• Journal of Environmental Science International
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• v.8 no.2
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• pp.151-154
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• 1999

To verify the accuracy of the numerical experiment of Part I, measurements at the matured rice canopy located around Junam reservoir were performed at August 14, 1995. According to the measured data, the foliage temperature recorded the highest value, and the ground temperature was the lowest around noon, and these results coincided with those of the numerical experiment using the combined model of Part I. From the estimation using measured data, the maximum value of the latent heat flux was 380$Wm^2$, the highest value among energy balance terms, and the energy redistribution ratio of the latent heat flux was averaged as 0.5, the highest values among redistribution ratios. These results are the same as those of the numerical experiment in tendency, but they reveals a little lower in the absolute values than those from the numerical experiment.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.908-910
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• 2003

In this paper the extraction method for the best suitable green vegetation area in urban area, Daegu, Korea, was developed using satellite images (1994, 1999, Landsat TM). For this, the GIS overlay analysis of GVI (Green Vegetation Index), SBI (Soil Brightness index), NWI (None-Such wetness Index) was performed to estimate the best suitable green vegetation area. Also, the statistical documents, algorithm and Tasseled-Cap index were used to recognize the change of land cover such as cultivation area, urban area, and damaged area. Through the result of this study, it is possible to monitor the large sized reclamation of land by drainage or damaged area by forest fires. Moreover, information with the change of green vegetation and the status of cultivation by GVI, but also moisture content by percentage by NWI and surface class by SBI can be obtained.

• Journal of Ecology and Environment
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• v.41 no.2
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• pp.34-44
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• 2017

Background: Monitoring terrestrial vegetation cover condition is important to evaluate its current condition and to identify potential vulnerabilities. Due to simplicity and low cost, point intercept method has been widely used in evaluating grassland surface and quantifying cover conditions. Field-based digital photography method is gaining popularity for the purpose of cover estimate, as it can reduce field time and enable additional analysis in the future. However, the caveats and uncertainty among field-based vegetation cover estimation methods is not well known, especially across a wide range of cover conditions. We compared cover estimates from point intercept and digital photography methods with varying sampling intensities (25, 49, and 100 points within an image), across 61 transects in typical steppe, forest steppe, and desert steppe in central Mongolia. We classified three photosynthetic groups of cover important to grassland ecosystem functioning: photosynthetic vegetation, non-photosynthetic vegetation, and bare soil. We also acquired normalized difference vegetation index from satellite image comparison with the field-based cover. Results: Photosynthetic vegetation estimates by point intercept method were correlated with normalized difference vegetation index, with improvement when non-photosynthetic vegetation was combined. For digital photography method, photosynthetic and non-photosynthetic vegetation estimates showed no correlation with normalized difference vegetation index, but combining of both showed moderate and significant correlation, which slightly increased with greater sampling intensity. Conclusions: Results imply that varying greenness is playing an important role in classification accuracy confusion. We suggest adopting measures to reduce observer bias and better distinguishing greenness levels in combination with multispectral indices to improve estimates on dry matter.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.1
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• pp.82-91
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• 2009

Research was initiated to investigate vegetation characteristics of native ('Pureundle' and 'Sewon') and introduced ('Brilliant' and 'Midnight') Kentucky bluegrass (KB, Poa pratensis L.) varieties by soil-seed applying system on a cut-slope in May 17, 2008. There were no statistic differences observed in soil hardness and soil moisture content while significant differences were observed in surface coverage rate, height and disease occurrence in native and introduced KB varieties. The introduced 'Brilliant' KB was highest in the surface coverage rate from the early period of seeding to August 11, 2008. The surface coverage rate of introduced varieties were high when compared to native varieties in their early growth stage. But native varieties reached to equal surface coverage rate with the introduced varieties when three months after seeding. The height of 'Pureundle' and 'Brilliant' KBs were high compared with Midnight and Sewon KBs. 'Pureundle' and 'Brilliant' KBs were damaged by disease whereas there were no disease occurrence in 'Midnight' and 'Sewon' KBs. Probably, the disease occurrence was close related with the height of KBs not with native and introduced KB varieties. These results indicate that the growth of KB on a cut-slope are statistically affected by varieties in early growth stage of this experiment but reach equal rate between native and introduced KB varieties in three months after seeding. This growth characteristics implies the huge potential of native KB varieties seeding for cut-slope vegetation. Considering that native KB varieties are adapted to a environment and have no risk of causing disturbance to the ecosystem compared to the introduced KB varieties, the use of them as native varieties for a cut-slope vegetation can be increased.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.1 no.1
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• pp.18-27
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• 1998

