• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.77-86
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• 2012

This study was aim to predict future land-cover changes and to analyze regional land-cover changes in irrigation areas and agricultural reservoir watersheds under climate change scenario. To simulate the future land-cover under climate change scenario - A1B of the SRES (Special Report on Emissions Scenarios), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation to socioeconomic and biophysical driving factors. For the study areas, 8 agricultural reservoirs were selected from 8 different provinces covering all around nation. The simulation results from 2010 to 2100 suggested future land-cover changes under the scenario conditions. For Madun reservoir in Gyeonggi-do, total decrease amount of paddy area was a similar amount of 'Base demand scenario' of Water Vision 2020 published by MLTMA (Ministry of Land, Transport and Maritime Affairs), while the decrease amounts of paddy areas in other sites were less than the amount of 'High demand scenario' of Water Vision 2020. Under A1B scenario, all the land-cover results showed only slight changes in irrigation areas of agricultural reservoirs and most of agricultural reservoir watersheds will be increased continuously for forest areas. This approach could be useful for evaluating and simulating agricultural water demand in relation to land-use changes.

• Journal of Ecology and Environment
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• v.30 no.1
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• pp.39-47
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• 2007

The relationships between the cover of herbaceous species and 15 soil chemical properties (organic carbon contents, total N, available P, exchangeable K, Na, Ca and Mg, HCl-extractable Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in nine poorly controlled waste landfill sites in Korea were examined by correlation analysis and multiple regression equations. Species showed different patterns of correlation between their cover values and soil chemical properties. The cover of Ambrosia artemisiifolia var. elatior, Aster subulatus var. sandwicensis and Erechtites hieracifolia were negatively correlated with the contents of Fe, Mn and Ni within landfill soils. Total cover of all species in quadrats was positively correlated with the contents of Cd and negatively correlated with the contents of Mn and Fe from stepwise regression analysis with 15 soil properties. Canonical correspondence analysis demonstrated that the distribution of native and exotic plants on poorly controlled landfills was significantly influenced by the contents of Na and Ca in soils, respectively.

• Structural Engineering and Mechanics
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• v.61 no.6
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• pp.711-719
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• 2017

This study investigates the effects of reinforcing bar diameter and cover depth on the shrinkage behavior of restrained ultra-high-performance fiber-reinforced concrete (UHPFRC) slabs. For this, twelve large-sized UHPFRC slabs with three different rebar diameters ($d_b=9.5$, 15.9, and 22.2 mm) and four different cover depths (h=5, 10, 20, and 30 mm) were fabricated. In addition, a large-sized UHPFRC slab without steel rebar was fabricated for evaluating degree of restraint. Test results revealed that the uses of steel rebar with a large diameter, leading to a larger reinforcement ratio, and a low cover depth are unfavorable regarding the restrained shrinkage performance of UHPFRC slabs, since a larger rebar diameter and a lower cover depth result in a higher degree of restraint. The shrinkage strain near the exposed surface was high because of water evaporation. However, below a depth of 18 mm, the shrinkage strain was seldom influenced by the cover depth; this was because of the very dense microstructure of UHPFRC. Finally, owing to their superior tensile strength, all UHPFRC slabs with steel rebars tested in this study showed no shrinkage cracks until 30 days.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.3 s.106
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• pp.295-306
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• 2006

In this paper, we proposed and implemented a novel antenna cover mounted over a microstrip path antenna for ultrafast aircraft. A protective antenna cover prevents alteration in the electrical characteristics of the antenna due to environmental conditions. The permittivity of the cover materials should be practically invariable at all operating frequencies. We evaluated the characteristics of the antenna with both simulation and experiment. The experimental results show that the proposed antenna cover can be useful for ultrafast aircraft.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1015-1025
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• 2021

