• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.1
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• pp.29-37
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• 1999

Land cover classification is an essential basic information in natural environment management; however, land cover classification studies in Korea have not yet been proceeded to a sufficient level. At the present, only a limited number of the precedent studies that only cover definite city area has been conducted. Furthermore, there is almost no research conducted on the land cover classification schemes that could accurately classify the Korea's land cover conditions. This study primarily focuses on the land cover classification scheme which carries the most urgent priority in order to classify and to map out the Korean land cover conditions. In order to develop the most suitable land cover classification scheme, many foreign land cover classification cases and projects that are being carried out were reviewed in depth. The land cover classification scheme this study proposes comprises 3 levels : The first level consists of 7 different classes; the second level consists of 22 different classes; and the third level is made up of 50 classes. The land cover classification map will serve many important roles in natural environment management, such as the conjecture of natural habitats and estimation of oxygen production or carbon dioxide absorption capability of a forest. In water pollution modelling, the land cover classification data can be used to estimate and locate non-point sources of water pollution. If applied to a watershed, modelling it will allow to estimate the total amount of pollution from non-point sources of pollution in the water shed. The land cover classification data will also be good as a barometer data that determines defusion of air pollutants in air pollution modelling.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.3
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• pp.103-119
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• 2016

This study aims to assess habitat feature on the large-scale spawning ground of the Boreal Digging Frog Kaloula borealis in Daemyung retarding basin of Daegu, and to analyze the relationships between species abundance and meteorological factors for each habitat. Fifty-seven(57) pitfalls were installed to collect species abundance of 4 survey regions, and high-resolution satellite image, soil sampling equipment, digital topographic map, and GPS were used to develop habitat features such as terrain, soil, vegetation, human disturbance. The analysis shows that the frog is most abundant in sloped region with densely herbaceous cover in southern part of the retarding basin. In the breeding season, lowland regions, where Phragmites communis and P. japonica dominant wetlands and temporary ponds distributed, are heavily concentrated by the species for spawning and foraging. Located in between legally protected Dalsung wetands and lowland regions of the retarding basin, riverine natural levee is ecologically important area as core habitat for Kaloula borealis, and high number of individuals were detected both breeding and non-breeding seasons. Temperate- and pressure-related meteorological elements are selected as statistically significant variables in species abundance of non-breeding season in lowland and highland regions. However, in sloped regions, only a few variables are statistically significant during non-breeding season. Moreover, breeding activities in sloped regions are statistically significant with minimum temperature, grass minimum temperature, dew point temperature, and vapor pressure. Significant meteorological factors with habitat features are effectively applied to establish species conservation strategy of the retarding basin and to construct for avoiding massive road-kills on neighboring roads of the study sites, particularly post-breeding movements from spawning to burrowing areas.

• Journal of the Korean Geographical Society
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• v.37 no.5
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• pp.511-521
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• 2002

Coastal sand dunes in West coast of Korea are under stress. Due to the newly constructed Seohaean(West Coast) Highways, the number of visitors and the anthropogenic pressures will keep rising in near future. Sea level rise due to the global warming may cause a lot of damage to the natural resources and residents of coastal area. Therefore, many countries including United States are doing nationwide coastline survey using highly sophisticated methodology. In this study, high resolution IKONOS satellite images along with aerial photographs taken since 1960's have been sequentially analyzed using GIS software (Erdas Imagine 8.3). Onsite monitoring has been performed at the 31 measuring points in 10 beaches since the May of 2001 in order to measure the sand budget. Post-construction monitoring after installation of sand fences is also being done on sites regularly. Restoration works seem to be effective at this moment.

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.205-211
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• 2014

Focused on Mt. Bogdkhan nature reserve in Mongolia, this study was conducted as a fundamental research to discover a tendency and characteristics of forest damage and to draw up measures for proper plans of forest restoration through an analysis of year-to year change using satellite images. In specific, land cover mapping was conducted by using Landsat images from 1994 to 2011, and then year-to year change was analyzed to investigate the features of forest damage in Mt. Bogdkhan. The results showed that the whole area of a reservation in Mongolia in 2011 was about $416.89km^2$; among them, forest area was $167,87km^2$, accounting for about 40.3%, followed by bare patch and grassland area (58.6%) and urban dry area (1.1%). In particular, compared in 1994, the area of forest in 2011 has increased by $6.12km^2$; while bare patch and grassland area has decreased by $10.81km^2$. Primary causes of forest degradation occurred in Mt. Bogdkhan nature reserve included illegal logging for fuel, forest and grassland degradation caused by domestic animals grazing, man-made forest fire, and disaster caused by insect pest.

