• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.405-407
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• 2003

An attempt has been in this study to delineate the characteristics of spectral signatures of the vegetation in terms of various VIs, particularly made the Normalized Difference Vegetation Index(NDVI), Modified Soil Adjusted Vegetation Index2(MSAVI2) and Enhanced Vegetation Index(EVI). Multitemporal SPOT-4 VEGETATION data from 1998 to 2002 have been used for the analysis. They have been compared with each other for their similarities and differences. The correlations between the vegetation indices observed at various degree of vegetation coverage during their different stages of growth were examined. All of the VIs have shown qualitative relationships to variations in vegetation. Apparently, the NDVI and MSAVI2 are highly correlated for all of the temporal changes, representing the different stages of phenology.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.224-227
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• 2008

Land cover and its changes, affecting multiple aspects of the environmental system such as energy balance, biogeochemical cycles, hydrological cycles and the climate system, are regarded as critical elements in global change studies. Especially in arid and semiarid regions, the observation of ecosystem that is sensitive to climate change can improve an understanding of the relationships between climate and ecosystem dynamics. The purpose of this research is analyzing the ecosystem surrounding the Gobi desert in North Asia quantitatively as well as qualitatively more concretely. We used Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION (VGT) sensor during 1999${\sim}$2007. Ecosystem monitoring of this area is necessary because it is a hot spot in global environment change. This study will allow predicting areas, which are prone to the rapid environmental change. Eight classes were classified and compare with MODerate resolution Imaging Spectrometer (MODIS) global land cover. The time-series analysis was carried out for these 8 classes. Class-1 and -2 have least amplitude variation with low NDVI as barren areas, while other vegetated classes increase in May and decrease in October (maximum value occurs in July and August). Although the several classes have the similar features of NDVI time-series, we detected a slight difference of inter-annual variation among these classes.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.199-209
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• 2006

The Global Land Cover 2000 (GLC 200) project, as a most recent issue, is to provide for the year 2000 a harmonized land cover database over the whole globe. The classifications were performed according to continental or regional scales by corresponding organization using the data of VEGETATION sensor onboard the SPOT4 Satellite. Even if the global land cover classification for Asia provided by Chiba University showed a good accuracy in whole Asian area, some problems were detected in Korean region. Therefore, the construction of new land cover database over Korea is strongly required using more recent data set. The present study focuses on the development of a new upgraded land cover map at 1 km resolution over Korea considering the widely used K-means clustering, which is one of unsupervised classification technique using distance function for land surface pattern classification, and the principal components transformation. It is based on data sets from the Earth observing system SPOT4/VEGETATION. Newly classified land cover was compared with GLC 2000 for Korean peninsula to access how well classification performed using confusion matrix.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.153-159
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• 2011

Vegetative land cover is an important variable many Earth system process, general circulation and carbon exchange model requires vegetative cover as boundary layer necessary to run model. The purpose of this study is to detect and to understand land surface change. To monitor changes of East Asia vegetation, we used NDVI 10-day MVC data derived from SPOT VEGETATION during 12 years from 1999 to 2010. Finally, according to the land cover of classified class, we performed analysis for dynamic zone(positive change zone and negative change zone), static zone in 1999, 2010. Therefore, land covers corresponding to each class have appeared change by 2010. Land cover change was confirmed by analyzing data during 12 years which appeared vegetation change of surrounding the actual desert area to east.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.165-167
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• 2003

To evaluate the thermal and water stress of vegetation canopy in Southern Qu$\'{e}$bec, leaf water status was evaluated from vegetation indices derived from SPOT VEGETATION images and surface temperature from NOAA AVHRR images. This study was conducted by investigating vegetation conditions for two different periods, from June to August, 1999 and 2000. The vegetation indices were integrated for the evaluating vegetation conditions as a new index, normalized moisture index (NMI). A trapezoid was defined by the NMI and surface temperature, and the thermal and water status of the vegetation canopy was determined according to separate small sections within the trapezoid.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.760-762
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• 2003

