• Korean Journal of Heritage: History & Science
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• v.43 no.1
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• pp.100-117
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• 2010

This study analyzed vegetation structure of natural monuments Koelreuteria paniculata community in search of a conservation and management plan. Plant sociological analysis of Koelreuteria paniculata community indicates that it can be classified into Achyranthes japonica subcommunity and Rhodotypos scandens subcommunity and Trachelospermum asiaticum var. intermedium subcommunity. While Koelreuteria paniculata community of Ahnmyeondo is composed of sub tree layer and herb layer, those of Pohang and Wando are composed of tree layer, Sub tree layer, shrub layer, herb layer. The results of tree vitality analysis showed that those in Ahnmyeondo appeared to be relatively low when compared to those in Pohang and Wando-gun. This can be understood in two different aspects: disease and insects vulnerability due to a relatively simple structure and lack of competitive species, and decreased vitality / natural branch losses due to crown competition arising from high density. The result of soil characteristics analysis showed that soil texture, soil pH, organic matter, $p_2O_5$, exchange positive ion were sufficient for tree growth while total nitrogen was not, so that discretion would be needed for fertilizer application. As there were damages of disease and inscet, but only for 10~15% of the entire area; it still requires consistent preconsideration. The study suggests the management methods for preservation of Koelreuteria paniculata community. First, securing designated areas is necessary in order to minimize environment deterioration due to surrounding development. Especially, for sections with decreased areas, expansion of designated areas through land purchase should also be considered. Second, artificial interference may affect the livestock. Therefore, monitoring of artificial interference is necessary, based on which protection projects must be conducted. Third, from analysis of young plants which influence the maintenance mechanisms of Koelreuteria paniculata community, a decrease compared to the prior year was observed; investigation is needed. Therefore, an active management policy through status examination of livestock such as germination and young plants is necessary.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.28-37
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• 2008

In this study, we perform land surface monitoring of NDVI (Normalized Difference Vegetation Index) variation by using remote sensing data during 1999-2005 over North Korea, which can't easily access to measure directly land surface characteristics due to one of the world's most closed societies. North Korea forest region has most abundant forest vegetation - so called Lungs of Korea in the Korea peninsula. NDVI represents vegetation activity used in many similar studies. In this study, we detect vegetation variation and analysis factors of the change over North Korea. By using variation of NDVI, we can infer that effect of drought over North Korea, and reduced vegetation indices by typhoon in North Korea. Land surface type except barren ground with decreased NDVI value is considered as when North Korea region was suffering from drought and typhoon effects, which show lower than mean of 7-year NDVI value. Especially, in recently, the food production of North Korea with political and economical issues can be inferred indirectly these trends by using estimated output data from this study.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.69-76
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• 2007

Kangwondo area is mountainous and landslide is easily happened easily during the rainy period in summer time. Especially, when there is torrential downpour caused by the unusual weather change, there will be greater possibility to see landslide. Another reason behind landslide is the continuous forest fire in these several years. Since the surface of the earth has been changed by the fire, when rainfall comes, landslide just happens easily. Also, it is reported that landcover condition, excepted rainfall condition, is the most effect for determining landslide susceptibility area. In this study, it is determined a landslide vulnerable area and landcover information is extracted from four satellite image(Landsat TM), about the landslide vulnerable area, which is pictured for each year. And which distribution change is analyzed. also, NDVI picture is made and distribution change of vegetation vitality is analyzed to study that change of landcover have a effect on landslide. As a result, could know that forest and NDVI are decreasing in landslide vulnerable area.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.729-735
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• 2023

The Moderate resolution Imaging Spectroradiometer (MODIS) is a multispectral sensor that has been actively researched in various fields using diverse land and atmospheric products. MODIS was first launched over 20 years ago, and the demand for novel sensors that can produce data comparable to that obtained using MODIS has continuously increased. In this study, land products obtained using the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched in 2011 were introduced, including land surface temperature and vegetation indices such as the normalized difference vegetation index and enhanced vegetation index. These land products were compared with existing data obtained using MODIS to verify their local applicability in South Korea. Based on spatiotemporal monitoring of an extreme drought period in South Korea and the application of VIIRS land products, our results indicate that VIIRS can effectively replace MODIS multispectral sensors for agricultural drought monitoring.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.5
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• pp.77-83
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• 2008

In this study, land cover classification and NDVI evaluation for hazard mitigation precaution are carried out in surrounding areas of Yeongi-gun, Chungcheongnam-do ($132\;km^2$) where a project for multi-functional administrative city is promoted by government. Image acquired from KOMPSAT 2, LANDSAT and ASTER is utilized and comparative evaluation on limitation in classification based on resolution was carried out. The area mainly consists of arable land including mountains, rice fields, ordinary fields, etc thus special attention was paid to the classification of rice fields and ordinary fields. For the classification of image acquired from KOMPSAT 2, segmentation technique for classification of high-resolution image was applied. To evaluate the accuracy of the classification, field investigation was conducted to examine the sample and it was compared with the land usage and classification of land category in land ledger of Korea. Acquired results were made into theme map in shape file format and it would be of great help in decision making of policy for the future-oriented development plan of multi-functional administrative city.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1097-1101
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• 2008

