• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.75-88
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• 2016

In this study, we used the CLUE-s model to predict the future land-use change based on the urban growth scenario in South Korea. The land-use maps of six classes (water, urban, rice paddy, upland crop, forest, and grass) for the year 2008 were obtained from the Ministry of Environment (MOE), and the land-use data for 5-year intervals between 1980 and 2010 were obtained from the Water Resources Management Information System (WAMIS), South Korea. For predicting the future land-use change, the MOE environmental conservation value assessment map (ECVAM) was considered for identifying the development-restricted areas, and various driving factors as location characteristics were prepared for the model. The predicted results were verified by comparing them with the land-use statistics of urban areas in each province for the year 2008. The prediction error rates were 9.47% in Gyeonggi, 9.96% in Gangwon, 10.63% in Chungbuk, 7.53% in Chungnam, 9.48% in Jeonbuk, 6.92% in Jeonnam, 2.50% in Gyeongbuk, and 8.09% in Gyeongnam. The sources of error might come from the gaps between the development of political decisions in reality with spatio-temporal variation and the mathematical model for urban growth rate in CLUE-s model for future scenarios. Based on the land-use scenario in 2008, the land-use predictions for the year 2100 showed that the urban area increased by 28.24%, and the rice paddy, upland crop, and forest areas decreased by 8.27, 6.72, and 1.66%, respectively, in South Korea.

• Journal of the Korean GEO-environmental Society
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• v.7 no.3
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• pp.5-19
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• 2006

The secondary consolidation settlement of soft clay is generally very little compared to the total settlement and occurs very slowly during long-term period. However the secondary consolidation settlement is comparatively large amount in organic and heavily compressed clay and is a very important engineering factor. In order to reduce residual settlements in reclaimed soft ground, the preloading method is often used. In this study, in order to determine reasonable long-term settlements of large reclaimed site, laboratory incremental loading consolidation tests and surcharging consolidation tests are performed. Sampling was done at Incheon area of west coast and Gwangyang area of south coast in Korea. The characteristics of secondary consolidation have obtained through laboratory tests and analyzed systematically to predict long-term settlements. Additionally, the location data and laboratory test results are correlated by using GIS(geographic information system). The secondary consolidation settlement of the site was predicted based on D/B and the operation technique and estimation technique of space of GIS.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.59-77
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• 2003

This study is to validate the use of macro language for the land suitability analysis aiming to help to resolve land use conflicts. The silver-town suitability analysis is conducted on the Geejang Gun, Busan Metropolitan city. Such digital maps as terrain, road, facility, and water body were created for various cartographic models. A cartographic model identified the best suitable areas for silver-town development based on the such site selection variables as a distance to facility and road, slope and aspect of terrain, land use etc. Then, the other cartographic model identified the most favorable site among the candidate sites based on the comparison of the aspect of proximity, usage and environmental quality. Macro language was used for these modeling process and was used for the manipulation of all these spatial variables used in the models to resolve land use conflicts relating to the decision making process of the final site selection. This study will improve the effectiveness and rationality of the traditional site suitability analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.21-35
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• 2020

Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.1-14
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• 2017

A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.2
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• pp.27-37
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• 2001

Using satellite image and GIS, spatial distribution characteristics of black locust forest as honey plant area was identified and analyzed. Upon the result, the most suitable area for black locust forest was selected through the integration analysis of transparent overlay. The variables used for spatial analysis such as topography(elevation, aspect, slope), soil, drainage, distance from urban area, land use, meteorological elements were considered. Based on the suitability analysis, it was clarified that the integration of linear and factor combination technique is greatly efficient method for the most suitable area. In addition, Gokung, Imgo, Chungtong, Hwanam area were shown to be suitable in Young-chun Area. As the result of suitability analysis for honey plant area of black locust in Young-chun using satellite image and GIS, the present portion of potential distribution area was produced about 42.53%. The portion of most suitable area for honey plant area of black locust was about 26.77%. Finally, the total area for honey plant area of black locust in Young-chun came up to $15.79km^2$. Additionally, satellite image and GIS were expected to be significant tools for suitability analysis of honey plant complex area.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.481-490
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• 2018

Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.122-131
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• 2007

This study estimates how soil loss in a basin has been occurred according to the change of land cover, and analyzes which type of land cover has the largest soil loss by classifying the land-cover type into each area and a whole basin. Musimcheon, the second branch stream of GeumGang, is chosen as a research area. The result of analysis shows that the average soil loss occurs most largely in a crop land and a paddy field. The yearly soil loss of watershed estimates approximately 14,000 ton/yr in case of using 100-year-frequency rainfall data. A forest area, which takes the largest area in watershed, shows the soil loss occurs approximately 1,000ton/yr. A crop field shows that soil loss increased most largely 4,900 ton/yr (34.6%) in 1985 to 8,100 ton/yr (56.1%) in 2000. The change of land cover in a crop land increased 8% to 14%, and this change influences on the increase of soil loss. As a result of analyzing the area over $200ton/km^2/yr$, the soil loss in a crop field accounts for 74% to 96%.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.132-147
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• 2008

So far ubiquitous service (u-service) priority has seldom been empirically examined based on the customer's view. It is usual to prioritize the relative importance of u-service variables by the supplier's intuition and a few specialist's experienced knowledge. Such approaches have the disadvantage that they provide only limited empirical information on the field practices in relation to u-service since customer demand of u-service is poorly defined despite abundant interest in this problem. Therefore, the aim of this research was to develop u-service priority model in the context of multi-criteria framework integrating customer and supplier's view, using high technology acceptance theory as major controlling factors. An important question was how to measure or represent criteria that is important to u-service and should be included in a priority model. The selection criteria for the model variables were derived from high technology acceptance theory and AHP approach through the analysis of frequency count, elimination of overlapping factors and brainstorming with specialists. Daegu showed top-rankings in transportation-aid service, guidance service for the eyesight disabled and u-telematics service. In contrast, disaster prevention service and industrial specialized town service ranked highly in the typical supplier's approach were not a dominant determining factor in the u-service priority. The model identified the fact that typical high priority service in terms of supplier's view did not necessarily accompany the important predictor for the u-service priority.