• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.460-472
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• 1994

This study has been conducted to give some ideas for reasonable ecological management of Taejon city and its adjacent forest ecosystem against the effect of acid rain. Rain monitoring points to analyse its components represented 1 point in industrial area, 4 points in commercial area, 4 points in residential area, and 5 points in suburban area and forest survey was done in 7 forest sites adjacent to rain monitoring points. Transformed vegetation index(TVI) based on Landsat TM data was analysed for forest area. Taejon area was seriously contaminated by air pollutants and average concentration of anions in precipitation were 20.16mg/l for $SO_4{^{2-}}$, 3.65mg/l for $NO_3{^-}$, and 3.09mg/l for $Cl^-$. Anion in precipitation were $1.09mg/m^2/month$ for $SO_4{^{2-}}$, $0.23mg/m^2/month$ for $NO_3{^-}$, and $0.20mg/m^2/month$ for $Cl^-$. Cation in precipitation were $0.14mg/m^2/month$ for $Ca^{2+}$, $0.10mg/m^2/month$ for $NH_4{^+}$, $0.08mg/m^2/month$ for $Na^+$, $0.07mg/m^2/month$ for $K^+$, and $0.08mg/m^2/month$ for $Mg^{2+}$. The region with the highest concentration of $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ in rain was industrial area. $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ concentrations in industrial area were 43.08, 3.88, and 3.64ppm, respectively. Forest soil showed strongly acidic ranging pH4.16-4.94. Transformed vegetation index(TVI) were 3.11 in Dangsan, 4.00 in Kyechoksan, 4.13 in Bomunsan, 4.18 in Kabhasan, 3.34 in Bongsan, 4.13 in Sikchangsan, and 4.20 in Seongchisan. Dangsan forest located near in industrial area showed the lowest TVI.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.27-43
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• 1992

The purpose of this study is to detect and evaluate the change of urban vegetation of Seoul during 1980s. Large areas covered with agricultural crops or forests were converted to residential and commercial areas, roads, schools, sports complexes, etc. There were also widespreas concerns on the deterioration of the quality of urban vegetation due to severe air pollution, overcrowding of nature parks, and idling of farm lands by land speculators. The image used for this study were MSS(Oct. 4, 1979) and TM(Apr. 26, 1990). The Green Vegetation Index of Kauth & Thomas(1976) was for the analysis. The GVI were resampled with 75$\times$75m grids and overlaid with the jurisdictional boundaries of 22 districts of Seoul. The results were reclassified to 6 classes, class 6 representing grids with the most vigorous vegetation or the best vegetation improvement in 1980s. The finding of this study can be summarized as follows : First, the most vigorous vigorous vegetation, in terms of GVI, of the 1979 image can be found at paddy fields located on alluvial near Han River. Broad-leaf forests located on hilly terrains have higher GVI than conifers located on the upper-parts of mountains. The average GVI of the northern part and southern part of Han River are 3.56 and 3.74, respectively. The main reason why the southern part has higher GVI is that there are more prime agricultural lands. Districts of Kangseo, Yangcheon, and Songpa have the highest percentage of grids of GVI class 6, and the percentages are 3.55 %, 3.47 %, and 2.69 %, respectively. Second, the most vigorous vegetation of the 1990 image can be found at the grass lands of the Yongsan golf club and the Sungsu horse racing track. The GVI of farm lands is lower than forest because most agricultural crops are at the early stage of growing season when the TM image was taken. The size of built-up area is much larger than of 1979. On the other hand, vegetation patches surrounded by developed area become smaller and have stronger contrast to surrounding area. The average GVI of the northern part and southern part of Han River are 3.57 and 3.51, respectively. The main reason why the southern part has lower GVI is the at more large-scale urban development projects were carried out in there during 1980s. Districts of Tobong, Nowon, and Seocho have the highest percentage of class 6, and the perecentages are 16.58 %, 10.14 %, and 8.50% respectively. Third, the change of urban vegetation in Seoul during 1980s are significant. Grids of GVI change classes 1 and 2, which represent severe vegetation loss, occupy 15.97% of Seoul. Three districts which lost the most vegetation are Yangcheon, Kangseo, and Songpa, where the percentages of GVI class 1 are 13.42%, 13.39% and 9.06%, respectively. The worst deterioration was mainly caused by residential developments. On the other hand, the vegetation of some part of Seoul improved in this period. Grids of GVI change classes 5 and 6 occupy 9.83 % of Seoul. Distircts of Jung, Yongsan, and Kangnam have the highest percentage of grids with GVI change classes 5 and 6, and their percentages are 22.31%, 19.17%, and 13.66%, respectively. The improvement of vegetation occurred in two areas. Forest vegetation is generally improving despite of concerns based on air pollution and heavy use by recreationists. Vegetation in open spaces established in riverside parks, large residential areas, and major public facilities are also improving.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.20-29
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• 2006

