• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Journal of Forest and Environmental Science
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• v.36 no.3
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• pp.199-206
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• 2020

Satchari National Park is one of the most biodiverse forest in Bangladesh and home of many endangered flora and fauna. 206 tons of CO₂ per hectare is sequestrated in this national park every year which helps to mitigate climate issues. As people living near the area are dependent on this forest, degradation has become a regular phenomenon destroying the forest biodiversity by altering its forest cover. So, it is important to map land cover quickly and accurately for the sustainable management of Satchari National Park. The main objective of this study was to obtain information on land cover change using remote sensing data. Combination of unsupervised NDVI classification and supervised classification using maximum likelihood is followed in this study to find out land cover map. The analysis showed that the land cover is gradually converting from one land use type to another. Dense forest becoming degraded forest or bare land. Although it was slowed down by the establishment of 'National Park' on the study site, forecasting shows that it is not enough to mitigate forest degradation. Legal steps and proper management strategies should be taken to mitigate causes of degradation such as illegal felling.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.121-135
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• 2014

Object-based classification methods provide a valid alternative to traditional pixel-based methods. This study reports the results of an object-based classification to examine land cover in the demilitarized zones(DMZs) of Inje-gun. We used land cover classes(7 classes for main category and 13 classes for sub-category) selected from the criteria by Korea Ministry of Environment. The average and standard deviation of the spectrum values, and homogeneity of GLCM were chosen to map land cover types in an hierarchical approach using the nearest neighborhood method. We then identified the distributional characteristics of land cover by considering 3 topographic characteristics (altitude, slope gradient, distance from the Southern Limited Line(SLL)) within the DMZs. The results showed that scale 72, shape 0.2, color 0.8, compactness 0.5 and smoothness 0.5 were the optimum weight values while scale, shape and color were most influenced parameters in image segmentation. The forests (92%) were main land cover type in the DMZs; the grassland(5%), the urban area (2%) and the forests (broadleaf forest: 44%, mixed forest: 42%, coniferous forest: 6%) also occupied mostly in land cover classes for sub-category. The results also showed that facilities and roads had higher density within 2 km from the SLL, while paddy, field and bare land were distributed largely outside 6 km from the SLL. In addition, there was apparent distinction in land cover by topographic characteristics. The forest had higher density at above altitude 600m and above slope gradient $30^{\circ}$ while agriculture, bare land and grass land were distributed mainly at below altitude 600m and below slope gradient $30^{\circ}$.

• Journal of Korean Society on Water Environment
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• v.30 no.4
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• pp.418-428
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• 2014

The purpose of this study is to predict the spatio-temporal changes in land uses and to evaluate land-based pollutant loads in the future under Total Water Pollution Load Management System using CLUE-S model. For these ends, sensitive parameters of conversion elasticities in CLUE-S model were calibrated and these calibrated parameters of conversion elasticities, level II land cover map of year 2009, and 7 driving factors of land use changes were used in predicting future land uses in 2002 with two scenarios(Scenario 1: non area restriction, Scenario 2: area restriction). This projected land use map of 2020 was used to estimate land-based pollutant loads. It was expected that urban areas will increase in 2020 from both scenarios 1 and 2. In Scenario 1, urban areas are expected to increase within greenbelt areas and deforest would be expected. Under Scenario 2, these phenomena were not expected. Also the results of estimation of BOD and TP pollutant loads, the BOD difference between scenarios 1 and 2 was 719 kg/day in urban areas and TP difference was 17.60 kg/day in urban areas. As shown in this study, it was found that the CLUE-S model can be useful in future pollutant load estimations because of its capability of projecting future land uses considering various socio-economic driving factors and area-restriction factors, compared with conventionally used land use prediction model.

• Journal of Korean Society of Rural Planning
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• v.20 no.3
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• pp.201-212
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• 2014

The Farm Revival Program of the Farm Land Bank, implemented in 2006, initiated as the Agricultural Land Bank's business proposal to achieve efficient usage of farm land. Also, expansion of Farm Revival Program will bring positive effects when considering the fact that Farm Revival Program contributes to farm liability issues and management improvements. However, despite the importance of Farm Revival Program, searching for improvement methods through a rural demand survey is very insufficient. The following research limits the target to farms that applied for the management redemption project within Gangwon Province and examined the application motivation, project satisfaction, and demands of the farms. This research holds value as a fundamental data which reflects the demands of farms to better manage Farm Land Purchasing of the Farm Land Bank.

