• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.293-301
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• 2005

In case of the roads that pass the mountain area, the cut sections or the tunnels are constructed. And In winter season it appears sunshine few in the specific segment, the shade is continued last and the freezing sections occur. So, the attention is necessary in traffic safety. This study was to evaluate the influence of sunshine and surface freezing sections expected in route plans of roads using GIS and makes alternative ideas in road stability security. After selecting 29 km sections of Donghae highway and creating a 3 dimensional terrain surface through the digital conversion of design plan data, it reflects the road alignment data of the same coordinates and a 3 dimensional road modeling is created. It set shadow time of road surface for the solar trace in the winter solstice in 20 minute interval. Shade areas are displayed and inputed in polygon data by manual vertorizing. Graphic and attribute data of this shade section is constructed in geodatabase of ArcCatalog. And it extracted the freezing section using intersect fuction of the GIS spatial analysis. By analyzing the winter meteorological data of temperature, rainfall, snowfall, humidity, and etc. and grasping dangerous freezing section of the road surface effectively, it will be able to make alternative ideas of the preliminary stability evaluation reflected in basic design.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.495-513
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• 2004

The shape of land surface work as a cradle for various environmental processes and human activities. As spatially distributed process modelings become increasing important in current research communities, a classification system that delineates land surface into characteristic geomorphological units is a pre-requisite for sustainable land use planning and management. Existing classification systems are either morphometric or generic, which have limitations to characterize continuous ecological processes over the landscape. A new classification system was developed to delineate the land surface into different geomorphological units from Digital Elevation Models(DEMs). This model assumes that there are pedo-geomorphological units in which distinct sets of hydrological, pedological, and consequent ecological processes occur. The classification system first divides the whole landsurface into eight soil-landscape units. Possible energy and material nows over the land surface were interpreted using a continuity equation of mass flow along the hillslope, and subsequently implemented in terrain analysis procedures. The developed models were tested at a 12$\textrm{km}^2$ area in Yangpyeong-gun, Kyeongi-do, Korea. The method proposed effectively delineates land surface into distinct pedo-geomorphological units, which identify the geomorphological characteristics over a large area at a low cost. The delineated landscape units mal provide a basic information for natural resource survey and environmental modeling practices.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.