• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.22-37
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• 2018

Unmanned aerial vehicles (UAV) have attracted considerable attention both at home and abroad. The UAV is equipped with a camera that shoots images, which is advantageous for access to areas where archaeological investigations are not possible. Moreover, it is possible to acquire three-dimensional spatial image information by modeling the terrain through aerial photographing, and it is possible to specify the interpretation of the terrain of the survey area. In addition, if we understand the change of the terrain through comparison with past aerial photographs, it will be very helpful to grasp the existence of the ruins. The terrain modeling for searching these remains can be divided into two parts. First, we acquire the aerial photographs of the current terrain using the drone. Then, using image registration and post-processing, we complete the image-joining and terrain-modeling using past aerial photographs. The completed modeled terrain can be used to derive several analytical results. In the present terrain modeling, terrain analysis such as DSM, DTM, and altitude analysis can be performed to roughly grasp the characteristics of the change in the form, quality, and micro-topography. Past terrain modeling of aerial photographs allows us to understand the shape of landforms and micro-topography in wetlands. When verified with actual findings and overlapping data on the modelling of each terrain, it is believed that changes in hill shapes and buried Microform can be identified as helpful when used in low-flying applications. Thus, modeling data using aerial photographs is useful for identifying the reasons for the inability to carry out archaeological surveys, the existence of terrain and ruins in a wide area, and to discuss the preservation process of the ruins. Furthermore, it is possible to provide various themes, such as cadastral maps and land use maps, through comparison of past and present topographical data. However, it is certain that it will function as a new investigation methodology for the exploration of ruins in order to discover archaeological cultural properties.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.12-21
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• 2006

Recently, Very large and high resolution geological data from aerial or satellite imagery are available. Many researches and applications require to do realtime visualization of interest geological area or entire planet. Important operation of wide-spreaded terrain realtime visualization technique is the appropriate model resolution selection from pre-processed multi-resolution model hierarchy depend upon participant's view. For embodying such realtime rendering system with large geometric data, Preprocessing multi-resolution hierarchy from large scale geological information of interest area is required. In this research, recent Cubic multiresolution 4-8 tile hierarchy is selected for global planetary applications. Based upon the tile hierarchy, It constructs the selective terminal level tile mesh for original geological information area and starts to sample individual generated tiles for terminal level tiles. It completes the hierarchy by constructing intermediate tiles with low pass filtering in bottom-up direction. This research embodies series of efficient cubic 4-8 tile hierarchy construction mechanism with out-of-core storage. The planetary scale Mars' geographical altitude data and image data were selected for the experiment.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.42-54
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• 2020

This study aimed to analyze the rate of increase and spread patterns of dead trees of the conifer (Abies koreana and others) in subalpine zones by using the high-resolution aerial images in Jirisan National Park around 10 years ago. Furthermore, factors affecting the death of conifer were identified by analyzing the altitude, topographical information, solar radiation, and moisture environment of the site where the dead trees are located. The number of dead trees per unit area increased by two to five times in the Banyabong peak, Yeongsinbong peak, and Cheonwangbong peak in Jirisan National Park over the past decade. The increase was about 2 times in the Banyabong peak, about 3.9 times in the Yeongsinbong peak, and about 5.2 times in the Cheonwangbong peak, indicating the most notable increase in the Cheonwangbong peak. It is estimated that dead trees commonly occurred in the environments where the soil moisture content was low due to the high slope, amount of evaporation was high due to strong solar radiation as the location faced south, and the soil was dry due to strong solar radiation and short rain retention time. In other words, dead conifer trees in subalpine zones were concentrated in dry location environments, and the tendency was the same more than ten years ago.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.203-215
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• 2019

As hyperspectral sensors that can be mounted on drones are developed, it is possible to acquire hyperspectral imagery with high spatial and spectral resolution. Although the importance of atmospheric correction has been reduced since imagery of drones were acquired at a low altitude,studies on the conversion process from raw data to spectral reflectance should be done for studies such as estimating the concentration of surface materials using hyperspectral imagery. In this study, a vicarious radiometric calibration and an atmospheric correction algorithm based on atmospheric radiation transfer model were applied to hyperspectral data of drone and the results were compared and analyzed. The vicarious calibration method was applied to an empirical line calibration using the spectral reflectance of a tarp made of uniform material. The atmospheric correction algorithm used ATCOR-4 based Modran-5 that was widely used for the atmospheric correction of aerial hyperspectral imagery. As a result of analyzing the RMSE of the difference between the reference reflectance and the correction, the vicarious calibration using the tarp in a single period of hyperspectral image was the most accurate, but the atmospheric correction was possible according to the application purpose of using hyperspectral imagery. If the correction process of normalized spectral reflectance is carried out through the additional vicarious calibration for imagery from multiple periods in the future, accurate analysis using hyperspectral drone imagery will be possible.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.558-568
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• 2021

Poor supervision and tourism activities have resulted in forest degradation in islands in Korea. Since the southern coastal region of the Korean peninsula was originally dominated by warm-temperate evergreen broad-leaved forests, it is desirable to restore forests in this region to their original vegetation. In this study, we identified suitable areas to be restored as evergreen broad-leaved forests by analyzing the environmental factors of existing evergreen broad-leaved forests in the islands of Jeollanam-do. We classified forest lands in the study area into six vegetation types from Sentinel-2 satellite images using a deep learning algorithm and analyzed the tolerance ranges of existing evergreen broad-leaved forests by measuring the locational, topographic, and climatic attributes of the classified vegetation types. Results showed that evergreen broad-leaved forests were distributed more in areas with a high altitudes and steep slope, where human intervention was relatively low. The human intervention has led to a higher distribution of evergreen broad-leaved forests in areas with lower annual average temperature, which was an unexpected but understandable result because an area with higher altitude has a lower temperature. Of the environmental factors, latitude and average temperature in the coldest month (January) were relatively less contaminated by the effects of human intervention, thus enabling the identification of suitable restoration areas of the evergreen broad-leaved forests. The tolerance range analysis of evergreen broad-leaved forests showed that they mainly grew in areas south of the latitude of 34.7° and a monthly average temperature of 1.7℃ or higher in the coldest month. Therefore, we predicted the areas meeting these criteria to be suitable for restoring evergreen broad-leaved forests. The suitable areas cover 614.5 km², which occupies 59.0% of the total forest lands on the islands of Jeollanamdo, and 73% of actual forests that exclude agricultural and other non-restorable forest lands. The findings of this study can help forest managers prepare a restoration plan and budget for island forests.