• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1009-1021
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• 2016

The community structure and abundance of epilithic biofilm were bimonthly examined to know spatial and temporal patterns of biofilm biomass and taxonimical composition at the two study sites, Gosapo and Gyeokpo with different degrees of wave exposure levels from November 2010 to September 2011. Biomass was estimated by using chlorophyll a contents (Chl a), normalized difference vegetation index (NDVI), and vegetation index (VI). Cyanobacteria such as Aphanotece spp. predominated in the proportion of 57.53% at Gosapo and of 61.12% at Gyeokpo and they are abundant in mid shore and in summer at both study sites. The diatoms Navicula spp., Achnanthes spp. and Licmophora spp. were common species and they showed an increasing trend from high to low shore. NDVI, VI, and chl a contents were the greatest at mid shore for Gosapo (0.44, 3.05, $24.56{\mu}g/cm^2$) and at low shore for Gyeokpo (0.41, 2.73, $17.98{\mu}g/cm^2$). NDVI, VI, and chl a content were all maximal in January and minimal in March at the both sites. Average NDVI, VI, and chlorophyll a contents of biofilms were greater at Gosapo (0.43, 2.89, $22.84{\mu}g/cm^2$) than Gyeokpo (0.38, 2.48, $15.48{\mu}g/cm^2$).Of three shore levels(high, mid, and low) Chl a contents were positively correlated with NDVI and VI at the two study sites indicating that non-destructive NDVI and VI values can be used in stead of destructive Chl a extraction method. In conclusion, epilithic biofilm was more abundant seasonally in winter, vertically in mid and low intertidal zone, and horizontally at wave exposed shore than in summer, at high and sheltered shore in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.163-174
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• 2012

CBI(Composite Burn Index) developed by USDA Forest Service is a index to measure burn severity based on remote sensing. In Korea, the CBI has been used to investigate the burn severity of fire sites for the last few years. However, it has been an argument on that CBI is not adequate to capture unique characteristics of Korean forests, and there has been a demand to develop KCBI(Korean Composite Burn Index). In this regard, this study aimed to develop KCBI by adjusting the CBI and to validate its applicability by using remote sensing technique. Uljin and Youngduk, two large fire sites burned in 2011, were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. Burn severity(BS) of the study areas were estimated by analyzing NDVI from SPOT images taken one month later of the fires. Applicability of KCBI was validated with correlation analysis between KCBI index values and NDVI values and their confusion matrix. The result showed that KCBI index values and NDVI values were closely correlated in both Uljin (r = -0.54 and p<0.01) and Youngduk (r = -0.61 and p<0.01). Thus this result supported that proposed KCBI is adequate index to measure burn severity of fire sites in Korea. There was a number of limitations, such as the low correlation coefficients between BS and KCBI and skewed distribution of KCBI sampling plots toward High and Extreme classes. Despite of these limitations, the proposed KCBI showed high potentials for estimating burn severity of fire sites in Korea, and could be improved by considering the limitations in further studies.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.26-67
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• 2020

Synthetic Aperture Radar(SAR) is able to photograph the earth's surface regardless of weather conditions, day and night. Because of its possibility to search for hydrological factors such as soil moisture and groundwater, and its importance is gradually increasing in the field of water resources. SAR began to be mounted on satellites in the 1970s, and about 15 or more satellites were launched as of 2020, which around 10 satellites will be launched within the next 5 years. Recently, various types of SAR technologies such as enhancement of observation width and resolution, multiple polarization and multiple frequencies, and diversification of observation angles were being developed and utilized. In this paper, a brief history of the SAR system, as well as studies for estimating soil moisture and hydrological components were investigated. Up to now hydrological components that can be estimated using SAR satellites include soil moisture, subsurface groundwater discharge, precipitation, snow cover area, leaf area index(LAI), and normalized difference vegetation index(NDVI) and among them, soil moisture is being studied in 17 countries in South Korea, North America, Europe, and India by using the physical model, the IEM(Integral Equation Model) and the artificial intelligence-based ANN(Artificial Neural Network). RADARSAT-1, ENVISAT, ASAR, and ERS-1/2 were the most widely used satellite, but the operation has ended, and utilization of RADARSAT-2, Sentinel-1, and SMAP, which are currently in operation, is gradually increasing. Since Korea is developing a medium-sized satellite for water resources and water disasters equipped with C-band SAR with the goal of launching in 2025, various hydrological components estimation researches using SAR are expected to be active.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.144-159
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• 2006

