• Journal of Korean Society of Rural Planning
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• v.13 no.3
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• pp.103-110
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• 2007

Land development policy in Korea, characterized by its supply-oriented policy, has driven rapid economic development. However, it has a negative impact on the natural environment across the country. Especially, as the introduction of quashi-farmland system with the deregulation of agricultural land development in the late 1990s, numerous unfavorable landscape features such as road, motels and apartment have emerged in the rural area. As those interfered irreversible rural landscapes have been expanded, the demand for well preserved rural landscapes have been increased. The objectives of this study, thus, is to suggest the mitigations between the land development and conservation of natural landscape. As such, this study examines the recognition of current rural landscape management status through 118 students with two groups of landscape architecture majored (50 people) and non-landscape majored (68). Both group express the negative impression of current rural landscape management system in general and they pointed out the major landscape problems are caused from inappropriate land use. However, in detail those two groups respond differently, for example, the first group selected the damaged landscape is the second cause of the landscape problem, while the other group selected the poorly maintained settlements. Based on the analysis of the survey, this study suggests 3 recommendations in order to improve the sustainable rural landscape as establishing the proper rural land use planning system, building local governments' capacity to actively participate in the rural landscape management, and preparing the landscape management plans considering area distinctive characteristics.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.275-284
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• 2001

This study was carried out to evaluate high resolution satellite imagery of IKONOS for classifying the land cover, especially forest type. The IKONOS imagery of 11km$\times$11km size was taken on April 24, 2000 in Bong-pyoung Myun Pyungchang-Gun, Kangwon Province. Land cover classes were water, coniferous evergreen, Larix leptolepis, broad-leaved tree, bare land, farm land, grassland, sandy soil and asphalted area. Supervised classification method with algorithm of maximum likelihood was applied for classification. The terrestrial survey was also carried out to collect the reference data in this area. The accuracy of the classification was analyzed with the items of overall accuracy, producer's accuracy, user's accuracy and k for test area through the error matrix. In the accuracy analysis of the test area, overall accuracy was 94.3%, producer's accuracy was 77.0-99.9%, user's accuracy was 71.9-100% and k and 0.93. Classes of bare land, sandy soil and farm land were less clear than other classes, whereas classification result of IKONOS in forest area showed higher performance than that of other resolution(5-30m) satellite data.

• Journal of Forest and Environmental Science
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• v.30 no.1
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• pp.50-55
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• 2014

DMZ has a lot of natural resources. Also there is very important position as a ecological and geographical. Meanwhile, development schemes and plans were established but that was development to only simple plan such as a tourism and income without communication with local residents. This study was tried to exhibit increasing income of residents in DMZ area using FGI (Focus Group Interview) and SWOT analysis. First of all, analyzed the status of forest resources and carried out a Focus Group Interview targeting residents who live in around DMZ, and then suggest an alternative to increasing income and regional development in Yanggu-gun by SWOT strategies. As a result, realistic plan for achieving regional development is deregulation of the laws related to forest land use conversion for the forest product in DMZ area. Military experts and forest experts have to inspect the area for considering the practical application of the regulation in protected areas directly. National or local government has to effort pursuing future business for regional development through the communication with residents in DMZ area.

• Journal of Korean Society on Water Environment
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• v.39 no.2
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• pp.142-152
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• 2023

Infiltration is a process by which precipitation infuses into subsurface soils. The process determines the surface flow and baseflow volume, and it is one of most important hydrological processes regarding nonpoint source pollution management. Therefore, the Ministry of Environment has developed a guideline to determine the impervious area ratio to understand the hydrological process in administrative districts and watersheds. The impervious area ratio can be determined using land use or land cover maps. Three approaches were explored to determine the impervious area ratio in 25 districts in Seoul. The impervious area ratio was determined by employing the Land registration map and Land property data in the first approach, Land property map in the second approach, and Land cover map in the third approach. The ratio ranged from 38.96% to 83.01% in the first approach, 38.98% to 83.02% in the second approach, and 37.62% to 76.63% in the third approach. Although the ranges did not provide any significant differences in the approaches, some districts displayed differences up to 9.48% by the approach. These differences resulted from the fact that the data were land use or land cover, especially in the area of airport, residential complex area, and school sites. In other words, division of the pervious and impervious areas in an individual plot was not allowed in the Land registration map, while it was allowed in the Land cover map. Therefore, it was concluded that there is a need to revise the guideline so that a reasonable impervious area ratio can be determined in the districts.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.190-200
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• 2022

