• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.839-849
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• 2003

Drought is one of the major environmental disasters. Weather data, particularity rainfall, are currently the primary source of information widely used for drought monitoring. However, weather data are often from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely drought detection. Data from remote sensing platforms can be used to complements weather data in drought. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI)-based vegetation condition index(VCI) were used in this study These indices showed their excellent ability to detect vegetation stress due to drought. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the VCI index.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.1
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• pp.72-82
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• 2015

We constructed greenhouse gas (GHG) and air pollution (AP) integrated sink/emission inventories and evaluated the environmental value for the vegetation sector in Seoul during year 2010. The data of vegetation, classified into four sectors of cultivated land, forest land, park and street tree, were obtained from Statistics Korea and Seoul City. Based on the previous studies, only $CO_2$ was chosen as GHG sink by vegetation. $NO_2$ and $SO_2$ were chosen as AP sink by vegetation, while isoprene, monoterpene, other VOC (OVOC) and NH3 were chosen as AP emission from vegetation. Estimation methodology and sink/emission factors were gathered from reports and published literatures. Estimated GHG sink by vegetation during year 2010 was 12,987,173 $tonCO_{2eq}$, of which approximately 1/4 was from pure vegetation and the remaining 3/4 from vegetation soil. AP sink and emission were estimated to be 23,309 tonAP and 2,629,797 tonAP, respectively. The analysis by administrative districts in Seoul revealed that among 25 districts, Seocho-gu, Nowon-gu, Eunpyeong-gu, Gwanak-gu and Gangbuk-gu were the major districts in GHG and AP sink/emission inventories for vegetation sector. Environmental value of vegetation as a function of GHG and AP sink, was estimated as 800 billion won, corresponding to 5% of the total cost of the forest land in Korea evaluated as a public function.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.423-438
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• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.181-188
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• 1997

Vegetation is an important factor in EIA(Environmental Impact Assessment) and it is assessed according to DGN(Degree of Green Naturality) in EIS(Environmental Impact Statement) preparation. But DGN has room for improvement of assessing vegetation Status. This study introduced NDVI(Normalized Difference Vegetation Index) for improving status assessment method that subjects to DGN. For the application of NDVI, Landsat TM data of Chunchon on May 2, 1989 and June 1, 1994, and data of Ulsan on November 5, 1984, November 2, 1992 and May 9, 1994 were used. It compared NDVI with DGN according to season and location. The correlation coefficient value for the spring image (1994, 0.7, p=0.01) was proved to be higher than that of autumn (1984, 0.5, p=0.01).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.328-330
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• 2003

The land cover of burned area has changed dramatically since Daxinganling forest fire in Northeastern China during May 6 ? June 4, 1987. This research focused on determining the burn severity and assessment of forest recovery. Burned severity was classified into three levels from June 1987 Landsat TM data acquired just after the fire. A regression model was established between the forest canopy closure from 1999 forest stand map and the NDVI values from June 2000 Landsat ETM+ data. The map of canopy closure was got according to the regression model. And vegetation cover was classified into four types according to forest closure density. The change matrix was built using the classified map of burn severity and vegetation recovery. Then the change conversions of every forest type were analyzed. Results from this research indicate: forest recovery status is well in most of burned scars; and vegetation change detection can be accomplished using postclassification comparison method.

• Architectural research
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• v.25 no.4
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• pp.73-84
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• 2023

Indoor thermal conditions greatly affect the health and comfort of humans who occupy the space in it. The purpose of this research is to analyze the influence of water and vegetation elements as a microclimate modifier in buildings to obtain thermal comfort through the study of thermal environment models. This research covers two objects, namely public buildings and housing in Makassar City, South Sulawesi Prov-ince - Indonesia. Quantitative methods through field surveys and measurements based on thermal and personal variables. Data analysis based on ASHRAE 55 2020 standard. The data was processed with a parametric statistical approach and then simulated with the Computational Fluid Dynamics (CFD) simulation method to find a thermal prediction model. The model was made by increasing the ventilation area by 2.0 m2, adding 10% vegetation with shade plant characteristics, moving water features in the form of fountains and increasing the pool area by 15% to obtain PMV + 0.23, PPD + 8%, TSV-1 - +0, Ta_25.7℃, and relative humidity 63.5 - 66%. The evaluation shows that the operating temperature can analyze the visitor's comfort temperature range of >80% and comply with the ASHRAE 55-2020 standard. It is concluded that water elements and indoor vegetation can be microclimate modifiers in buildings to create desired comfort conditions and adaptive con-trols in buildings such as the arrangement of water elements and vegetation and ventilation systems to provide passive cooling effects in buildings.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.107-115
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• 2017

This study illustrated the process of bar structure and vegetation coverage to understand historical changes of riverbed and suppose adaptive management in Tan-chun ecological landscape reserve. The study site that lower reach of the Tan-chun are known as habitats of migratory bird and aquatic species with dynamic riverbed. Aerial photos from 2006 to 2016 and surveyed vegetation data in 2006 and 2016 were used by analysis of landscape changes and comparison of vegetation coverage. Study area is classified into 3 sites (A: straight site, B: meandering site, C: meandering and junction with Yangjae-cheon). The result showed that bar area of A and C sites gradually increased, B site decreased during 10 years. Also, ratio of bar area to vegetation coverage and level of vegetation coverage increased in all sites during 10 years. All sites seem to have experienced the terrestrialization with time. On the other hand, ratio of annual vegetation increased and ratio of perennial vegetation decreased in C site in 2016 compare to 2006. Because area of Japanese Hops (Humulus japonicas) as one type of annual vegetation increased, other vegetation could not grow up by its powerful expandability. It is time to make active adaptive management based on not only continuos monitoring but also revaluation of river conditions in order to enhance habitat quality and quantity in Tan-chun ecological landscape reserve.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.545-552
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• 2017

Aeolian dunes are typical sand dunes which are maintained and developed by interactions of earth surface, wind and vegetation. Developing a model which can predict the changing phenomena of these sand dunes is vital in enhancing the efficiency of understanding and management of terrains such as land degradation. In the existing models, however, there is lack of studies on the long - term behaviors of the sand dunes and application to actual topography. Therefore, this study applied the wind-vegetation model considering vegetation to the actual topography and analyzed the applicability of the wind-vegetation model by analyzing the long-term behaviors and comparing them with actual data. Through analysis, study found out that use of wind-vegetation model and data from unmanned aerial vehicle is effective in analyzing the changes of actual dune topography. Except for the boundary, the error of about 1m was generated compared with the change of the actual dune topography.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• Proceedings of the KSRS Conference
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• v.2
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• pp.852-855
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• 2006

There is an increasing need to use data from different sensors in order to maximize the chances of obtaining a cloud-free image and to meet timely requirements for information. However, the use of data from multiple sensor systems is depending on comprehensive relationships between sensors of different types. Indeed, a study of inter-sensor relationships is well advanced in the effective use of remotely sensed data from multiple sensors. This paper was concerned with relationships between sensors of different types for vegetation indices (VI). The study was conducted using IKONOS and Landsat-7 ETM+ images. IKONOS and Landsat-7 ETM+ image of the same or about the same dates were acquired. The Landsat-7 ETM+ images were resampled in order to make them coincide with the pixel sizes of IKONOS. Inter-relationships of vegetation indices between images were performed using at-satellite reflectance obtained by converting image digital number (DN). All images were applied to topographic normalization method in order to reduce topographic effect in digital imagery. Also, Inter-sensor model equations between two sensors were developed and applied to other study region. In the result, the relational equations can be used to compute or interpret VI of one sensor using the VI of another sensor.