• Spatial Information Research
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• v.18 no.5
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• pp.27-36
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• 2010

This study observed distribution of vegetation to confirm change of tundra-taiga boundary. Tundra-taiga boundary is used to observe the transfer of vegetation pattern because it is very sensitive to human activity, natural disturbances and climate change. The circumpolar tundra-taiga boundary could observe reaction about some change. Reaction and confirmation about climate change were definite than other place. This study used Leaf Area Index(LAI) 8-Day data in August from 2000 to 2009 that acquire from Terra satellite MODerate resolution Imaging Spectroradiometer(MODIS) sensor and used K$\"{o}$ppen Climate Map, Global Land Cover 2000 for reference data. This study conducted analysis of spatial distribution in low density vegetated areas and inter-annual / zonal analysis for using the long period data of LAI. Change of LAI was confirmed by analysis based on boundary value of LAI in study area. Development of vegetation could be confirmed by area of grown vegetation($730,325km^2$) than area of reduced vegetation ($22,372km^2$) in tundra climate. Also, area was increased with the latitude $64^{\circ}$ N~$66^{\circ}$ N as the center and around the latitude $62^{\circ}$ N through area analysis by latitude. Vegetation of tundra-taiga boundary was general increase from 2000 to 2009. While area of reduced vegetation was a little, area of vegetation growth and development was increased significantly.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.1
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• pp.45-64
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• 2014

This study was carried out to offer the ecological data for restoring and maintaining a local stream by analyzing the vegetation and flora in Geumsan Stream and Gisa Stream, Geumsan-gun, Chungcheongnam-do, Korea. As a result of comparison of realities of land use near Geumsan Stream and Gisa Stream, in Geumsan Stream, the ratio of residential areas, commercial and business places, and places of transportation facilities was high. With these types of land use aggregating densely in the center, farmlands were formed on both sides. On the other hand, in Gisa Stream, farmlands were distributed evenly in all sections. As a result of comparison of flora of the two streams, Geumsan Stream had a total of 166 taxons including 53 families, 131 genuses, 139 species, 23 varieties, and 4 forms, and Gisa Stream had a total of 142 taxons including 42 families, 111 genuses, 116 species, 21 varieties, and 5 forms. As a result of calculation of the Naturalization Index and Urbanization Index, the indices were analyzed to be 23.5% and 12.1% in Geumsan Stream and to be 21.8% and 9.7% in Gisa Stream, respectively. Hence, Geumsan Stream showed higher figures in both evaluation indices than those of Gisa Stream. In addition, as a result of calculation of the Actual Urbanization Index, which is the index supplemented by considering the species pool and area, it could be known that Geumsan Stream (0.0285) was urbanized more than Gisa Stream (0.0107) by about 2.7 times. A total of 18 plant communities were classified in Geumsan Stream and Gisa Stream. In Geumsan Stream, 14 vegetation types were identified, and it was analyzed that there are various vegetation types including Phalaris arundinacea community, Zoysia japonica community, Phragmites japonica-Phalaris arundinacea community, etc. evenly distributed. 11 vegetation types were identified in Gisa Stream, and it was examined that Phragmites japonica community is widely distributed in all sections.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1975-1984
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• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.161-161
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• 2021

본 연구에서는 금강 상류의 용담댐 유역(930.0 km²)을 대상으로 Sentinel-1 SAR(Synthetic Aperture Radar) 및 Sentinel-2 MultiSpectral Instrument(MSI) 위성영상을 활용한 토양수분 산출연구를 수행하였다. 연구에 사용된 자료는 10 m 해상도의 Sentinel-1 IW(Interferometric Wide swath) mode GRD(Ground Range Detected) product의 VV(Vertical transmit-Vertical receive) 및 VH(Vertical transmit-Horizontal receive) 편파자료와 Sentinel-2 Level-2A Bottom of Atmosphere(BOA) reflectance 자료를 2019년에 대해 각 6일 및 5일 간격으로 구축하였다. 위성영상의 Image processing은 SNAP(SentiNel Application Platform)을 활용하여 Sentinel-1 영상의 편파 별(VV, VH) 후방산란계수와 Sentinel-2의 적색(Band-4) 및 근적외(Band-8) 영상을 생성하였다. 토양수분 산출 모형은 다중선형회귀모형(Multiple Linear Regression Model)을 활용하였으며, 각 지점에 해당하는 토양 속성별로 모형을 생성하였다. 모형의 입력자료는 Sentinel-1 위성의 편파별 후방산란계수, Sentinel-1 위성에서 산출된 식생지수 RVI(Radar Vegetation Index)와 Sentinel-2 위성에서 산출된 NDVI(Normalized Difference Vegetation Index)를 활용하여 식생의 영향을 반영하고자 하였다. 모의 된 토양수분을 검증하기 위해 6개 지점의 TDR(Time Domain Reflectometry) 기반 실측 토양수분 자료를 수집하고, 상관계수(Correlation Coefficient, R), 평균제곱근오차(Root Mean Square Error, RMSE) 및 IOA(Index of Agreement)를 활용하여 전체 기간 및 계절별로 나누어 검증할 예정이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.20-38
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• 2014