본 연구에서는 SLURP 수문모형을 이용하여 미래기후와 예측된 토지이용자료 및 식생의 활력도를 고려한 상태에서 하천유역의 유출 및 증발산량에 미치는 영향을 분석하였다. 경안천 상류유역($260.04\;km^2$)을 대상유역으로 선정하여 4개년(1999-2002) 동안의 일별 유출량 자료를 바탕으로 모형의 보정(1999-2000)과 검증(2001-2002)을 실시하였다. 모형의 보정 및 검정 결과 Nash-Sutcliffe 모형효율은 0.79에서 060의 범위로 나타났다. 미래 기후자료는 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 A1B 기후변화시나리오의 MIROC3.2 hires, ECHAM5-OM, HadCM3 모델의 결과값을 이용하였다. 먼저 과거 30년 기후자료(1977-2006, baseline)를 바탕으로 각 모델별 20C3M(20th Century Climate Coupled Model)의 모의 결과값을 이용하여 강수와 온도를 보정한 뒤 Change Factor Method로 Downscaling하였다. 미래 기후자료는 2020s(2010-2039), 2050s(2040-2069), 2080s(2070-2099)의 세 기간으로 나누어 분석하였다. 미래 토지이용은 과거 시계열 Landsat 토지이용도를 이용하여 CA-Markov기법으로 예측된 토지이용을 사용하였으며, 미래의 식생정보 예측을 위하여 NOAA/AVHRR 위성영상으로부터 추출된 월별 NDVI(1998-2002)와 월평균기온간의 선형 회귀식을 도출하여 미래의 식생지수 정보를 추정하였다. 모형의 적용결과, 미래기후변화에 따른 연평균 하천유출은 현재보다 최대 2020s는 23.9%, 2050s는 40.7%, 2080s는 39.5% 증가하였다. 봄 강수량 패턴의 변화로 유출량 증가하는 것으로 나타났으며 여름에는 유출량은 감소하고 증발산량은 증가하는 결과를 보였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.33-49
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• 2000

This research demonstrates the application of GIS to the selection of the waste landfill site through the case study of a urban area. The estimation factors for the suitability analysis of the waste landfill site were determined. The database was built through collection, input, and transformation of data. The recent land cover classification data and NDVI data which were obtained through processing of satellite imagery were incorporated into GIS data as estimation factors. The relative weights of importance among 2nd category estimation factors were determined by the pairwise comparison method. Also relative weights of 1st category estimation factors which are divided into the social-economical factor and the natural environmental factor were combined with those of 2nd category estimation factors. As the results of this case study, the suitability analysis was conducted in accordance with various estimation criteria. The highest suitability index was obtained in the case where we considered the relative weights of 2nd category estimation factors as different in the viewpoint which regards the social economical factor as important.

• Korean Journal of Environment and Ecology
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• v.22 no.2
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• pp.119-127
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• 2008

This research managed to establish the space information on incidence factors of landslide targeting Bukhansan National Park and aimed at suggesting a basic data for disaster prevention of a landslide for the period to come in Bukhansan National Park through drawing up the map indicating vulnerability to a landslide and ecological risks by the use of overlay analysis and adding-up estimation matrix analysis methods. This research selected slope angle, slope aspect, slope length, drainage, vegetation index(NDVI) and land use as an assessment factor of a landslide and constructed the spatial database at a level of '$30m\times30m$' resolution. The analysis result was that there existed high vulnerability to a landslide almost all over Uidong and Dobong valleys. As for ecological risks, Dobong valley, Yongueocheon valley, Jeongneung valley and Pyeongchang valley were analyzed to be higher, so it is judged that the impact on a landslide risk should be also considered in time of establishing a management plan for these districts for the time to come.

• Journal of The Geomorphological Association of Korea
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• v.17 no.1
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• pp.1-14
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• 2010

This paper deals with the classification and distribution of geomorphic surfaces and analysis on effects of geomorphic processes on the landforms in the inaccessable DMZ (Demilitarized Zone) to Wonsan Bay of East Sea coast of Chugaryeong Rift Valley, Central Korea. DEM (Digital Elevation Model) and Landsat images are used for the above anlaysis. The geomorphic surfaces are classified by TPI (Topographical Position Index) for the analysis of the convexity and concavity calculated using topographical elements such as elevation, steepness, and relief. In the Chugayreong Valley, 10 geomorphic surfaces are classified as steep valley, shallow valley, upland drainage, U-shaped valley, plain, open slope, upper slope, local ridge, midslope ridge, and high ridge. Zonal Statistics presents average characteristics of geomorphological processes of surfaces by the relationships between bedrock and relief, surface and relief, and between surface and NDVI. So, these analysis can help to understand geomorphological process such as dissection of lava plateau and watershed divide evolution.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.229-239
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• 2019

All vegetation colonies have layered structure. This layer is called 'forest vertical structure.' Nowadays it is considered as an important indicator to estimate forest's vital condition, diversity and environmental effect of forest. So forest vertical structure should be surveyed. However, vertical structure is a kind of inner structure, so forest surveys are generally conducted through field surveys, a traditional forest inventory method which costs plenty of time and budget. Therefore, in this study, we propose a useful method to classify the vertical structure of forests using remote sensing aerial photographs and machine learning capable of mass data mining in order to reduce time and budget for forest vertical structure investigation. We classified it as SVM (Support Vector Machine) using RGB airborne photos and LiDAR (Light Detection and Ranging) DSM (Digital Surface Model) DTM (Digital Terrain Model). Accuracy based on pixel count is 66.22% when compared to field survey results. It is concluded that classification accuracy of layer classification is relatively high for single-layer and multi-layer classification, but it was concluded that it is difficult in multi-layer classification. The results of this study are expected to further develop the field of machine learning research on vegetation structure by collecting various vegetation data and image data in the future.