• Journal of the Korean Geographical Society
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• v.9
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• pp.67-75
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• 1974

The vegetation activity of the Korean peninsula has been monitored temporal variations through a satellite remote sensing and the vegetation index was used to set up the vegetation data map of Korea. The AVHRR data sent by the NOAA-14 satellite was collected for 8 months between April and November, 1997 to calculate the normalized difference vegetation index(NDVI) which was combined the MVC(Maximum Value Composite). Then this NDVI composite map was prepared to review the temporal variations in the vegetation activity. The NDVI has been subject to the unsupervised classification for the growing season between May and October. And the vegetation type is divided into five classes ; urban, bare soil, grass, farming land, deciduous forest and coniferous forest. The unsupervised classificaion of vegetation distribution in the Korean Peninsula shows that the urban and bare soil take 4.14% of total national area, grass 4.49%, farming land 27.54%, deciduous forest 25.61% and coniferous forest 38.22%.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.2
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• pp.7-14
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• 2009

The purpose of this study is to identify how much the MODIS NDVI (Normalized Difference Vegetation Index) can explain the forest soil moisture simulated from SWAT (Soil and Water Assessment Tool) model. For ChungjuDam watershed ($6,661.3\;km^2$) which covers 82.2% of forest, the SWAT model was calibrated for four years (2003-2006) at two locations of the watershed using daily streamflow data and was verified for three years (2000-2002) with average Nash and Sutcliffe model efficiencies of 0.69 and 0.75 respectively. For the period from March to June, the average spatial correlation between 16 days composite MODIS NDVI and the corresponding SWAT forest soil moisture was 0.90. The two variables averaged for each data set during that period showed an inverse relation with the average coefficient of determination of 0.55.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.10-12
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• 2003

This study was to monitor changes of leaf area index (LAI) and normalized difference vegetation index (NDVI), calculated from ground-based remotely sensed high resolution reflectance spectra, during rice (Oryza sativa L. cv. TNG 67) growth so as to determine their relationships and the optimum time period to use these parameters for yield prediction. Field experiments were conducted at the experimental farm of TARI to obtain various scales of grain yield and values of LAI and NDVI in the first and the second cropping seasons of 2001-2002. It was found that LAI and NDVI can be mutually estimated through an exponential relationship, and hence plant growth information and spectral remote sensing data become complementary counterparts through this linkage. Correlation between yield and LAI was best fitted to a nonlinear function since about 7 weeks after transplanting (WAT). The accumulated and the mean values of LAI from 15 days before heading (DBH) to 15 days after heading (DAH) were the optimum time period to predict rice yield for First Crops, while values calculated from 15 DBH to 10 DAH were the optimal timing for Second Crops.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.119-121
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• 2012

수문순환과정의 시공간적 거동의 해석 및 정량화는 효율적인 수자원 관리 및 계획을 위해서 반드시 선행되어야 하는 연구이다. 그러나 현재 국내의 수문순환과정을 분석하는 연구는 매우 미비한 실정이다. 특히 수문기상인자 중 토양수분은 지표와 대기에서 물과 에너지를 연결해주는 중요한 인자중 하나로 그 중요성 대두되고 있지만 관측시설의 제한과 큰 시공간 변동성을 가지고 있을 값을 추정하는데 어려움이 있다. 최근에는 이를 보완하기 위하여 선진국을 중심으로 연구되고 있는 원격탐사 기술을 도입하였다. 특히 원격탐사를 통해 산정된 Normilized Difference vegetation Index (NDVI) 와 토양수분과의 관계를 파악하기 위한 많은 연구들이 진행되어 왔다. NDVI는 토양수분에 직, 간접적인 영향을 주는 식생의 활동을 나타내는 인자이다. 이러한 이유로 많은 연구에서 NDVI와 토양수분과의 관계에 대해 규명해 왔으며, NDVI를 통한 토양수분의 추정 및 검증이 이루어졌다. 본 연구에서는 Moderate Resolution Imaging Spectroradiometer (MODIS) 에서 산정된 식생지수와 토양수분의 실측데이터를 이용하여 관측지에서의 식생지수와 토양수분의 관계를 규명한 후, 이 관계를 이용하여 관측 지역 이외의 장소의 토양수분 값을 추정 할 것이다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.582-584
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• 2003