To investigate the restoration progression on soil physical properties and vegetation at the surface of logging road affected by timber harvesting operation. This study was carried out at logging roads constructed from 1989 to 1994 in Mt. Baekwoon, Kwangyang, Chollanam-do. Judging from the analysis of soil hardness, there were significant changes in the depth of soil between 5 and 10cm. Soil hardness was recovered from the compacted condition to the natural forest condition after 9 years passed. Soil macroporous ratio (pF2.7) of topsoil was higher than that of deep soil. Soil moisture retention of topsoil was more improved than that of deep soil. From the view of soil bulk density, the necessary time for recovering to the undisturbed condition of forest soil was about 10 years in the logging road left. Soil physical properties such as soil bulk density and porous ratio were recovered as time passed. Improved soil physical properties promoted the plant recovery on the logging road surface. The dominant species on the logging roads were Comus kousa, Prunus sargentii as overstory species, Rubus crataegifolius, Lespedeza bicolor as understory species, and Saussurea gracilis, Pteridium aquilinum var. latiusculum as herbaceous species. The plant recovery of bank-slopes was faster than that of cut-slopes and road surface. In progress of year, average plant coverage were 70 to 90% in cut- and bank-slopes and 30 to 60% on the logging road, surface which was elapsed 9 years after logging road construction. Therefore, additional planting and seeding work could be effective to the soil condition and vegetation restoration.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.94-100
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• 2008

Recently, global warming for climate system is a crucial issue over the world and it brings about severe climate change, abnormal temperature, a downpour, a drought, and so on. Especially, a drought over the earth surface accelerates desertification which has been advanced over the several years mainly originated from a climatic change. The objective of this study is to detect variation of vegetation water condition around China and Mongolia desert by using satellite data having advantage in observing surface biological system. In this study, we use SPOT/VEGETATION satellite image to calculate NDWI (Normalized Difference Water Index) around study area desert for monitoring of status of vegetation characteristics. The vegetation water status index from remotely sensing data is related to desertification since dry vegetation is apt to desertify. We can infer vegetation water status using NDWI acquired by NIR (Near infrared) and SWIR (Short wave infrared) bands from SPOT/VGT. The consequence is that NDWI decreased around desert from 1999 to 2006. The areas that NDWI was decreased are located in the northeast of Mongolian Gobi desert and the southeast of China Taklamakan desert.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.329-332
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• 2007

Annual vegetation growth patterns are determined by the intrinsic phenological characteristics of each land cover types. So, if typical growth patterns of each land cover types are well-estimated, and a NDVI time-series data of a certain area is compared to those estimated patterns, we can implement more advanced analyses such as a land surface-type classification or a land surface type change detection. In this study, we utilized Terra MODIS NDVI 250m data and compressed full annual NDVI time series data into several indices using the Harmonic Analysis of Time Series(HANTS) algorithm which extracts the most significant frequencies expected to be presented in the original NDVI time-series data. Then, we found these frequencies patterns, described by amplitude and phase data, were significantly different from each other according to vegetation types and these could be used for land cover classification. However, in spite of the capabilities of the HANTS algorithm for detecting and interpolating cloud-contaminated NDVI values, some distorted NDVI pixels of June, July and August, as well as the long rainy season in Korea, are not properly corrected. In particular, in the case of two or three successive NDVI time-series data, which are severely affected by clouds, the HANTS algorithm outputted wrong results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.7
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• pp.660-663
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• 2016

This paper presents the effect of vegetation layer and radar parameters on soil moisture measurement using the vegetation layer scattering model and surface scattering model. The database of backscattering coefficients for various vegetation layer densities, incidence angles, frequencies, and polarizations is generated using $1^{st}$-order RTM(Radiative Transfer Model). Then, surface soil moisture contents were estimated from the backscattering coefficients in the database using the WCM(Water Cloud Model) and Oh model. The retrieved soil moisture contents were compared with the soil moisture contents in the input parameters of the RTM to estimate the retrieval errors. The effects of vegetation layer and radar parameters on soil moisture measurement are analyzed using the retrieval errors.

• Atmosphere
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• v.29 no.2
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• pp.131-147
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• 2019

On the urban scale, Micro-climate analysis models for urban scale have been developed to investigate the atmospheric characteristics in urban surface in detail and to predict the micro-climate change due to the changes in urban structure. BioCAS (Biometeorological Climate Impact Assessment System) is a system that combines such analysis models and has been implemented internally in the Korea Meteorological Administration. One of role in this system is the analysis of the health impact by heat waves in urban area. In this study, the vegetation cooling models A and B were developed and linked with BioCAS and evaluated by the temperature drop at the vegetation areas during ten selected heat-wave days. Smaller prediction errors were found as a result of applying the vegetation cooling models to the heat-wave days. In addition, it was found that the effects of the vegetation cooling models produced different results according to the distribution of vegetation area in land cover near each observation site - the improvement of the model performance on temperature analysis was different according to land use at each location. The model A was better fitted where the surrounding vegetation ratio was 50% or more, whereas the model B was better where the vegetation ratio was less than 50% (higher building and impervious areas). Through this study, it should be possible to select an appropriate vegetation cooling model according to its fraction coverage so that the temperature analysis around built-up areas would be improved.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.