products; MOD13 and MYD13 for NDVI and EVI, MOD15 and MYD15 for LAI, respectively from a NASA web site were used. Relations of NDVI, EVI, and LAI obtained in July and August from 2000 to 2011 with rice yield were investigated to find informative days for rice yield estimation. Weather data of rainfall and sunshine hours (climate data 1) or solar radiation (climate data 2) were selected to correlate rice yield. Aqua NDVI at DOY 233 was chosen to represent maximum vegetative growth of rice canopy. Sunshine hours and solar radiation during rice ripening stage were selected to represent climate condition. Multiple regression based on MODIS NDVI and sunshine hours or solar radiation were conducted to estimate rice yields in Korea. The results showed rice yield of $494.6kg\;10a^{-1}$ and $509.7kg\;10a^{-1}$ in 2011, respectively and the difference from statistics were $1.1kg\;10a^{-1}$ and $14.1kg\;10a^{-1}$, respectively. Rice yield distributions from 2002 to 2011 were presented to show spatial variability in the country.

• 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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• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.37-42
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• 2009

This study extracted Near Infrared (NIR) band using Image Processing Technology (IPT), and calculated Normalized Difference Vegetation Index (NDVI). Aerial photography from Daum portal in combination with high resolution satellite image was employed to improve vegetation sensitivity by extracting NIR band and calculating NDVI with comparison to QuickBird result. The extracted NIR band and NDVI through IPT presented similar distribution pattern. In addition, a regression analysis by land cover character showed high correlation paddy and forest Therefore, this approach could be acceptable to acquire vegetation environment information.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.1
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• pp.15-24
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• 2004

The purpose of this study is to estimate monthly evapotranspiration (ET) using normalized difference vegetation index (NDVI) obtained from NOAA-AVHRR data sets. Actual evapotranspiration was evaluated by the complementary relationship, and monthly NDVI was obtained by maximum value composite method from daily NDVI images in the Korean peninsula for the year 2001 The monthly actual ETs for each land cover were compared with the monthly NDVIs to determine relationships between actual ET and NDVI for each land cover category, There was a high correlation between monthly NDVI and monthly mean actual ET. This study presents an alternative approach for land surface evapotranspiration based on remote sensing techniques.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.670-672
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• 2003

The purpose of this study is to estimate monthly evapotranspiration (ET) using normalized difference vegetation index (NDVI) obtained from NOAA/AVHRR data sets. Actual evapotranspiration was evaluated by the complementary relationship (Morton, 1978, Brutsaert and Stricker, 1979), and monthly NDVI was obtained by maximum value composite method from daily NDVI images in the Korean peninsula for the year 2001. The monthly actual ETs for each land cover were compared with the monthly NDVIs to determine relationships between actual ET and NDVI for each land cover category. There was a high correlation between monthly NDVI and monthly averaged actual ET. This study presents an alternative approach for land surface evapotranspiration based on remote sensing techniques.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.35-45
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• 1999

The research is to examine urban heat island effects which is resulted from urbanization using thermal infrared band of Landsat TM data and to demonstrate heat island alleviation effects of green spaces through correlation analysis of NDVI(Normalized Difference Vegetation Index) and surface temperature. According to the results, forests which are covered with natural vegetation have a high NDVI digital values, but surface temperature is very low, and urban areas which is composed of artificial paving materials have a low NDVI, surface temperature increases gradually. In summary, the analysis of relationship between NDVI and surface temperature, used in this study, is regarded as one of effective methodologies for proving heat island alleviation effects of vegetation.