This paper explores two such indexes----the Aerosol Free Vegetation Index (AFRI) and the Atmospherically Resistant Vegetation Index (ARVI). Comparisons were made with the NDVI (normalized vegetation index) to see if they indeed performed better. In general, the results showed that the AFRI and ARVI (with gamma=1) did indeed perform better than their NDVI counterpart study with the related channels were employed.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.162-168
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• 2007

기후변화는 강수유형, 기온상승과 일사량의 변화로 인한 증발산량의 변화, 유역 식생피복변화로 인한 지표-대기 관계의 변화와 같은 현상을 통해 지역 부존 수자원과 유출량에 큰 변화를 가져올 수 있다. 특히 지표면의 76%를 차지하고 있는 식생피복은 지표와 대기 사이의 물 순환과정에서 중요한 인자이다. 본 연구에서는 넓은 지역에 대한 식생피복의 파악이 용이한 NOAA 위성의 AVHRR (Advanced Very High Resolution Radiometer) 센서로부터 얻을 수 있는 정규화 식생지수 (Normalized Difference Vegetation Index, NDVI)를 통하여 현 식생정보를 정량화하였다. 이로부터 토지피복별 NDVI와 기상인자(기온, 강수량, 일조시간, 풍속, 습도) 사이의 상관관계를 분석하고, 이를 기후변화 시나리오에 의한 기상인자로 부터 토지피복에 따른 미래 NDVI를 추정하였다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.552-555
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• 2007

In this study, the MODIS NDVI for the period of $2000{\sim}2007$ was collected and processed to obtain VCI and SVI which are the quantitative indexes of drought. The VCI and SVI based on NDVI can be used for understanding seasonal pattern of vegetation, drought identification and quantitative analysis of drought. VCI and SVI compared with monthly precipitation ratio to average, Standardized Precipitation Index(SPI), and etc., which are used to identify spring drought, to analyze drought region, similarity and difference in drought severity. In addition, frequency of Spring droughts were calculated for the period of $2000{\sim}2007$, and the usability of the MODIS images as a tool for establishing countermeasures against drought was presented by analyzing drought frequently areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1300-1304
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• 2004

This study is to present a method of flood damaged area detection by the typhoon RUSA (August 31 - September 1, 2002) using Landsat 7 ETM+ and Landsat 5 TM images. Two images of Sept. 29, 2000 and Sept. 11, 2002 (path 115, row 34) were prepared for Gangreung, To identify the damaged areas, firstly, the NDVI (Normalized Difference Vegetation Index) of each image was computed, secondly, the NDVI values were reclassified as two categories that the negative index values including zero are the one and the positive index values are the other, thirdly the reclassified image before typhoon is subtracted from the reclassified image after typhoon to get DNDVI (Differential NDVI). Some part of urban and agricultural were classified into damaged area due to typhoon RUSA in Gangreung, $18.8km^2$ and $17.7km^2$ respectively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1033-1035
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• 2003

This study attempts to analyze the potential of global scale NDVI data archive to monitor regional scale droughts. Ten-days maximum value NDVI composite data of the northeast Asia region were acquired for the growing seasons from 1993 to 2003. Two NDVI-derived drought indices (SVI, VCI), reported from previous studies, were applied to the study area. Although the SVI and VCI are mainly developed for monitoring the drought condition at the agriculture crop and grasslands, it turned out that they were also effective to reveal the drought condition over the temperate mixed forest. The drought symptom lasts at least one or two months even after the normal raining begins.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.3-11
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• 2016

Sixty four percent of Korean territory consists of forest which is fragile for forest fire. However, it is difficult to detect the disaster-induced damages due to topographic complexity in mountainous areas and harsh weather conditions. For this reason, satellite imaging systems have been widely utilized to detect the damage caused by forest fire. In particular, ground vegetation condition can be estimated from multi-spectral satellite images and change detection technique has been used to detect forest fire damages. However, since Korea has clear four seasons, simple change detection technique has limitation. In this regard, this study applied the NDVI(normalized difference vegetation index) annual cycle modeling technique on time-series of Landsat images from 1991 to 2007 to analyze influence of forest fire of Yangyang-gun, Gangwon-do in 2005 on vegetation condition. The encouraging result was obtained when comparing the areas where forest fire occurs with non-damaged areas. The mean value of NDVI was decreased by 0.07 before and after the forest fire. On the other hand, annual variability of NDVI had been increasing and peak value of NDVI was stationary after the forest fire. It is interpreted that understory vegetation was seriously damaged from the forest fire occurred in 2005.