In this study, the island's land-use and land-cover change (LULCC) is analyzed in South Korea using remotely sensed land cover data(Globeland 30) acquired from 2000 to 2020 to meet the requirement of providing practical information for forest management. Analysis of LULCC between the 2000 and 2020 images revealed that changes to agricultural land were the most common type of change (7.6% of pixels), followed by changes to the forest (5.7%). The islands forests maintain 157,246 ha (42.2% of the total island area). Land cover types that changed to the forest from grasslands were 262 islands, while reverse cases have occurred on 421 islands. These 683 islands have a possibility of transition and disturbance. The artificial land class was newly calculated in 22 islands. The forests, which account for 42.2% of the 22 island area, turned into grassland, and 27.8% of agricultural land and grassland turned into forests. The development of artificial land often affects developed areas and surrounding areas, resulting in deforestation, management of agriculture, and landscaping. This study can provide insights concerning the fundamental data for assessing ecological functions and constructing forest management plans in islands ecosystems.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.351-362
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• 2009

The Soil and Water Assessment Tool (SWAT) model, semi-distributed model, first divides the watershed into multiple subwatersheds, and then extracts the basic computation element, called the Hydrologic Response Unit (HRU). In the process of HRU generation, the spatial information of land use and soil maps within each subwatershed is lost. The SWAT model estimates the HRU topographic data based on the average slope of each subwatershed, and then use this topographic datum for all HRUs within the subwatershed. To improve the SWAT capabilities for various watershed scenarios, the Spatially Distributed-HRU (SD-HRU) pre-processor module was developed in this study to simulate site-specific topographic data. The SD-HRU was applied to the Hae-an watershed, where field slope lengths and slopes are measured for all agricultural fields. The analysis revealed that the SD-HRU pre-processor module needs to be applied in SWAT sediment simulation for accurate analysis of soil erosion and sediment behaviors. If the SD-HRU pre-processor module is not applied in SWAT runs, the other SWAT factors may be over or under estimated, resulting in errors in physical and empirical computation modules although the SWAT estimated flow and sediment values match the measured data reasonably well.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.739-745
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• 2011

The MUSLE was utilized in this study to estimate soil erosion using daily precipitation which was main influential factor in soil loss estimation. Various scenarios were simulated to evaluate how transition of slope, agricultural products and precipitation could affect soil loss in the field. It was found that slope was the most affecting factor in soil loss estimation. Especially 1.8 times the soil loss was expected with potato at 45% slope compared with codonopsis at same slope with MUSLE model. Fortunately, farmers had planted codonopsis at this slope to reduce soil erosion from this steep slope. As shown in this study, the MUSLE method could be utilized to determine optimum crop type for each field with various slope conditions to minimize soil erosion. This approach utilized in this study could be applied to other agricultural watersheds to evaluate various soil erosion conditions.

• Journal of Environmental Impact Assessment
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• v.14 no.5
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• pp.337-346
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• 2005

Pollution load allocation can likely be much controversial, which is essential to formulate the total water pollution load management plan. Existing rules(or guidances) in Korea, can provide no specific criteria for load allocation. Therefore, this paper studied(comprehensively) possible standards how or why to choose any particular allocation method, which was applied in the Gwangju City's load allocation for the satisfaction of set water quality goal. This load allocation is basically focused on the load reduction of domestic wastewater rather than industrial wastewater, because the land-use is strictly regulated and larger sources of pollution are few in the Gwangju City. This paper recommends the city to increase the capacity of sewage treatment plants, promote sewerage maintenance, and set higher effluent standards.

• Journal of Environmental Science International
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• v.33 no.7
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• pp.547-552
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• 2024

Satellite technology has emerged as a powerful tool in modern agriculture, offering capabilities for Earth observation, land-use pattern analysis, crop productivity assessment, and natural disaster prevention. This mini-review provides a concise overview of the applications and benefits of satellite technologies in agriculture. It discusses how satellite imagery enables the monitoring of crop health, identification of land-use patterns, evaluation of crop productivity, and mitigation of natural disasters. Farmers and policymakers can make informed decisions to optimize agricultural practices, enhance food security, and promote sustainable agriculture by leveraging satellite data. Integrating satellite technology with other advancements, such as artificial intelligence and precision farming techniques, holds promise for further revolutionizing the agricultural sector. Overall, satellite technology has immense potential for improving agricultural efficiency, resilience, and sustainability in the face of evolving environmental challenges.