• Journal of Korean Society for Geospatial Information Science
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• 제20권3호
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• pp.3-10
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• 2012

The investigation of valley networks and their volume provide important information about past water activities on Mars. As an alternative of conventional image processing methods, terrain filtering algorithm using pointcloud data is suggested in this study. First, the topography of pointcloud is inverted so that the valleys become positive features and the algorithm is then applied to distinguish the valleys from the surface. Ground DEM and object DEM are generated from both the valleys and the surface pointcloud then the volume of valleys is estimated by multiplying the height difference between the surface with valleys and the area of valleys based on grid cellsize. In the test of valleys adjacent to Tuscaloosa crater, the total volume of valleys was estimated to be $1.41{\times}10^{11}m^3$ with the difference of 12% and 16% compared with the infill volume of Tuscaloosa crater and BTH result respectively.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2008년도 공동학술대회
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• pp.185-190
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• 2008

Geophysical survey were investigated in the offshore around East Sea Research Institute, Korea Ocean Research and Development Institute (Jukbyeon-myun, Uljin-gu, Gyeongsangbuk-do, Korea). The surveys were conducted aboard the R/V Jangmok in 2008 using a hull-mounted EM 3002 multi-beam echosounder. Precise bathymetry and seabed images were obtained using multi-beam and thicknesses of sedimentary layer were found through seismic survey. Submarine topography deepens parallel to the coastline to -60 m and rock mass distributed in the southeast of study area. By finding the thickness of sedimentary layer through seismic survey, a sedimentary thickness on the study area was established. Futhermore, monitoring data of bathymetry, substructure and sedimentary environment will be secured through successive geophysical investigation.

• Atmosphere
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• 제29권5호
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• pp.537-550
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• 2019

To analyze the observation environment of solar radiation stations operated by the Korea Meteorological Administration (KMA), we analyzed the skyline, Sky View Factor (SVF), and solar radiation due to the surrounding topography and artificial structures using a Digital Elevation Model (DEM), 3D camera, and solar radiation model. Solar energy shielding of 25 km around the station was analyzed using 10 m resolution DEM data and the skyline elevation and SVF were analyzed by the surrounding environment using the image captured by the 3D camera. The solar radiation model was used to assess the contribution of the environment to solar radiation. Because the skyline elevation retrieved from the DEM is different from the actual environment, it is compared with the results obtained from the 3D camera. From the skyline and SVF calculations, it was observed that some stations were shielded by the surrounding environment at sunrise and sunset. The topographic effect of 3D camera is therefore more than 20 times higher than that of DEM throughout the year for monthly accumulated solar radiation. Due to relatively low solar radiation in winter, the solar radiation shielding is large in winter. Also, for the annual accumulated solar radiation, the difference of the global solar radiation calculated using the 3D camera was 176.70 MJ (solar radiation with 7 days; suppose daily accumulated solar radiation 26 MJ) on an average and a maximum of 439.90 MJ (solar radiation with 17.5 days).

• Korean Journal of Remote Sensing
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• 제31권1호
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• pp.29-38
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• 2015

The coastline influenced naturally and artificially changes dynamically. While the long-term change is influenced by the rise in the surface of the sea and the changes in water level of the rivers, the short-term change is influenced by the tide, earthquake and storm. Also, man-made thoughtless development such as construction of embankment and reclaimed land not considering erosion and deformation of coast has been causes for breaking functions of coast and damages on natural environment. In order to manage coastal environment and resources effectively, In this study is intended to analyze and predict erosion in coastal environment and changes in sedimentation quantitatively by detecting changes in coastal line from data collection for satellite images and aerial LiDAR data. The coastal line in 2007 and 2012 was extracted by manufacturing Digital Surface Model (DSM) with Aviation LiDAR materials. For the coastal line in 2009 and 2010, Normalized Difference Vegetation Index (NDVI) method was used to extract the KOMPSAT-2 image selected after considering tide level and wave height. The change rate of the coastal line is varied in line with the forms of the observation target but most of topography shows a tendency of being eroded as time goes by. Compared to the relatively monotonous beach of Taean, the gravel and rock has very complex form. Therefore, there are more errors in extraction of coastlines and the combination of transect and shoreline, which affect overall changes. Thus, we think the correction of the anomalies caused by these properties is required in the future research.

• Journal of the Korean Society of Environmental Restoration Technology
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• 제23권1호
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• pp.1-14
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• 2020

In this study, we 1) identified the damaged areas along the south limit line (SLL) of the demilitarized zone (DMZ) by the military's 'DMZ barren land campaign', and 2) categorized the identified damaged areas into a few ecological types. Using high-resolution satellite images, we delineated the total damaged areas to be 1,183.2 ha, which accounted for 50.1% of the 100-m northern buffer regions from the SLL. Of the total damaged areas, 16% were severely damaged, i.e., they had been damaged until recently and so remained barren without vegetation cover. In other areas, the levels of damage were either moderate (59.9%) or slight (24.1%), due to natural succession that turned those areas to grassland or forest. Using satellite image-derived land cover maps and climatic and topographic data, we categorized the damaged areas into seven types: lowland grassland (19.8%), western lowland forest (21.4%), low-altitude forest (25.5%), mid-altitude forest (18.4%), high-altitude forest (6.8%), vicinity in east coast (7.9%), and waterbody (0.2%). These types can be used to identify proper measures to restore ecosystems in the DMZ for now and after Korean reunification.

