• The Journal of Engineering Geology
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• v.10 no.2
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• pp.215-233
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• 2000

The national geochemical baseline mapping project has been conducted since 1996 to establish a quantitative assessment system for geochemical hazards in natural environments. The geochemical image maps have been edited for thirty-six elements(i.e., 10 major oxides and 26 trace elements) in light sediments, finer fraction than 150 $\mu$m, collected from first- to second-order streams(totally 11,000) over five provinces in the western half(ca. 45,000 km$^2$) of Korea. Natural background values of the elements were given for different geological environments. Based on the statistics, geochemical baselines were newly obtained for a quantitative hazard assessment on toxicity of heavy metals and deficiency of essential nutrients. Some chosen examples of geochemical hazards are presented based on new geochemical image maps and related baseline data.

• Spatial Information Research
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• v.11 no.2
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• pp.185-201
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• 2003

The purpose of this study is to seek the methods of constructing a cultural information system based on GIS. It is impossible for regional culture to be formed apart from its surrounding space, so a study of culture should be based on realizing the features of its space. It is important to note that the elements composing a culture complicatedly interact with each other in their function and continuously change. Also they are interrelated in space and plentiful in their amount. Nevertheless, those studies practised so far in relation to culture and constructing cultural database are too limited in establishing cultural area or community life area required to recognize the regional identity So it is now essential that we should study the methods of cultural expression surpassing objective historical and cultural site maps instead of simple maps depicting historical remains or sites. From this viewpoint, this study tries to find various cultural phenomena in relation to their space through seeking the methods of constructing the cultural database model using XML. In addition, this study tries to construct a base for increasing the utilization of information in making the cultural contents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.273-286
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• 2022

An HD map is essential in the automated driving of level 4 and above to generate the vehicle's global path since it contains road information and each road's lane information. Therefore, all the road elements in the HD map must be correctly defined to construct the correct road network necessary to generate the global path. But unfortunately, it is not difficult to find various errors even in the most recent HD maps. Hence, a preprocessing algorithm has been developed to detect and correct errors in the HD map. This error detection and correction result in constructing the correct road network for use in global path planning. Furthermore, the algorithm was tested on real roads' HD maps, demonstrating its validity.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1294-1294
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• 2024

Flood risk maps are used in urban flooding to understand the spatial extent and depth of inundation damage. To construct these maps, hydrodynamic modeling capable of simulating flood waves is necessary. Flood waves are typically fast, and inundation patterns can significantly vary depending on the terrain, making it essential to accurately represent the terrain of the flood source in flood wave analysis. Recently, methods using UAVs for terrain data construction through Structure-from-Motion or LiDAR have been utilized. These methods are crucial for UAV operations, and thus, still require a lot of time and manpower, and are limited when UAV operations are not possible. Therefore, for efficient nationwide monitoring, this study developed a model that can automatically generate terrain data by estimating depth information from a single image using c-GAN (Conditional Generative Adversarial Networks) and BBDM (Brownian Bridge Diffusion Model). The training, utilization, and validation datasets employed images from the ISPRS (2018) and directly aerial photographed image sets from five locations in the territory of the Republic of Korea. Compared to the ground truth of the test data set, it is considered sufficiently usable as terrain data for flood wave analysis, capable of generating highly accurate and precise terrain data with high reproducibility.

• Spatial Information Research
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• v.18 no.5
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• pp.37-45
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• 2010

AT(Aerial Triangulation) is the essential procedure for creating orthophoto and transforming coordinates on the photographs into the real world coordinates utilizing GCPs (Ground Control Point) which is obtained by field survey and the external orientation factors from GPS/INS as a reference coordinates. In this procedure, all of the GCPs can be collected from field survey using GPS and Total Station, or obtained from digital maps. Collecting GCPs by field survey is accurate than GCPs from digital maps; however, lots of manpower should be put into the collecting procedure, and time and cost as well. On the other hand, in the case of obtaining GCPs from digital maps, it is very difficult to secure the required accuracy because almost things at each stage in the collecting procedure should rely on the subjective judgement of the performer. In this study, the results from three methods have been compared for the accuracy assessment in order to know if the results of each case is within the allowance error: for the perceivable objects such as road boarder, speed bumps, constructions etc., 1) GCPs selection utilizing the unique LiDAR intensity value reflected from such objects, 2) using LiDAR DSM and 3) GCPs from field survey. And also, AT and error analysis have been carried out w ith GCPs obtained by each case.