Hydrological models are tools intended to realistically represent the basin's complex system in which hydrological characteristics result from a number of physical, vegetative, climatic, and anthropomorphic factors. Spatially distributed hydrological models were first developed in the 1960s, Remote sensing(RS) data and Geographical Information System(GIS) play a rapidly increasing role in the field of hydrology and water resources development. Although very few remotely sensed data can applied in hydrology, such information is of great. One of the greatest advantage of using RS data for hydrological modeling and monitoring is its ability to generate information in spatial and temporal domain, which is very crucial for successful model analysis, prediction and validation. In this paper, SLURP model is selected as semi-distributed hydrological model and MODIS Leaf Area Index(LAI), Normalized Difference Vegetation Index(NDVI) as Remote sensing input data to hydrological modeling of Kyung An-chen basin. The outlet of the Kyung An stage site was simulated, We evaluated two RS data, based on ability of SLURP model to simulate daily streamflows, and How the two RS data influence the sensitivity of simulated Evapotranspiration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.2
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• pp.114-124
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• 2014

For classifying fire damaged areas and analyzing burn severity of two large-fire areas damaged over 100 ha in 2011, three methods were employed utilized supervised classification, unsupervised classification and Normalized Difference Vegetation Index (NDVI). In this paper, the post-fire imageries of SPOT were used to compute the Maximum Likelihood (MLC), Minimum Distance (MIN), ISODATA, K-means, NDVI and to evaluate large-scale patterns of burn severity from 1 m to 5 m spatial resolutions. The result of the accuracy verification on burn severity from satellite images showed that average overall accuracy was 88.38 % and the Kappa coefficient was 0.8147. To compare the accuracy between burn severity and field survey at Uljin and Youngduk, two large fire sites were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. The burn severities of the study areas were estimated by analyzing burn severity (BS) classes from SPOT images taken one month after the occurrence of the fire. The applicability of composite burn index (CBI) was validated with a correlation analysis between field survey data and burn severity classified by SPOT5, and by their confusion matrix. The result showed that correlation between field survey data and BS by SPOT5 were closely correlated in both Uljin (r = -0.544 and p<0.01) and Youngduk (r = -0.616 and p<0.01). Thus, this result supported that the proposed burn severity analysis is an adequate method to measure burn severity of large fire areas in Korea.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.2
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• pp.70-78
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• 2009

Remote sensing technique in agriculture can be used to identify chlorophyll content, biomass, and yield caused from N stress level. This study was conducted to evaluate biomass, N stress levels, and yield of tobacco (Nicotiana tabacum L.) under sand culture in a plastic film house using ground-based remote sensors. Nitrogen rates applied were 40, 60, 80, 100, 120, and 140 percent of N concentration in the Hoagland's nutrient solution. Sensor readings for reflectance indices were taken at 30, 35, 40, 45, 50 and 60 days after transplanting(DAT). Reflectance indices measured at 40th DAT were highly correlated with dry weight(DW) of tobacco leaves and N uptake by leaves. Especially, green normalized difference vegetation index(gNDVI) from spectroradiometer and aNDVI from Crop Circle passive sensor were able to explain 85% and 84% of DW variability and 85% and 92% of N uptake variability, respectively. All the reflectance indices measured at each sampling date during the growing season were significantly correlated with tobacco yield. Especially the gNDVI derived from spectroradiometer readings at the 40th DAT explained 72% of yield variability. N rates of tobacco were distinguished by sufficiency index calculated using the ratio of reflectance indices of stress to optimum plot of N treatment. Consequently results indicate that the reflectance indices by ground-based remote sensor can be used to predict tobacco yield and recommend the optimum application rate of N fertilizer for top dressing of tobacco.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.91-107
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• 2018