• Korean Journal of Remote Sensing
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• 제22권1호
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• pp.25-40
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• 2006

Synthetic aperture radar (SAR) from satellites provides the opportunity to regularly incorporate microwave information into forest classification. Radar backscatter can improve classification accuracy, and SAR interferometry could provide improved thematic information through the use of coherence. This research examined the potential of using multi-temporal JERS-l SAR (L band) backscatter information and interferometry in distinguishing forest classes of mountainous areas in the Northeastern U.S. for future forest mapping and monitoring. Raw image data from a pair of images were processed to produce coherence and backscatter data. To improve the geometric characteristics of both the coherence and the backscatter images, this study used the interferometric techniques. It was necessary to radiometrically correct radar backscatter to account for the effect of topography. This study developed a simplified method of radiometric correction for SAR imagery over the hilly terrain, and compared the forest-type discriminatory powers of the radar backscatter, the multi-temporal backscatter, the coherence, and the backscatter combined with the coherence. Statistical analysis showed that the method of radiometric correction has a substantial potential in separating forest types, and the coherence produced from an interferometric pair of images also showed a potential for distinguishing forest classes even though heavily forested conditions and long time separation of the images had limitations in the ability to get a high quality coherence. The method of combining the backscatter images from two different dates and the coherence in a multivariate approach in identifying forest types showed some potential. However, multi-temporal analysis of the backscatter was inconclusive because leaves were not the primary scatterers of a forest canopy at the L-band wavelengths. Further research in forest classification is suggested using diverse band width SAR imagery and fusing with other imagery source.

• Korean Journal of Remote Sensing
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• 제35권5_1호
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• pp.715-726
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• 2019

With the increasing prevalence of high-resolution satellite images, the need for technology to generate accurate 3D information from the satellite images is emphasized. In order to create a digital terrain model (DTM) that is widely used in applications such as change detection and object extraction, it is necessary to extract trees, buildings, etc. that exist in the digital surface model (DSM) and estimate the height of the ground. This paper presents a method for automatically generating DTM from DSM extracted from KOMPSAT-3A stereo images. The technique was developed to detect the non-ground area and estimate the height value of the ground by using the previously constructed low-resolution topographic data. The average vertical accuracy of DTMs generated in the four experimental sites with various topographical characteristics, such as mountainous terrain, densely built area, flat topography, and complex terrain was about 5.8 meters. The proposed technique would be useful to produce high-quality DTMs that represent precise features of the bare-earth's surface.

• Current Optics and Photonics
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• 제5권3호
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• pp.229-237
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• 2021

The capabilities of the near-field scanning optical microscope (NSOM) for obtaining high resolution lateral topographical images as well as for mapping the spectroscopic and optical properties of a sample below the diffraction limit of light have made it an attractive research field for most researchers dealing with optical characteristics of materials in nano scales. The apertured NSOM technique involves confining light into an aperture of sub-wavelength size and using it to illuminate a sample maintained at a distance equal to a fraction of the sub-wavelength aperture (near-field region). In this article, we present a setup for developing NSOM using a cantilever with a sub-wavelength aperture at the tip. A single laser is used for both cantilever deflection measurement and near-field sample excitation. The laser beam is focused at the apex of the cantilever where a portion of the beam is reflected and the other portion goes through the aperture and causes local near-field optical excitation of the sample, which is then raster scanned in the near-field region. The reflected beam is used for an optical beam deflection technique that yields topographical images by controlling the probe-sample in nano-distance. The fluorescence emissions signal is detected in far-field by the help of a silicon avalanche photodiode. The images obtained using this method show a good correlation between the topographical image and the mapping of the fluorescence emissions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제39권6호
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• pp.381-392
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• 2021

In this study, we perform deep learning-based object detection analysis on eight types of buildings defined by the digital map topography standard code, leveraging images taken with UAV (Unmanned Aerial Vehicle). Image labeling was done for 509 images taken by UAVs and the YOLO (You Only Look Once) v5 model was applied to proceed with learning and inference. For experiments and analysis, data were analyzed by applying an open source-based analysis platform and algorithm, and as a result of the analysis, building objects were detected with a prediction probability of 88% to 98%. In addition, the learning method and model construction method necessary for the high accuracy of building object detection in the process of constructing and repetitive learning of training data were analyzed, and a method of applying the learned model to other images was sought. Through this study, a model in which high-efficiency deep neural networks and spatial information data are fused will be proposed, and the fusion of spatial information data and deep learning technology will provide a lot of help in improving the efficiency, analysis and prediction of spatial information data construction in the future.

• Korean Journal of Agricultural Science
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• 제50권3호
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• pp.555-567
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• 2023

This study was conducted to compare the level of vegetation recovery based on the forest restoration techniques (natural restoration and artificial restoration) determined using the satellite imagery that targeted forest fire damaged areas in Goseong-gun, Gangwon-do. The study site included the area affected by the Goseong forest fire (1996) and the East Coast forest fire (2000). We conducted a time-series analysis of satellite imagery on the natural restoration sites (19 sites) and artificial restoration sites (12 sites) that were created after the forest fire in 1996. In the analysis of satellite imagery, the difference normalized burn ratio (dNBR) and normalized difference vegetation index (NDVI) were calculated to compare the level of vegetation recovery between the two groups. We discovered that vegetation was restored at all of the study sites (31 locations). The satellite image-based analysis showed that the artificial restoration sites were relatively better than the natural restoration sites, but there was no statistically significant difference between the two groups (p > 0.05). Therefore, it is necessary to select a restoration technique that can achieve the goal of forest restoration, taking the topography and environment of the target site into account. We also believe that in the future, accurate diagnosis and analysis of the vegetation will be necessary through a field survey of the forest fire-damaged sites.