• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.137-153
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• 2016

The price of agricultural products has changed from year to year, the m ajor c ause o f price fluctuation is the imbalance of supply and demand. Materials which are mainly used in korean cabbage production volume is the forecast model, using the cadastral result, slope calculation is impossible to achieved. For this reason, this implies the drastic decrease of prices and the prediction of supply and demand of field crops that is cultivated in a highland slope area, this situation is being repeated. Therefore, the target area of this research is the slopes of high land, by using 2D and 3D Lidar data for the analysis of the cultivated area. Experiment was carried out in the same area to compare the data differences. The rate of change in the area of slope is quantitatively increasing presented by the regression model. An alternative methodology that can improve the reliability of the calculated slope area using 2D is through cadastral map.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.64-75
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• 2008

Since the current database systems for managing geotechnical investigation results were limited by being described boring test result in point feature, it has been trouble for using other GIS data. Although there are some studies for spatial characteristics of subsurface modeling, it is rather lack of being interoperable with GIS, considering geotechnical engineering facts. This is reason for difficulty of practical uses. In this study, we has developed subsurface spatial information model through extracting needed geotechnical engineering data from geotechnical information DB. The developed geotechnical information clustering program(GEOCL) has made a cluster of boring formation(and formation ratio), classification of layer, and strength characteristics of subsurface. The interpolation of boring data has been achieved through zonal kriging method in the consideration of spatial distribution of created cluster. Finally, we make a subsurface spatial information model to integrate with digital elevation model, and visualize 3-dimensional model by subsurface spatial information viewing program(SSIVIEW). We expect to strengthen application capacity of developed model in subsurface interpretation and foundation design of construction works.

• Land and Housing Review
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• v.15 no.4
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• pp.11-20
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• 2024

Building Information Modeling (BIM) is a key technology in the construction industry's digital transformation and is increasingly being utilized in the planning, design, and construction phases. However, BIM application in the maintenance phase remains limited due to various technical constraints. This study proposes a methodology to activate maintenance BIM technology by conducting bridge condition assessments based on standardized procedures utilizing BIM. Several new methods were proposed in the research, such as using an integrated information model by inserting defect elements into a structural model, data linkage between structural members and damage, constructing a database using COBie, and automated condition assessment procedures. The effectiveness of the proposed methodology and the accuracy of condition assessment results were verified by a proof test using a four-span PSC bridge with various types of over 250 damage.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.135-144
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• 2017

The riverbed areas have exposed to various natural disasters and the private use by neighboring residents have caused many problems. The research objectives are to survey the actual situation of riverbed areas in order to prevent landscape damage and private use. Drone and photogrammetry, orthophoto, DSM(Digital Surface Model), digital topographic map and cadastral information have been integrated by GIS technology. The flood and disaster vulnerable area has been surveyed and the land use and private use has been analyzed using cadastral information. The research results show that the analyzed data can be used for providing foundation data for management of river and also can be used for surveying actual situation of private use on the riverbed areas.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Spatial Information Research
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• v.13 no.1 s.32
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• pp.1-17
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• 2005

This paper draws new guidelines on the current method in Land Suitability Assessment (LSA), enforced to identify potential of parcels .elated to agricultural productivity, preservable value, and economic viability. In order to make recommendations of current LSA methodology, this study analyzes the issues related to the parcel-based LSA and addresses its inappropriateness f3r incorporating characteristics of each parcel. Through case studies and sensitivity analyses using GIS, the results show that (1) the $10\times10m$ grid-based LSA is much better assessment method than parcel-based one, because it gives detailed informations on attributes of each parcel; (2) more than one-distance factor should be taken into account to calculate the appropriate potential measure; and (3) the characteristics of public facilities or urbanized areas including size, density, and land use should be incorporated into the attraction variable of ny Potential model. Finally future research areas are outlined.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.583-598
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• 2015

This paper presents derivation of background temperature from geostationary satellite and its validation based on ground measurements and Geographic Information System (GIS) for future use in weather and surface heat variability. This study only focuses on daily and monthly brightness temperature in 2012. From the analysis of COMS Meteorological Data Processing System (CMDPS) data, we have found an error in cloud distribution of model, which used as a background temperature field, and in examining the spatial homogeneity. Excessive cloudy pixels were reconstructed by statistical reanalysis based on consistency of temperature measurement. The derived Brightness temperature has correlation of 0.95, bias of 0.66 K and RMSE of 4.88 K with ground station measurements. The relation between brightness temperature and both elevation and vegetated land cover were highly anti-correlated during warm season and daytime, but marginally correlated during cold season and nighttime. This result suggests that time varying emissivity data is required to derive land surface temperature.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.2
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• pp.73-86
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• 2000

Using monthly AVHRR-NDVI composite images, global vector data and statistical information, land cover change patterns in Asia during the major growing season (June, July and August) were analyzed for each country. Specifically, explanations on NDVI changes were developed at a regional scale emphasizing human impacts on ground vegetation. The annual mean change in each country showed NDVI-gain trends in high latitude areas and some parts of eastern China and northern/western India. On the contrary, NDVI-loss trends were distinctive in Japan, Korea, some parts of southeastern China, Vietnam, Laos, Cambodia, Thailand, Myanmar and some parts in southwestern/eastern India. These patterns largely coincided with socio-economic information reflected by human behavior. The NDVI change trends showed significant correlation with forest area changes. Also, a multiple regression model showed that the NDVI change patterns were significantly dependent on the changes in forest area and total population.

• Journal of Ecology and Environment
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• v.33 no.4
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• pp.377-389
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• 2010

Understanding the factors relevant to endangerment and the patterns of habitat locations in relation to protected areas is critically important for the conservation of rare species. Although 64 plant species have recently been listed as endangered species in Korea, this information has, until now, not been available, making appropriate management and conservation strategies impossible to devise. Thus, we collected information on potentially threatening factors, as well as information on the locations in which these species were observed. The potentially threatening factors were classified into seven categories. National parks, provincial parks, ecosystem conservation areas, and wetland conservation areas were defined as protected conservation areas. Korean digital elevation model data, along with the maps of all protected areas were combined with the maps of endangered plant species, and analyzed via Geographic Information Systems (GIS). Excluding the category of "small population", endangered plant species in Korea were associated more frequently with extrinsic factors than intrinsic factors. Considering land surface only, all conservation areas in Korea totaled 4.9% of the land, far lower than International Union for Conservation of Nature and Natural Resources (IUCN)'s 10% coverage target. At the species level, 69% of the endangered plant species were detected in conservation areas, mostly in national parks. However, this result demonstrates that 31% of endangered species inhabit areas outside the conservation zones. Furthermore, at the habitat level, a large proportion of endangered species were found to reside in unprotected areas, revealing "gaps" in protected land. In the face of rapid environmental changes such as population increases, urbanization, and climate changes, converting these gap areas to endangered species' habitats, or at least including them in habitat networks, will help to perpetuate the existence of endangered species.