• Journal of Korean Society on Water Environment
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• v.31 no.5
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• pp.543-555
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• 2015

The existing standard for soil erosion risk assessment has limitations in sustainable topsoil management since the fixed criteria are applied to determination of soil erosion risk areas regardless of land use types. It may not be necessary to apply soil erosion best management practices to agricultural areas with high potential of soil erosion because human or economic damage derived from soil erosion might be tiny in that region. Furthermore, the fixed criterion with absolute values can select too many hot spots of soil erosion to conduct efficient soil erosion management. Thus, objective of this study was to suggest the relative criteria using statistical analysis for efficient soil erosion management. In future, the relative indices for soil erosion prevention should be improved to provide a priority of soil erosion management considering economic damage from soil erosion or functional values of soil with quantitative soil erosion. Additional researches will be needed to reflect a regional characteristics and to consider various land use types and different criteria.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.405-412
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• 2011

Increased Non-permeable areas which have resulted from civilization reduce the volume of groundwater infiltration that is one of the important factors causing water shortage during a dry season. Thus, seeking the efficient method to analyze the volume of groundwater in accurate should be needed to solve water shortage problems. In this study, two different watersheds were selected and precipitation, soil group, and land use were surveyed in a particular year in order to figure out the accuracy of estimated infiltration recharge ratio compared to Web-based Hydrograph Analysis Tool (WHAT). The volume of groundwater was estimated considering Antecedent soil Moisture Condition (AMC) and Curve Number (CN) using Long Term Hydrologic Impact Assessment (L-THIA) model. The results of this study showed that in the case of Kyoung-an watershed, the volume of both infiltration and baseflow seperated from WHAT was 46.99% in 2006 and 33.68% in 2007 each and in Do-am watershed the volume of both infiltration and baseflow was 33.48% in 2004 and 23.65% in 2005 respectively. L-THIA requires only simple data (i.e., land uses, soils, and precipitation) to simulate the accurate volume of groundwater. Therefore, with convenient way of L-THIA, researchers can manage watershed more effectively than doing it with other models. L-THIA has limitations that it neglects the contributions of snowfall to precipitation. So, to estimate more accurate assessment of the long term hydrological impacts including groundwater with L-THIA, further researches about snowfall data in winter should be considered.

• Journal of Forest and Environmental Science
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• v.40 no.3
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• pp.180-187
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• 2024

Land utilisation for various production practices in rural communities in Nigeria is marked with copious challenges and the management has become unsustainable among the local population. Therefore, the study was conducted to analyse factors influencing land use typologies, LUT among farming households in Akinyele Municipality of Oyo State, Nigeria. The employed a 3-stage sampling procedure for selection of 50 respondents from the study area. Information on demographic characteristics of the respondents, typologies of land use and factors impacting was collected with a structured questionnaire. The analyses of data collected was carried out was with frequencies, percentages and logit regression. The study showed majority (78.0%) were male, aged between 40 and 49 years, married (86.0%) and had secondary education (56.0%). The majority (78.0%) had household size ranging from 4-6 members, engaged in farming (80.0%). Furthermore, the result revealed that 94.0% of respondents conserve existing trees on their farmland, and about 56.0% of them were practicing agroforestry. The major factors affecting land use typologies were outcomes of climate change. The determining factors influencing LUT among farming households were occupation (β=1.829^*), irregular rainfall (β=1.436^*), depleted fruiting (β=1.438^*), poor weather condition/drought (β=1.020^*), and farmers' indigene (β=3.247^*) at α_0.05. The study recommends strengthening of land management policies and stakeholders' engagement in decision making as regards policies actualization to make land use typologies noticeable, effective and pronounce among farming households.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.89-102
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• 2021

Soils in agricultural lands contain large amount of organic matter and nutrients due to the injected fertilizers and manure. During heavy rain, surface water and base runoff pollutants flows into a nearby stream or lake with eroded soil from agricultural lands. On the other hands, agricultural lands near the lake are inundated due to the increase of the water level in the lake, leading to organic matter and nutrient release from the inundated soil. In this study, releasing rates of nutrient salts and organic substances were analyzed for the soil in the agricultural land, where cultivation activities has been carried out and periodically flooded, to account for the possibility of contamination from the inundated agricultural land in reservoir areas The experiment results have shown that COD was released from the soil in anaerobic conditions, and T-P was released in both anaerobic and aerobic conditions. However, in the case of T-N, it was found that the runoff by soil was not made before the rainfall occurred, and when the soil was impound due to rainfall, the elution occurred under the aerobic conditions. Through the results of this study, it was possible to account for the effect of flooded agricultural lands on the water quality in the lake, and this could be reflected in an efficient agricultural non-point pollution management policy. In order to determine the precise releasing rate for each agricultural land, it is believed that the leaching experiment for paddy fields and grasslands are needed.

• Korean Architects
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• s.525
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• pp.52-61
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• 2013