This study confirmed the usefulness of short-wavelength infrared (SWIR) in the discrimination and classification of evergreen forest types. A forested area near Hisayama and Sasaguri in Fukuoka Prefecture, Japan, served as the study area. Warm-temperate forest vegetation dominates the study site vegetation. Coniferous plantation forest, natural broad-leaved forest, and bamboo forest were analyzed using LANDSAT5/TM and SPOT4/HRVIR remote sensing data. Samples were extracted for the three forest types, and reflectance factors were compared for each band. Kappa coefficients of various band combinations were also compared by classification accuracy. For the LANDSAT5/TM data observed in April, October, and November, Bands 5 and 7 showed significant differences between bamboo, broad-leaved, and coniferous forests. The same significant difference was not recognized in the visible or near-infrared regions. Classification accuracy, determined by supervised classification, indicated distinct improvements in band combinations with SWIR, as compared to those without SWIR. Similar results were found for both LANDSAT5/TM and SPOT4/HRVIR data. This study identified obvious advantages in using SWIR data in forest-type discrimination and classification.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.17-24
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• 2011

Global warming and climatic changes due to human activities impact on marine and terrestrial ecosystems, which feedbacks to climate system. These negative feedbacks amplify or accelerate again global climate change. In particular, it is important to analyze vegetation change. This study attempts to analyze quantitatively vegetation change in Korea peninsula by using harmonic analysis. Harmonic-Analysis based on Fourier Transform is the method to effectively demonstrate for time series data. Especially, Harmonic-Analysis is very suitable method to analyze vegetation change because the vegetation repeats the cycle growth and extinction every year. The result of harmonic-analysis shows vegetation change as time passes. In this study, SPOTNEGETATION S10 MVC NDVI data was used during last 10 years (1999-2008) in Korea Peninsula. Also, land type classification used MODIS Land Cover Map data. The study estimated that phase values moved up approximately 0.5 day per year in cropland and 0.8 day per year in forest.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.582-594
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• 2012

A simple ecohydorlogic model that simulates hydrologic components and vegetation dynamics simultaneously based on equations of soil water dynamics and vegetation's growth and mortality is discussed. In order to simulate ungauged watersheds, the proposed model is calibrated with indirected estimated observation data set; 1) empirically estimated annual vaporization, 2) monthly surface runoff estimated by NRCS-CN method, and 3) vegetation fraction estimated by SPOT/VEGETATION NDVI. In order to check whether the model is performed well with indirectly estimated data or not, four upper dam watersheds (Andong, Habcheon, Namgang, Milyang) in Nakdong River watershed are selected, and the model is verified.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.952-954
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• 2003

In this paper, we present the different characteristics of NDVI fluctuation pattern between irrigated and non-irrigated area in Suphanburi province, in Central Thailand. For non-irrigated rice cultivation area, there is a strong correlation between NDVI fluctuation and peak rainfall, while there is a lower correlation with irrigated area. In this study, the 'peak detector' classifier was developed to identify the area of non-irrigated and irrigated cropping and its cropping intensity (number of crops per year). This classifier was created based on cropping characteristics such as number of crops, time or planting period of each crop and its relationship with the peak of rainfall. The classified result showed good accuracy in identification irrigated and nonirrigated rice cultivation areas.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.965-967
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• 2003

Information on forest volume, forest coverage and biomass are important for developing global perspectives about CO$_{2}$ concentration changes. Forest biomass cannot be directly measured from space yet, but remotely sensed greenness can be used to estimate biomass on decadal and longer time scales in regions of distinct seasonality, as in the north. Hence, in this research, numerical methods were used to estimate forest biomass in higher northern regions. A regression model linking Normalized Difference Vegetation Index(NDVI), to forest biomass extracted from SPOT/4 VEGETATION data and PAL 8km data in regional and continental area (N40-N70) respectively. Statistical tests indicated that the regression model can be used to represent the changes of forest biomass carbon pools and sinks at high latitude regions over years 1982-2000. This study suggests that the implementation of estimation of biomass based on 8-km resolution NOAA/AVHRR PAL and SPOT-4/VEGETATION data could be detected over a range of land cover change processes of interest for global biomass change studies.