Modeling urban climate caused by land use conversion is critical for human welfare and sustainable development, but has hampered because detailed information on urban characteristics is hard to obtain. With the advantage of satellite observations and the new statistical boundary system, this paper measures the economic and environmental effects of green area loss due to land use conversion in urban areas. To perform this purpose, data were collected from the various sources basic statistical unit data from the National Statistical Office, digital maps from the National Geographic Information Institute, satellite images, and field surveys when necessary. All data (maps and attributes) are built into the geographic information system (GIS). This paper also utilizes Landsat TM 5 imagery of Daegu city to derive vegetation index and to measure average surface temperature. The satellite data were examined using standard image processing software, ERDAS IMAGINE, and the results of the digital processing were presented with ARCVIEW(v.3.3). SAS package was used to perform statistical analyses. This study presents that there exists a strong relationship between land use change and climatic change as well as land price change. Based on results of the analysis, this paper suggests that planners should implement effective tools and policies of urban growth management to detect environmental quality and to make right decisions on policies concerning smart urban growth.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.38-47
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• 2002

This paper demonstrates a regional analysis of landslide occurrence potential by applying geographic information system to the Kumi City selected as a pilot study area. The estimate criteria related to natural and humane environmental factors which affect landslides were first established. A slope map and a aspect map were extracted from DEM, which was generated from the contour layers of digital topographic maps, and a NDVI vegetation map and a land cover map were obtained through satellite image processing. After the spatial database was constructed, indexes of landslide occurrence potential were computed and then a few landslide-potential areas were extracted by an overlay method. It was ascertained that there are high landslide-potential at areas of about 30% incline, aspects including either south or east at least, adjacent to water areas or pointed end of the water system, in or near fault zones, covered with medium vegetable. For more synthetic and accurate analysis, soil data, forest data, underground water level data, meteorological data and so on should be added to the spatial database.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.3
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• pp.173-183
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• 2006

Purpose of this study was to estimate of soil erosion, which is related with crop productivity and water quality in watershed, in Seonakdong river watershed using USLE. The data set for USLE estimation were derived from detailed digital map(K factor), satellite imagery(C and P factors) and DEM(LS factor). The R factor was calculated by AWS data from Kimhae agricultural technology center. The soil loss from arable land was equivalent of 31.5% of total soil loss in Seonakdong river watershed. The soil loss amount of paddy field and upland were 2.8% and 97.2% of arable land, respectively, even in the area where paddy field was occupied much largely as 76.3%. The reason of large amount of soil loss from upland was that 30.4% of upland was distributed at "severe" and "very severe" soil erosion grade in watershed. The distribution of soil erosion grade during cropping season(May-Sept.) was similar to the annual soil loss. Soil erosion of non-cropping season(Oct.-Apr.) was small due to a low R factor. But, soil erosion grade of near mountain footslope areas showed severe and very severe even in non-cropping season.

• Spatial Information Research
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• v.18 no.4
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• pp.1-11
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• 2010

Unlike the previous studies which have focused on 2-dimensional urban characteristics, this paper presents statistical models explaining urban heat island(UHI) effect by 3-dimensional urban morphologic information and addresses its policy implications. 3~dimensional informations of Columbus, Ohio arc captured from LiDAR data and building boundary informations are extracted from a building digital map, Finally NDV[ and temperature data are calculated by manipulating band 3, band 4, and thermal hand of LandSat images. Through complicated data processing, 6 independent variables(building surface area, building volume, height to width ratio, porosity, plan surface area) are introduced in simple and multiple linear regression models. The regression models are specified by Box-Tidwell method, finding the power to which the independent variable needs to raised to be in a linearity. Porosity, NDVI, and building surface area are carefully chosen as explanatory variables in the final multiple regression model, which explaining about 57% of the variability in temperatures. On reducing UHI, various implications of the results give guidelines to policy-making in open space, roof garden, and vertical garden management.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.374-380
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• 2012

The k-Nearest Neighbor (kNN) technique is popularly applied to assess forest resources at the county level and to provide its spatial information by combining large area forest inventory data and remote sensing data. In this study, two approaches such as distance-weighting and stratification of training dataset, were compared to improve kNN-based forest growing stock estimates. When compared with five distance weights (0 to 2 by 0.5), the accuracy of kNN-based estimates was very similar ranged ${\pm}0.6m^3/ha$ in mean deviation. The training dataset were stratified by horizontal reference area (HRA) and forest cover type, which were applied by separately and combined. Even though the accuracy of estimates by combining forest cover type and HRA- 100 km was slightly improved, that by forest cover type was more efficient with sufficient number of training data. The mean of forest growing stock based kNN with HRA-100 and stratification by forest cover type when k=7 were somewhat underestimated ($5m^3/ha$) compared to statistical yearbook of forestry at 2011.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.105-117
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• 1998

The main object of this study was to prove the effectiveness of satellite Image data for extraction of the pine needle gall midge damaged area in the part of Kangwon-do area, and to present the detailed procedure of a digital image processing for extraction of those damaged area. The effectiveness of extraction of damaged area was improved by using the BRCT(Backwards Radiance Correction Transformation) with DEM for the normalization of topographic effects. The topographic surface analysis of the extracted damaged area revealed that the general damaged area was at south-west and south-east aspect with the slope of 31 to 38 degrees, the temperature of 21 to 25, and 23% to 39% of the highest altitude mountains. The new damaged area in which expanded area was at 27 to 30 degree of slope, the aspect of 46 to 180 degrees, the temperature of $11^{\circ}C\;to\;12^{\circ}C$ and 27% to 39% of the highest altitude mountains. The NDI(New Damaged Index) was developed using the environment factor and simple vegetation index.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.