• The Korean Journal of Soil Zoology
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• v.5 no.2
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• pp.47-62
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• 2000

This study investigated the effect of soil animals at forest fire area, and it carried out the mountain located at Jundae Ri, Houeng-chen Myen, Ha-dong Gun, Kyoung-Nam Province, southern part of Korea, where burned out about 50 hectars on April 11, 1997. Vegetation of the examined area absolutely dominated with the pines of 7-14 cm in diameter and 20 to 30 years old and the rest were covered with mixed forest with a shrub such as the oak (Quereus mongolia Fisch, Quereus variabilis BI, Quereus dentana Thunb), snowbell(Styrax japonica, S, et, z), lacquer tree (Rhus trichocarpa Mig), azalea (Rhododendron mucronulatum Turcz), etc. And there were simple area organized as a herbaceous plant, and the burnt area was poor experimental sites, where litter layer and herbaceous plant disappeard due to fire, and the unburnt area was rich in surface plant, dead leaves, twigs, etc. But the ground cover vegetations were poor in the unburnt area. The distribution of each animal groups, the seasonal fluctuation in population density, the biomass of meso$.$macroarthropods and the relationship between soil animal and some environmental factors were investigated and analyzed at each experimental area. The result are summarized as follow: 1. Identificated 257,087 individuals of soil microarthropods were classified into 7 classes and 24 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta., and identified 8,006 individuals of the total meso$.$macroarthropods were classified into 7 classes and 20 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta. 2. Among the total soil microarthropods, Arachinida formed 70.9%, followed by Insecta for 28.4% and among the total meso$.$macroarthropod , Insecta formed 57.6%, followed by Chilopoda for 23.8%.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.123-133
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• 2007

Thermal spatial representativities of meteorological stations over Korea have been investigated using land surface temperature (LST) based on MODerate resolution Imaging Spectroradiometer (MODIS) satellite observation. The linear regression method was used to estimate air temperatures from MODIS LST product. To compare MODIS LST with observed air temperatures at six meteorological stations, the mean values of MODIS LST with nine given window sizes were calculated. In this case, the position of centered pixel in each given window size is correspond to that of each meteorological station. We also applied $4^{\circ}C$ threshold for RMSE comparison, which is based on a analogous study on daily maximum air temperature model using satellite data. In this study, the results showed that each station has a different representativity; Deajeon $15km{\times}15km$, Chuncheon $11km{\times}11km$, Seoul $7km{\times}7km$, Deagu $5km{\times}5km$, Kwangju $3km{\times}3km$, and Busan $3km{\times}3km$.

• Korean Journal of Environment and Ecology
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• v.28 no.2
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• pp.253-262
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• 2014

This study was conducted to find methods of qualitative landscape assessment for vegetational landscapes using ecological analysis. The study site was Seoraksan National Park in Korea. For this study, differing unique landscape resources were categorized and identified according to ecosystems. After identifying the study areas, the relationship between trail visitor preference and the amount of visible overexposure caused by people to the resources was examined. Landscape resources chosen for ecological analysis at Seoraksan National Park were subalpine vegetation community, high mountain rocks, ombrogenous deciduous broadleaf forest in the valley area, edaphic climax community, big tree community, flowering tree dominant community, autumnal tree dominant community and needle-leaf forest in the subalpine area. As a result of the study, it was found that the landscape resources with the highest correlation to visitor trail preference were big tree community area, flowering tree dominant community area, and needle-leaf forest in the subalpine area. As a result of overlapping the analysis of the amount of visible overexposure to the landscape resources and the analysis of preferential use of trails by visitors, guidance for the appropriate season for each trail can be provided. Since a positive correlation exists between certain sections of the natural landscapes and visitor preference, ecological impact on landscape resource ecosystems did not appear to cover wide areas of the trails, but was limited to certain areas preferred by visitors.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.322-330
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• 1994

The Universal Soil Loss Equation (USLE) has been widely used to predict long-term soil loss by incorporating several erosion factors, such as rainfall, soil, topography, and vegetation. This study is aimed to introduce the LISLE within geographic information system(GIS) environment. The Kwangneung Experimental Forest located in Kyongki Province was selected for the study area. Initially, twelve years of hourly rainfall records that were collected from 1982 to 1993 were processed to obtain the rainfall factor(R) value for the LISLE calculation. Soil survey map and topographic map of the study area were digitized and subsequent input values(K, L, S factors) were derived. The cover type and management factor (C) values were obtained from the classification of Landsat Thematic Mapper(CM) satellite imagery. All these input values were geographically registered over a common map coordinate with $25{\times}25m^2$ ground resolution. The USLE was calculated for every grid location by selecting necessary input values from the digital base maps. Once the LISLE was calculated, the resultant soil loss values(A) were represented by both numerical values and map format. Using GIS to run the LISLE, it is possible to pent out the exact locations where soil loss potential is high. In addition, this approach can be a very effective tool to monitor possible soil loss hazard under the situations of forest changes, such as conversion of forest lands to other uses, forest road construction, timber harvesting, and forest damages caused by fire, insect, and diseases.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.265-278
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• 1991

