• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.489-508
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• 2018

As climate changes, it is necessary to predict changes in the habitat environment in order to establish more aggressive adaptation strategies. The bioclimatic classification which clusters of areas with similar habitats can provide a useful ecosystem management framework. Therefore, in this study, biological habitat environment of Northeast Asia was identified through the establishment of the bioclimatic zones, and the impac of climate change on the biological habitat was analyzed. An ISODATA clustering was used to classify Northeast Asia (NEA)into 15 bioclimatic zones, and climate change impacts were predicted by projecting the future spatial distribution of bioclimatic zones based upon an ensemble of 17 GCMs across RCP4.5 and 8.5 scenarios for 2050s, and 2070s. Results demonstrated that significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward, and some zones were predicted to be greatly expanded or shrunk where we suggested as regions requiring intensive management. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.281-291
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• 2000

In this study tree plantation planning for the plantation blocks of Eucalyptus species was constructed in order to apply to the two farms Jangada and Jamaica, where are located in the western district of the state Mato Grosso do Sul in Brazil. At first the satellite photo was analyzed for the land use classification and the forest ecosystem was classified with GIS technique, and then on the basis of this result the planting available area was accounted for the two farms. According to the request of the land owner the planting planning was established for the planting available area for 3 years. The total area for the two farms is 5,301 ha, and the planting available area is estimated to be 3,913ha(74%). The rest area is 1,388ha(26%), and should be classified to the permanent legal reserve forest area. In order to minimize the soil loss and the erosion, the planting blocks were divided according to the parallel to the contour line： for the first planing year the plantation area was divided to the 27 blocks and the total area was 1,308ha, for the second planing year the area also divided to 27 blocks(1,327.4ha) and for the third planning year 30 blocks divided (1276.5).

• Journal of Wetlands Research
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• v.26 no.3
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• pp.245-253
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• 2024

Blue-green algal bloom, or harmful algal bloom has a negative impact on the aquatic ecosystem and purified water supply system due to oxygen depletion in the water body, odor, and secretion of toxic substances in the freshwater ecosystem. This Blue-green algal bloom is expected to increase in intensity and frequency due to the increase in algae's residence time in the water body after the construction of the Nakdong River weir, as well as the increase in surface temperature due to climate change. In this study, in order to respond to the expected increase in green algae phenomenon, an algal bloom forecast system based on hydro-meteorological factors was presented for preemptive response before issuing a algal bloom warning. Through polyserial correlation analysis, the preceding influence periods of temperature and discharge according to the algal bloom forecast level were derived. Using the decision tree classification, a machine learning technique, Classification models for the algal bloom forecast levels based on temperature and discharge of the preceding period were derived. And a algal bloom forecast system based on hydro-meteorological factors was derived based on the results of the decision tree classification models. The proposed algae forecast system based on hydro-meteorological factors can be used as basic research for preemptive response before blue-green algal blooms.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.349-357
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• 2006

The purpose of this study is to evaluate the water pollution degree in the Mid-Nakdong River watershed regarding to landcover types using GIS method. As a result of landcover classification, rate of urban appeared highly on Daegu Metropolitan city. Also, rate of agriculture showed highly in the riparian zones of the Nakdong and Guemho River and rate of forest appeared highly in the borders of the study area. To identify the groups of watershed with similar landcover patterns using the Cluster Analysis. According to the cluster analysis, the fifty sub-watersheds were grouped in three clusters, 'Urban watershed', 'Agriculture watershed', 'Forest watershed'. The proportion of urban area in each cluster had a positive correlation with water pollution degree. Otherwise, the proportion of agriculture in the Agriculture watershed had a high positive correlation with water pollution degree. Therefore, it is necessary to estimate environmental capacity of water duality considering ecological and environmental characteristics of watershed ecosystem and expand water duality monitoring systems to small stream.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.319-328
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• 2014

Dorang - the Korean term for headwater streams - occupy a large portion of the total stream length in a basin, and contribute significantly towards the quantitative and qualitative characteristics, and the ecosystem, of the main river. The Ministry of Environment of South Korea has supported the investigation of the status of Dorang in the nation's four major basins, since 2007. Without a widely accepted academic or legal definition of Dorang, however, there are limits to understand the distribution of Dorang at the national scale and to systematically compile a Dorang database. This paper, through a review of the stream classification system and Korean legal system delineating streams, defines Dorang as 1st and 2nd order streams according to the Strahler ordering method, in a 1:25,000 geographical scale. Analysis of the Geum River basin, with this definition, reveals that the total length of Dorang is 20,622.4 km (73.6% of total stream length), and the number of Dorang catchments is 23,639 (71.3% of the basin area). Further analysis of the geomorphological characteristics of Dorang catchments shows that the average total stream length is 1.1 km, average catchment length is 1.2 km, average drainage area is $0.4km^2$, and average drainage density is 3.08/km.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.303-315
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• 2012