• Journal of Ecology and Environment
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• v.29 no.5
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• pp.445-452
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• 2006

The number of species and forest area has decreased as urbanization is progressed. The landscape degradation was examined by analyzing vegetation map, satellite image and characteristics of actual vegetation. The study was conducted in Mt. Baekja and its surroundings located on Gyeongsan city, southeastern Korea. As the result of landscape analysis, agricultural field was a characteristic attribute of the study area. Lowlands of this study area were occupied by agricultural field and various plantations. For 15 years from 1987 to 2002, forest area decreased from 2,072.9 ha to 1,853.2 ha, and shape index and fractal dimension of vegetation patches increased from 1.32 to 1.65 and from 1.05 to 1.09, respectively. Pinus densiflora Siebold & Zucco. community showed the highest species diversity, whereas Larix kaempferi (Lamb.) Carriere community showed the lowest species abundance. As forest management implications, monitoring of endangered plant species (Jeffersonia dubia (Maxim.) Benth. & Hook.f. ex Baker & S.Moore), and restoration of lowland forest from plantation to natural forest were discussed. Further, establishment of greenways utilizing existing streams, roadside, and public facilities were recommended.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.423-432
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• 2018

Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.761-777
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• 2016

This study is to suggest landform and environmental problems of border region of N. Korea and China by analyzing results of field work for the Dumangang and the Amnokgang from year 2000 up to year 2016. By the social system in North korea, access of study material is possible with satellite image and published statistical data, but impossible direct data collection. We gathered field work data on landform and environment in border Region of N. Korea and China. Before field survey, we analysed geometrical landform and geology using DEM and digital geology map. We analyzed landform and environmental problems occurring in upper, midstream, and downstream region of the Dumangang and the Amnokgang using field work data. Resultingly, this study will be expected to support as basic data for resonable management on natural resources and empirical research activities on North Korea.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.558-568
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• 2021

Poor supervision and tourism activities have resulted in forest degradation in islands in Korea. Since the southern coastal region of the Korean peninsula was originally dominated by warm-temperate evergreen broad-leaved forests, it is desirable to restore forests in this region to their original vegetation. In this study, we identified suitable areas to be restored as evergreen broad-leaved forests by analyzing the environmental factors of existing evergreen broad-leaved forests in the islands of Jeollanam-do. We classified forest lands in the study area into six vegetation types from Sentinel-2 satellite images using a deep learning algorithm and analyzed the tolerance ranges of existing evergreen broad-leaved forests by measuring the locational, topographic, and climatic attributes of the classified vegetation types. Results showed that evergreen broad-leaved forests were distributed more in areas with a high altitudes and steep slope, where human intervention was relatively low. The human intervention has led to a higher distribution of evergreen broad-leaved forests in areas with lower annual average temperature, which was an unexpected but understandable result because an area with higher altitude has a lower temperature. Of the environmental factors, latitude and average temperature in the coldest month (January) were relatively less contaminated by the effects of human intervention, thus enabling the identification of suitable restoration areas of the evergreen broad-leaved forests. The tolerance range analysis of evergreen broad-leaved forests showed that they mainly grew in areas south of the latitude of 34.7° and a monthly average temperature of 1.7℃ or higher in the coldest month. Therefore, we predicted the areas meeting these criteria to be suitable for restoring evergreen broad-leaved forests. The suitable areas cover 614.5 km², which occupies 59.0% of the total forest lands on the islands of Jeollanamdo, and 73% of actual forests that exclude agricultural and other non-restorable forest lands. The findings of this study can help forest managers prepare a restoration plan and budget for island forests.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.135-148
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• 2015

This research is carried out for the land cover change detection in the Nakdong River basin before and after the 4 major rivers restoration project using the LiDAR DEM(Digital Elevation Model) and the multi-temporal Landsat imagery. Firstly the river basin polygon is generated by using the levee boundaries extracted from the LiDAR DEM, and the four river basin imagery are generated from the multi-temporal Landsat-5 TM(Thematic Mapper) and Landsat-8 OLI(Operational Land Imager) imagery by using the generated river basin polygon. Then the main land covers such as river, grass and bare soil are separately generated from the generated river basin imagery by using the image classification method, and the ratio of each land cover in the entire area is calculated. The calculated land cover changes show that the areas of grass and bare soil in the entire area have been significantly changed because of the seasonal change, while the area of the river has been significantly increased because of the increase of the water storage. This paper contributes to proposing an efficient methodology for the land cover change detection in the Nakdong River basin using the LiDAR DEM and the multi-temporal satellite imagery taken before and after the 4 major rivers restoration project.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.1-14
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• 2019

The 1st Forest Health Management survey was conducted to examine the health of the forests in Korea. However, in order to understand the health of the forests, which account for 63.7% of the total land area in South Korea, it is necessary to comprehensively spatialize the results of the survey beyond the sampling points. In this regard, out of the sample points of the 1st Forest Health Management survey in Gyeongbuk area, 78 spots were selected. For these spots, the species diversity index was selected from the survey sections, and the spatial interpolation method was applied. Inverse distance weighted (IDW), Ordinary Kriging and Ordinary Cokriging were applied as spatial interpolation methods. Ordinary Cokriging was performed by selecting vegetation indices which are highly correlated with species diversity index as a secondary variable. The vegetation indices - Normalized Differential Vegetation Index(NDVI), Leaf Area Index(LAI), Sample Ratio(SR) and Soil Adjusted Vegetation Index(SAVI) - were extracted from Landsat 8 OLI. Verification was performed by the spatial interpolation method with Mean Error(ME) and Root Mean Square Error(RMSE). As a result, Ordinary Cokriging using SR showed the most accurate result with ME value of 0.0000218 and RMSE value of 0.63983. Ordinary Cokriging using SR was proven to be more accurate than Ordinary Kriging, IDW, using one variable. This indicates that the spatial interpolation method using the vegetation indices is more suitable for spatialization of the biodiversity index sample points of 1st Forest Health Management survey.