• Journal of Korean Society on Water Environment
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• v.32 no.1
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• pp.60-69
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• 2016

In this study, we estimated root zone soil moisture dynamics using remotely sensed (RS) data. A soil moisture data assimilation scheme was used to derive the soil and root parameters from MODerate resolution Imaging Spectroradiometer (MODIS) data. Based on the estimated soil/root parameters and weather forcings, soil moisture dynamics were simulated at spatio-temporal scales based on a hydrological model. For calibration/validation, the Little Washita (LW13) in Oklahoma and Chungmi-cheon/Seolma-cheon sites were selected. The derived water retention curves matched the observations at LW 13. Also, the simulated soil moisture dynamics at these sites was in agreement with the Time Domain Reflectrometry (TDR)-based measurements. To test the applicability of this approach at ungauged regions, the soil/root parameters at the pixel where the Seolma-cheon site is located were derived from the calibrated MODIS-based (Chungmi-cheon) soil moisture data. Then, the simulated soil moisture was validated using the measurements at the Seolma-cheon site. The results were slightly overestimated compared to the measurements, but these findings support the applicability of this proposed approach in ungauged regions with predictable uncertainties. These findings showed the potential of this approach in Korea. Thus, this proposed approach can be used to assess root zone soil moisture dynamics at spatio-temporal scales across Korea, which comprises mountainous regions with dense forest.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.935-943
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• 2014

Normalized Difference Vegetation Index (NDVI) used as input data for various hydrologic models plays a key role in understanding the variation of Hydrometeological parameters and Interaction between surface and atmosphere. Many studies have been conducted to estimate accurate remotely-sensed NDVI using spectral characteristics of vegetation. In this study, we conducted comparative analysis between Communication, Ocean and Meteorological Satellite and MOderate-Resolution Imaging Spectroradiometer (MODIS) NDVI. For comparison, Maximum Value Composite (MVC) was used to estimate 8-day and 16-day composite COMS NDVI. Both 8-day and 16-day COMS NDVI showed high statistical results compared with MODIS NDVI. Based on the results in this study, it can be concluded that COMS can be widely applicable for further ecological and hydrological studies.

• Spatial Information Research
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• v.16 no.4
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• pp.411-420
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• 2008

To provide technological foundation for periodic and real-time land monitoring over the Korean peninsula where the land cover changes are prevailing, the Land Monitoring Research project was initiated as one of five core projects within the Intelligent National Land Information Technology Innovation Project operated by the Korean Land Spatialization Group (KLSG). This four year project can be categorized into two research themes with nine sub-projects. The first research theme is dealing with the real-time data acquisition from aerial platform and in-situ measurements by ubiquitous sensor network (USN), ground video camera, and automobile-based data collection systems. The second research theme is mainly focused on the development of application systems that can be directly utilized in several public organizations dealing with land monitoring over the nation. The Moderate Resolution Imaging Spectroradiometer (MODIS)-based land monitoring system that is currently under development is one of such application systems designed to provide necessary information regarding the status and condition of land cover in near real-time.

• Spatial Information Research
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• v.21 no.5
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• pp.15-22
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• 2013

The purpose of this work is to investigate correlation between $CO_2$ concentration and NDVI (Normalized Difference Vegetation Index) in North East Asia. Geographically weighted regression techniques were used to evaluate the spatial relationships between GOSAT (Greenhouse Observing SATellite) $CO_2$ measurement and MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation index. The results reveals that $CO_2$ concentration to be negatively associated with NDVI. The analysis of Global Morans' I index and Anselin Local Morasn's I showed spatial autocorrelation between the overall spatial pattern of $CO_2$ and NDVI. Ultimately, there were clustered patterns in both data sets. The results show that carbon dioxide concentration shows non-random distribution patterns in relation to NDVI clusters, which proves that intense development activities such as deforestation are influencing carbon dioxide emission across the area of analysis. However, as the concentration of carbon dioxide varies depending on a variety of factors such as artificial sources, plant respiration, and the absorption and discharge of the ocean, follow-up studies are required to evaluate the correlations among more related variables.