This study developed a wetland inventory describing the characteristics and change of Nakdong estuary wetland ecosystem. The data which are used to develop the inventory are Landsat TM(April 1, 1986; June 23, 1987; June 18, 1997), Kompsat(Jan. 12, 2008) and LiDAR(March 1, 2009) images and published monitoring data of Busan metropolitan city. The developed inventory was utilized for the classification of wetland cover, the spatiotemporal analysis of wetland and landscape pattern, the distribution of benthos species etc. Furthermore, the developed 3 dimensional wetland map showed a better way to delineate wetland boundary and understand wetland dynamics. Considering these results, it's concluded that it is possible to use the similar techniques for the development of wetland inventory in Korea.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.231-238
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• 2002

In this study we classified sediment types of tidal flat using Landsat-5 images. This is for groping the method which can analyze correctly various kinds of sediment faces through satellite images. This work was performed by referencing ground truth of sediment faces which was investigated in the field. With this data we classified Landsat-5 image of 1997's to grope a most suitable classification method. As a result, in case of south Kanghwa island area, it was the optimum way to compound band 4, 5, 7 of Landsat-5 TM imagery. And, this work classified 3 kinds of sediment faces - M(mud), sM(sandy mud) and (g)M(slightly gravelly mud) - in land and mixed water area. It is anticipated that if this method is applied to a image of extremely lower sea level time, it can classify the sediment types of a broad tidal flat area. This is expected to be a beginning of estimating the effect of sediment faces to the change of the tidal flat ecosystem.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.103-114
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• 2012

The purpose of this research is classifying stream into different types depending on various factor from the perspective of stream corridor restoration and using it as basic data, which are used to consider efficient management and planning for the healthy stream according to the characteristic by types. In this study, 130 points of location of the Nakdong river basin which consist of various geographic factors have been chosen and hierarchical cluster analysis has been carried out in these points by using biological and physiochemical factors whose health can be considered to be predicted and evaluated. As a result of cluster analysis, there were three divided types. Type A whose biology and water quality are considered the best was the highest in forest area percentage so that it was classified into natural stream. Type B was classified into a rural region stream with a mixture of urban and agricultural region. Type C, with the most damaged water quality and biology health had the most urban region surface area and was named as urban region stream. Moreover, an overall restoration strategy according to characteristic by stream types was set. By the results of correlation analysis on factors, water quality showed a high correlation with biological properties and was affected by surrounding land usage. In evaluation of streams, it proves the need to consider not only other habitat's geographical and biological factors but also the water quality and land usage factors. There needs to be further research on stream ecosystem functionality factors and structural aspects by using a more objective and total evaluation result in selecting additional index and various other specific classification methods by stream types and its restoration strategies.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.1
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• pp.73-83
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• 2016

Forest degradation reduces ecosystem services provided by forest and could lead to change in composition of species. In North Korea, there has been significant forest degradation due to conversion of forest into terrace fields for food production and cut-down of forest for fuel woods. This study analyzed the phenological changes in North Korea, in terms of vegetation and moisture in soil and vegetation, from March to Octorber 2013, using MODIS (MODerate resolution Imaging Spectroradiometer) images and indexes including NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), and NDWI (Normalized Difference Water Index). In addition, marginal farmland was derived using elevation data. Lastly, degraded terrace fields of 16 degree was analyzed using NDVI, NDSI, and NDWI indexes, and marginal farmland characteristics with slope variable. The accuracy value of land cover classification, which shows the difference between the observation and analyzed value, was 84.9% and Kappa value was 0.82. The highest accuracy value was from agricultural (paddy, field) and forest area. Terrace fields were easily identified using slope data form agricultural field. Use of NDVI, NDSI, and NDWI is more effective in distinguishing deforested terrace field from agricultural area. NDVI only shows vegetation difference whereas NDSI classifies soil moisture values and NDWI classifies abandoned agricultural fields based on moisture values. The method used in this study allowed more effective identification of deforested terrace fields, which visually illustrates forest degradation problem in North Korea.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.