Our research work aimed to evaluate cover crop effects of winter rye on soil characteristics, soil conservation, and yield productivities on potato fields with 15% slope during a fallowed period. There were two controls of bared field without any cultivation and conventional potato cultivation without winter rye. Potato cultivation increased soil pH, organic matter, available phosphate, and exchangeable cation regardless of cover crop cultivation. Sub-soil, particularly, all components of soil chemical properties showed higher value in winter rye cultivation than conventional cultivation. Higher soil density was observed on cover crop cultivation than conventional cultivation resulting from root residues of the cover crop both topsoil and subsoil. Cover crop residues positively affected plant growth and reduced the amount of soil erosion by holding the soil. Although severe soil erosion was seen in conventional cultivation, winter rye cultivation declined soil erosion by 47% during the fallow period on potato slope fields. Distinct soil bacterial communities were detected among treatments and some OTU(Operational Taxonomic Unit)s showed significantly higher abundance in winter rye treatment. Total yield and commercial rate demonstrated no significant differences while higher tuber phosphate, K⁺, and Mg²⁺ contents were observed in winter rye cultivation.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.267-279
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• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.9-17
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• 2014

The Vegetation cover is a significant factor to comprehend characteristics of the ground surface for meterological and hydrological models, which measure energy in the atmosphere or predict the runoff of ground surface. Deardorff introduced vegetation cover fraction to quantitatively comprehend the vegetation cover in 1978. After Deardorff, most of previous researches were conducted on low-resolution or high-resolution images, but only few researches on Landsat that are in medium-resolution images. Therefore, this study aims to investigate a way of calculating the vegetation cover fraction by using NDVI of Landsat images, which were hardly handled previously. For accurate vegetation cover fraction, we compared the evaluated parameters from this study with past vegetation cover fraction parameters that have been calculated for using NDVI of Landsat OLI images. The result of research was shown that NDVI is quite correlated with the vegetation fraction cover in the previous researches. In fact, RMSE of vegetation cover fraction values that obtained through the suggested parameters on this study showed the highest accuracy of 7.3% among all the cases.

• Bulletin of the Korean Mathematical Society
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• v.52 no.3
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• pp.977-986
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• 2015

Let G be a graph on the vertex set $V(G)=\{x_1,{\cdots},x_n\}$ with the edge set E(G), and let $R=K[x_1,{\cdots},x_n]$ be the polynomial ring over a field K. Two monomial ideals are associated to G, the edge ideal I(G) generated by all monomials $x_i,x_j$ with $\{x_i,x_j\}{\in}E(G)$, and the vertex cover ideal $I_G$ generated by monomials ${\prod}_{x_i{\in}C}{^{x_i}}$ for all minimal vertex covers C of G. A minimal vertex cover of G is a subset $C{\subset}V(G)$ such that each edge has at least one vertex in C and no proper subset of C has the same property. Indeed, the vertex cover ideal of G is the Alexander dual of the edge ideal of G. In this paper, for an unmixed bipartite graph G we consider the lattice of vertex covers $L_G$ and we explicitly describe the minimal free resolution of the ideal associated to $L_G$ which is exactly the vertex cover ideal of G. Then we compute depth, projective dimension, regularity and extremal Betti numbers of R/I(G) in terms of the associated lattice.

• Spatial Information Research
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• v.2 no.1
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• pp.47-51
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• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.181-188
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• 2007

The objective of this research was to investigate the optimal land cover classification algorithm for the monitoring of North Korea with MODIS multi-temporal data based on monthly phenological characteristics. Three frequently used land cover classification algorithms, ISODATA1), SMA2), and SOM3) were employed for this study; the land cover categories were forest, grass, agricultural, wetland, barren, built-up, and water body. The outcomes of the study can be summarized as follows. First, the overall classification accuracy of ISODATA, SMA, and SOM was 69.03%, 64.28%, and 73.57%, respectively. Second, ISODATA and SMA resulted in a higher classification accuracy of forest and agricultural categories, but SOM performed better for the built-up area, bare soil, grassland, and water. A possible explanation for this difference would be related to the difference of sensitivity against the vegetation activity. This would be related to the capability of SOM to express all of their values without any loss of data by maintaining the topology between pixels of primitive data after classification, while ISODATA and SMA retain limited amount of data after normalization process. Third, we can conclude that SOM is the best algorithm for monitoring the land cover change of North Korea.