The purpose of this study is to suggest objective basic data for the design and management of the national park roadside slopes through the quantitative analysis of the visual quality included in the physical environment of the Chi-ri national park, for this, visual volumes of physical elements have been evaluated by using the mesh analysis, spatial images structure of physical elements have been analyzed by factor analysis algorithm, and degree of visual quality have been measured mainly by questionnaires. Result of this thesis can be summarized as fallows. Visual volumes of the naked, rock, ground cover of seed spray, and artificial planting are found to be the main factor determining the visual quality. Factors covering the spatial image of the national park roadside slopes landscape have been found to be the overall synthetic evaluation, spatial, appeal, physical, openness and dignity factors such as the overall the spatial, physical and openness yield high factor scores. As for the factors determining the degree of visual quality of the roadside slopes, variables such as the summit, the constructions management, harmony of landscape, visual stability of roadside slopes, suitable artificial planting and suitable constructions.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.371-384
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• 2015

Although GOCI has potential for land surface monitoring, there have been only a few cases for land applications. It might be due to the lack of reliable land products derived from GOCI data for end-users. To use for land applications, it is often essential to provide cloud-free composite over land surfaces. In this study, we proposed a cloud detection method that was very important to make cloud-free composite of GOCI reflectance and vegetation index. Since GOCI does not have SWIR and TIR spectral bands, which are very effective to separate clouds from other land cover types, we developed a multi-temporal approach to detect cloud. The proposed cloud detection method consists of three sequential steps of spectral tests. Firstly, band 1 reflectance threshold was applied to separate confident clear pixels. In second step, thick cloud was detected by the ratio (b1/b8) of band 1 and band 8 reflectance. In third step, average of b1/b8 ratio values during three consecutive days was used to detect thin cloud having mixed spectral characteristics of both cloud and land surfaces. The proposed method provides four classes of cloudiness (thick cloud, thin cloud, probably clear, confident clear). The cloud detection method was validated by the MODIS cloud mask products obtained during the same time as the GOCI data acquisition. The percentages of cloudy and cloud-free pixels between GOCI and MODIS are about the same with less than 10% RMSE. The spatial distributions of clouds detected from the GOCI images were also similar to the MODIS cloud mask products.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Korean Journal of Environment and Ecology
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• v.18 no.1
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• pp.53-60
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• 2004

This study was carried out to investigate the effect of green area in apartment complexes to variation of temperature. The inside temperature of each site was estimated by analyzing Landsat ETM＋ image data. The factors on variation of temperature were landcover type, building density, and Normalised Difference Vegetation Index(NDVI). The results of correlation between inside temperature of apartment complex and land cover type showed that the green area ratio had negative(－) correlation and impermeable pavement ratio had positive(＋) correlation. Building-to-land ratio was not significant with inside temperature. A coefficient of correlation between the temperature value and the value of permeable pavement ratio added up green area ratio was higher than a coefficient of correlation between the temperature value and the value of permeable pavement ratio added up impermeable pavement ratio. Thus we may define that permeable pavement area decrease urban temperature with green area in apartment complex. Floor area ratio had no significant correlation with inside temperature. Inside temperature was decreased as the NDVI was increased. To establish the temperature distribution model in a development apartment complex, As the result of regression analysis between inside temperature as dependent variable and permeable pave ratio+green area ratio, green area ratio, building-to-land ratio and NDIT as independent variables, only permeable pavement ratio added up green area ratio of the independent variables was accepted fur regression equation in both two seasons and adjusted coefficient of determination was 41.4 on September, 2000 and 40.4 on June,2001.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.837-847
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• 2017

Land Surface Model (LSM) was developed for the Soyang river basin located in Korean Peninsula to clarify the spatio-temporal variability of hydrological weather parameters. Variable Infiltration Capacity (VIC) model was used as a LSM. The spatial resolution of the model was 10 km and the time resolution was 1 day. Based on the daily flow data from 2007 to 2010, the 7 parameters of the model were calibrated using the Isolated Particle Swarm Optimization algorithm and the model was verified using the daily flow data from 2011 to 2014. The model showed a Nash-Sutcliffe Coefficient of 0.90 and a correlation coefficient of 0.95 for both calibration and validation periods. The hydrometeorological variables estimated for the Soyang river basin reflected well the seasonal characteristics of summer rainfall concentration, the change of short and shortwave radiation due to temperature change, the change of surface temperature, the evaporation and vegetation increase in the cover layer, and the corresponding change in total evapotranspiration. The model soil moisture data was compared with in-situ soil moisture data. The slope of the trend line relating the two data was 1.087 and correlation coefficient was 0.723 for the Spring, Summer and Fall season. The result of this study suggests that the LSM can be used as a powerful tool in developing precise and efficient water resources plans by providing accurate understanding on the spatio-temporal variation of hydrometeorological variables.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.132-139
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• 2007

The Moderate Resolution Imaging Spectroradiometer (MODIS) regularly provides the eight-day gross primary productivity (GPP) at 1 km resolution. In this study, we evaluated the uncertainties of MODIS GPP caused by errors associated with the Data Assimilation Office (DAO) meteorology and a biophysical variable (fraction of absorbed photosynthetically active radiation, FPAR). In order to recalculate the improved GPP estimate, we employed ground weather station data and reconstructed cloud-free FPAR. The official MODIS GPP was evaluated as +17% higher than the improved GPP. The error associated with DAO meteorology was identified as the primary and the error from the cloud-contaminated FPAR as the secondary constituent in the integrative uncertainty. Among various biome types, the highest relative error of the official MODIS GPP to the improved GPP was found in the mixed forest biome with RE of 20% and the smallest errors were shown in crop land cover at 11%. Our results indicated that the uncertainty embedded in the official MODIS GPP product was considerable, indicating that the MODIS GPP needs to be reconstructed with the improved input data of daily surface meteorology and cloud-free FPAR in order to accurately monitor vegetation productivity in Korea.