• Spatial Information Research
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• v.22 no.1
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• pp.27-33
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• 2014

Considering the wide coverage, the transparency from climate condition, Interferometric Synthetic Aperture Radar (InSAR) possesses a great potential for the landcover classification as shown in many precedent researches. In addition to the merits of InSAR products for the landcover classification, the time series analysis of InSAR pairs can provide a highly reliable basis to interpret landcover. We applied such idea with the test site in Mountain Baekdu located on the border between North Korea and China. Since it is recently noted as the potential volcanic activation site, the landcover especially the vegetation distribution information is highly essential to validate the reliability of Differential Interferometric Synthetic Aperture Radar (DInSAR) over Mt. Baekdu. The algorithms combining the auxiliary information from Moderate Resolution Imaging Spectroradiometer (MODIS) to analyze the phase coherence and backscatter coefficient of Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) was established. The results using InSAR signatures from two polarization modes of ALOS PALSAR showed high reliability for mining landcover and spatial distribution.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.293-296
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• 2008

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

• Atmosphere
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• v.19 no.2
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.3
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• pp.255-262
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• 1997

To estimate the total dry matter(TDM) of rice plant by non-destructive method, spectral reflectance from rice plant canopy was measured by using the spectroradiometer (LI-1800, LICOR Inc.) with one week interval during the rice growing season at Suwon paddy field in 1993. Two medium late maturing rices, Daechung-byeo Ilpum-byeo, and one early maturing variety, Jinbu-byeo, were cultured to observe TDM, then they were compared with those estimated by vegetation index together. Vegetation index determined by the reflectance of visible against near infrared wavelength showed high correlation with TDM. Vegetation index derived from narrow band(10nm interval) ratio, R910/R460, has the highest correlation coefficient with TDM. TDM estimated from R910/R460 from transplanting to heading stage corresponded well to measured values (Y=21.2428X-212.734 ; $R^2$=0.87). But another vegetation index, NIR(720~1,100nm) /Red(600~700nm) showed higher correlation with TDM than NIR(720~1,100nm) /Blue(400~500nm) did from heading stage to maturity.

• Journal of Korean Society of Rural Planning
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• v.16 no.4
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• pp.109-116
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• 2010

Climate change is known to affect both natural and managed ecosystems, and will likely impact on the terrestrail carbon balance. This paper reports the effects of climate change on spatial-temporal changes in carbon reductions in South Korea's during 2000-2100. Future carbon (C) stock distributions are simulated for the same period using various spatial data sets including land cover, net primary production(NPP) and leaf area index (LAI) obtained from MODIS(Moderate Resolution Imaging Spectroradiometer), and climate data from Data Assimilation Office(DAO) and Korea Meteorological Administration(KMA). This study attempts to predict future NPP using multiple linear regression and to model dependence of soil respiration on soil temperature. Plants store large amounts of carbon during the growing periods. During 2030-2100, Carbon accumulation in vegetation was increased to $566{\sim}610gC/m^2$/year owing to climate change. On the other hand, soil respiration is a key ecosystem process that releases carbon from the soil in the form of carbon dioxide. The estimated soil respiration spatially ranged from $49gC/m^2$/year to $231gC/m^2$/year in the year of 2010, and correlating well with the reference value. This results include Spatial-Temporal C reduction variation caused by climate change. Therefore this results is more comprehensive than previous results. The uncertainty in this study is still large, but it can be reduced if a detailed map becomes available.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.409-414
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• 1998

To examine the detectability of the aerosol and/or Yellow dust from China crossing over the Yellow sea, three works carried out as follows , Firstly, a comparison was made of the visible(VIS), water vapor(WV), and Infrared(IR) images of the GMS-5 and NOAA/AVHRR on the cases of yellow sand event over Korea. Secondly, the spectral radiance and reflectance(%) was observed during the yellow sand phenomena on April, 1998 in Seoul using the GER-2600 spectroradiometer, which observed the reflected radiance from 350 to 2500 nm in the atmosphere. We selected the optimum wavelength for detecting of the yellow sand from this observation, considering the effects of atmospheric absorption. Finally, the atmospheric radiance emerging from the LOWTRAN-7 radiative transfer model was simulated with and without yellow sand, where we used the estimated aerosol column optical depth ($\tau$ 673 nm) in the Meteorological Research Institute and the d'Almeida's statistical atmospheric aerosol radiative characteristics. The image analysis showed that it was very difficult to detect the yellow sand region only by the image processing because the albedo characteristics of the sand vary irregularly according to the density, size, components and depth of the yellow sand clouds. We found that the 670-680 nm band was useful to simulate aerosol characteristics considering the absorption band from the radiance observation. We are now processing the simulation of atmospheric radiance distribution in the range of 400-900 nm. The purpose of this study is to present the preliminary results of the aerosol and/or Yellow dust detectability using the Ocean Scanning Multispectral Imager(OSMI), which will be mounted on KOMPSAT-1 as the ocean color monitoring sensor with the range of 400-900 nm wavelength.