It is required to monitor and assess the desertification in Tunisia, where the Sahara Desert, which is located in the southern part of Tunisia, is recently expanding northward. In this study, by using remote sensed data, land cover changes were examined, and the Normalized Difference Vegetation Index (NDVI), Topsoil Grain Size Index (TGSI) and Albedo are used to monitor and assess desertification in Tunisia. Decision Tree was constructed, and the frequencies and trends of each assessment indicator, desertification degree and land cover were identified. In addition, we analyzed the correlation between assessment indicators and precipitation. As a result, desertification is generally intensifying northward, especially in areas with high levels of desertification. Also, bivariate correlation analysis showed that Albedo, NDVI and TGSI were all highly correlated with precipitation. It indicates that changes in precipitation have also been shown to affect Tunisian desertification. In conclusion, this study has improved the usability of various methodologies considering the assessment indicators based on satellite imagery, Decision Tree, which is a method of evaluating them complexly, and trends of land cover change.

• Weed & Turfgrass Science
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• v.3 no.1
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• pp.41-49
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• 2014

Four preparations of liquid turfgrass fertilizers were tested cool season turfgrasses during fall season. The preparations of PS-A, PS-B, PH-C and PH-D for commercial products were contained with essential nutrient elements, seaweed extract, amino acids, and humus substance. Growth and quality of creeping bentgrass (Agrostis palustris Huds cv. Penn-A1) and Kentucky bluegrass (Poa pratensis L.) mixture (Midnight 33%, Moonlight 33%, Prosperity 33%) were evaluated by normalized difference vegetation index (NDVI), root length and fresh weight, shoot density, turf color, and chlorophyll content. Three foliar sprays of 4 preparations with an interval of 7 days were made in the fall of 2013 in the sod production field at Hapchun, Korea. No significant difference among 3 preparations was found in NDVI of creeping bentgrass. However, PS-A was significantly increased NDVI of Kentucky bluegrass. Two to three applications of PS-A significantly increased chlorophyll content and turf color. Three foliar sprays of PS-A and PS-B were significantly increased the shoot density of Kentucky bluegrass on 20 days after final application. These results may indicate that the use of some preparation is beneficial in producing higher quality turfgrass sod with better color and chlorophyll content during fall season.

• Weed & Turfgrass Science
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• v.4 no.3
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• pp.268-277
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• 2015

Organic fertilizer preparation was developed with organic materials to improve growth and qualities of cool-season turfgrass species. Organic fertilizer preparation were contained with essential macronutrient elements and organic matter for growth of cool season turfgrass. Four preparations of organic fertilizers were tested on creeping bentgrass (Agrostis palustris Huds) cultivar Penn-A1 and Kentucky bluegrass (Poa pratensis L.) mixed cultivars (Midnight 33%, Moonlight 33%, and Prosperity 33%) by one time application on fifty days after sowing. Two species of cool season turfgrasses were evaluated on turfgrass coverage, growth on NDVI (Normalized Difference Vegetation Index) and qualities from fall season to spring season in sod producing farm. It were found significantly difference found on turfgrass coverage, turf color, chlorophyll contents and growth increase on two species of cool season turfgrasses. Turfgrass coverage, chlorophyll content, turf color and growth increase of organic fertilizer preparation were significantly increased on creeping bentgrass cultivar and Kentucky bluegrass mixed cultivar for six time investigation in spring season. These results may indicate that the use of some preparation is beneficial for sod producing sod and turfgrass management.