• 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 Wetlands Research
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• v.22 no.4
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• pp.275-285
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• 2020

In this study, after estimating VCI (Vegation Condition Index), TCI (Thermal Condition Index) and VHI (Vegetation Health Index) from the NDVI (Normalized Differentiation Vegetation Index) and LST (Land Surface Temperature) remotely sensed at major sites in Korea during the 2001-1919 period, the correlation between these indices and various drought indices is analyzed for the purpose of assessing the effects of ecological drought. The relative impact of VCI and TCI on vegetation health was found to vary by region. The effects of drought on vegetation in Korea's forest areas could be more clearly identified in TCI than in VCI. It is suggested that the revised VHI, reflecting the relative influence of VCI and TCI, can better explain the effects of drought on vegetation.

• Journal of the Korean GEO-environmental Society
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• v.15 no.10
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• pp.35-42
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• 2014

This study is to evaluate Net Primary Production (NPP) using NDVI calculated by MODIS in the Nakdong river basin. This study is based on the method of using the fact that NPP is proportional to natural vegetation condition. This method is different from existing one, using remote sensed data. It is known that NPP of natural vegetation is proportional to the absorbed amount of visible light that is proportional to NDVI. Therefore, estimating NPP by using NDVI is one of the most highly useful methods. This method can be used in a wide range of areas where vegetation data can not be obtained easily or where there is not enough meterological data. This study proposes the estimating method for NPP that is based upon NDVI, which is obtained by MODIS, and verifies by comparing the NPP with empirical results.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.71-81
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• 2007

One of the most important hydrologic components is evapotranspiration. It is a process by which water is evaporated from moist land surfaces and transpired into atmosphere by plants. There are many methods of estimating evapotranspiration rate and its potential such as the methods of soil-moisture sampling, lysimeter measurements, water balance, energy balance, groundwater fluctuations and evapotranspiration. But it is very difficult to estimate evapotranspiration in terms of regional discrete characteristics of topography and/or vegetation. The evapotranspiration is strongly affected by ground covering vegetation, and the degree of vegetation growth. In order to grasp vegetation condition over a vast study area, NDVI (Normalized Difference Vegetation Indices) calculated from the data obtained from NOAA/AVHRR were utilized. Through multi-regression analysis, we developed a model equation to estimate the evapotranspiration using NDVIs and temperature data.

• KCID journal
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• v.9 no.1
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• pp.29-37
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• 2002

Rapid environmental changes result in not only damage to agricultural produce but also the poor growth and death of plants. Remote Sensing (RS) is one of effective methods for collecting, analyzing information and predicting the change of agricultural env

• 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 Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.9-17
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• 2014

The Vegetation cover is a significant factor to comprehend characteristics of the ground surface for meterological and hydrological models, which measure energy in the atmosphere or predict the runoff of ground surface. Deardorff introduced vegetation cover fraction to quantitatively comprehend the vegetation cover in 1978. After Deardorff, most of previous researches were conducted on low-resolution or high-resolution images, but only few researches on Landsat that are in medium-resolution images. Therefore, this study aims to investigate a way of calculating the vegetation cover fraction by using NDVI of Landsat images, which were hardly handled previously. For accurate vegetation cover fraction, we compared the evaluated parameters from this study with past vegetation cover fraction parameters that have been calculated for using NDVI of Landsat OLI images. The result of research was shown that NDVI is quite correlated with the vegetation fraction cover in the previous researches. In fact, RMSE of vegetation cover fraction values that obtained through the suggested parameters on this study showed the highest accuracy of 7.3% among all the cases.

• 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.

• Journal of Conservation Science
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• v.31 no.4
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• pp.395-402
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• 2015

This study was considered utilization of hyperspectral image analysis for monitoring. Accordingly we applied to stone cultural properties to data correction methods, image classification techniques, NDVI computation techniques using hyperspectral image. As the results, hyperspectral image analysis was possible making detailed deterioration map, accurate calculation of deterioration rate, mapping of normalized difference vegetation index on the basis of reflectance of each materials. Therefore, hyperspectral image analysis will be used for effective monitoring techniques of stone cultural heritages.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.363-372
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• 2006

Many methods have been used to estimate evapotranspiration. However, there is little information about the evapotranspiration from river basins with complicated topographies and variable land use. Remote sensing technique is a probable means to estimate distribution of the evapotranspiration in connection with regional characteristics of vegetation and landuse. The evapotranspiration not only depends on meteorological circumstances but also on the condition of the vegetation. The latter effect can be expressed in terms of NDVI(Normalized Difference Vegetation Index) obtained by NOAA/AVHRR datasets. In this paper, a simple method to estimate evapotranspiration of the Keum river basin is proposed based on NDVI and temperature data.