• Journal of Life Science
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• v.25 no.9
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• pp.1059-1071
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• 2015

Watermelon and melon are economically important Cucurbitaceae crops. Recently, the development of molecular markers based on the construction of genetic linkage maps and detection of DNA sequence variants through next generation sequencing are essential as molecular breeding strategies for crop improvement that uses marker-assisted selection and backcrossing. In this paper, we intended to provide useful information for molecular breeding of watermelon and melon by analyzing the current status of international and domestic research efforts on genomics and molecular markers. Due to diverse genetic maps constructed and the reference genome sequencing completed in the past, DNA markers that are useful for selecting important traits including yield, fruit quality, and disease resistances have been reported and publicly available. To date, more than 16 genetic maps and loci and linked markers for more than 40 traits have reported for each watermelon and melon. Furthermore, the functional genes that are responsible for those traits are being continuously discovered by high-density genetic map and map-based cloning. In addition, whole genome resequencing of various germplasm is under progress based on the reference genome. Not only by the efforts for developing novel molecular markers, but application of public marker information currently available will greatly facilitate breeding process through genomics-assisted breeding.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.1-15
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• 2012

Marine scientific monitoring, including monitoring of oil pollution, marine ecosystems, and the marine environment in general, has been being carried out continuously in order to assess the impact of oil pollution since the Hebei Spirit oil spill in December 2007. GIS thematic maps containing visual and summarized information are very useful for conducting exploratory analyses on the spatio-temporal variability of the marine environment and marine ecosystems due to oil pollution. Defining map types and building a legend in accordance with data characteristics are essential elements for mapping. In the present study, map types were defined according to the data attributes and GIS data types for each data item and classification of data intervals for the legend was defined by using two data distribution types through a histogram analysis. The data interval method was defined as follows: If the histogram of data has a uniform distribution, an equal interval method is applied; in the case of a normal distribution, a standard deviation method is applied. In addition, thematic map templates were made for each map type through the definition of marginal elements. Through the establishment of systematic mapping methods and procedures in this study, it was possible to effectively make standardized thematic maps for various kinds of marine scientific data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.19-30
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• 2007

Modeling 3D buildings is an essential process to revive the real world into a computer. There are two ways to create a 3D building model. The first method is to use the building layer of 1:1000 digital maps based on high density point data gained from airborne laser surveying. The second method is to use LiDAR point data with digital images achieved with LiDAR. In this research we tested one sheet area of 1:1000 digital map with both methods to process a 3D building model. We have developed a process, analyzed quantitatively and evaluated the efficiency, accuracy, and reality. The resulted differed depending on the buildings shape. The first method was effective on simple buildings, and the second method was effective on complicated buildings. Also, we evaluated the accuracy of the produced model. Comparing the 3D building based on LiDAR data and digital image with digital maps, the horizontal accuracy was within ${\pm}50cm$. From the above we derived a conclusion that 3D building modeling is more effective when it is based on LiDAR data and digital maps. Using produced 3D building modeling data, we will be utilized as digital contents in various fields like 3D GIS, U-City, telematics, navigation, virtual reality and games etc.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.479-495
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• 2021

To improve on the efficient management of forest resources, it is necessary to create a forest soil map, which represents a comprehensive database of forest lands. Although a 1:25,000 scale forest site map has been used in Korea, the need for a large-scale forest soil map with high precision and information on forest lands that is specialized for individual purposes has been identified. Moreover, to keep pace with the advancement in forest management and transition to a digital society, it is essential to develop a method for constructing new forest soil maps that can diversify its use. Therefore, this paper presented a developmental process and used a 1:5,000 scale forest soil map to propose future directions. National maps showing the soil type, depth, and texture were produced based on the survey and analysis of forest soils, followed by the Forest Land Soil Map (1:5,000) Production Standard Manual. Alternatively, forest soil map data were the basis on which various other maps that can be used to prevent and predict forest disasters and evaluate environmental capacities were developed. Accordingly, ways to provide appropriate information to achieve the national forest plan, secure forestry big data, and accomplish sustainable forest management that corresponds to the national development plan are proposed based on results from the current study.