Vegetation phenology is the most important indicator of ecosystem response to climate change. Therefore it is necessary to continuously monitor forest phenology. This paper analyzes the phenological characteristics of forests in South Korea using the MODIS vegetation index with error from clouds or other sources removed using the HANTS algorithm. After using the HANTS algorithm to reduce the noise of the satellite-based vegetation index data, we were able to confirm that phenological transition dates varied strongly with altitudinal gradients. The dates of the start of the growing season, end of the growing season and the length of the growing season were estimated to vary by +0.71day/100m, -1.33day/100m and -2.04day/100m in needleleaf forests, +1.50day/100m, -1.54day/100m and -3.04day/100m in broadleaf forests, +1.39day/100m, -2.04day/100m and -3.43day/100m in mixed forests. We found a linear pattern of variation in response to altitudinal gradients that was related to air temperature. We also found that broadleaf forests are more sensitive to temperature changes compared to needleleaf forests.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.103-109
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• 2007

To investigate the effects of artificial vegetation island (AVI) on fish distribution, we compared fish fauna from artificial vegetation island (AVI) area, which installed in 2000, natural vegetation area (NVA) and vegetation-free area (VFA) at Kyungan Stream area of Lake Paldang from Jul. to Nov., 2005. Results showed that 11 families 23 genera 24 fish species were distributed in the AVI and NVA. Squalidus japonicus coreanus, a small-size fish which generally lives at the downstream, dominated absolutely in the individual numbers. However, only 6 families 11 genera 12 species of fishes caught at the VFA, and dominant fishes were Hemibarbus labeo and Erythroculter erythropterus, a medium to large-size migratory fishes which live in mid-depth of water column. The dominance index was high at the AVI (0.778) and NVA (0.868), whereas the diversity index and evenness index were high at the VFA. Fish distribution at AVI was similar to that of the NVA in numbers of species, indicating that the AVI could playa role as spawning and inhabitation zone to a variety of fishes. We believe that AVI may be used for a restoration of the damaged and disturbed littoral ecosystem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.211-221
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• 2021

The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.

• Journal of Environmental Impact Assessment
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• v.4 no.2
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• pp.71-91
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• 1995

In order to develop an appropriate set of criteria applicable for environmental impact assessment (EIA) of natural forest 8 items are proposed. The criteria are vegetation distribution area (DA), distribution pattern (DP), size (S), diameter of breast height of tree (DBH), humus (H), sustainment (ST), successional stage (SS) and impact of adjacent ecosystem (IAE), Each criterion has an interval which minimum 1 score to maximum 5 score Forest Evaluation Index (FEI) was obtained as the sum of 8 criteria value. Above 70% is considered to be absolutely conservative and from 50% to 70% range of total score is to be considered conservative. In the case of the Sancho˘ng Pumping-up Power Plant of Mt. Chiri, 8 criteria were applied base on actual vegetation map. Pinus densiflora community got 73%(29 scores) and Quercus variabilis - Q. serrata community got 60%(24 scores). This may be said that this local vegetation has high ecological potentiality. These criteria cannot always be absolutely evaluation tool. So it is expected to take the more time to be developed further, and holistically added by the other field such as fauna, geological feature etc.

• Spatial Information Research
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• v.4 no.1
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• pp.13-20
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• 1996

This study has been on detection of land-cover change on Korean peninsula (including the area of north Korean territory) between May of 1990 year and that of 1995 year using NOAA AVHRR data. It was necessary that imagery data should be registered to each other and should not be deviated much in seasonal variation in order to recognize land - cover change. Atmosphic effect such as clould and dirt was erased by maximum NDVI(Normalized Difference Vegetation Index) method the equation of which was as following $$NDVI(i,j,d)=\frac{ch2(j,j,d)-ch1(i,j,d)}{ch2(i,j,d)+ch1(i.j,d)}$$ Each image of maximum NDVI of '90 year and '95 year was c1assifed onto 8 categories ,using iso-clustering method each of which was water, wet barren and urban, crop field, field, mixed vegetation, shrub, forest and evergreen.