• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.693-703
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• 2019

Long-term coastal topographical data is critical for analyzing temporal and spatial changes in shorelines. Especially understanding the change trends is essential for future coastal management. For this research, in the data preparation, we obtained digital aerial images, terrestrial laser scanning data and UAV images in the year of 2009. 2018 and 2019 respectively. Also tidal observation data obtained by the Korea Hydrographic and Oceanographic Agency were used for Bangamoeri beach located in Ansan, Gyeonggi-do. In the process of it, we applied the photogrammetric technique to extract the coastline of 4.40 m from the stereo images of 2009 by stereoscopic viewing. In 2018, digital elevation model was generated by using the raw data obtained from the laser scanner and the corresponding shoreline was semi-automatically extracted. In 2019, a digital elevation model was generated from the drone images to extract the coastline. Finally the change rate of shorelines was calculated using Digital Shoreline Analysis System. Also qualitative analysis was presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.451-456
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• 2018

UAVs (Unmanned Aerial Vehicles) are widely used for maintenance and monitoring of facilities. It is necessary to acquire a high-resolution image for evaluating the appearance state of the facility in safety inspection. In addition, it is essential to acquire the video data in order to acquire data over a wide area rapidly. In general, since video data does not include position information, it is difficult to analyze the actual size of the inspection object quantitatively. In this study, we evaluated the utilization of 3D point cloud data of bridges using a matching between video frames and reference photos. The drones were used to acquire video and photographs. And exterior orientations of the video frames were generated through feature point matching with reference photos. Experimental results showed that the accuracy of the video frame data is similar to that of the reference photos. Furthermore, the point cloud data generated by using video frames represented the shape and size of bridges with usable accuracy. If the stability of the product is verified through the matching test of various conditions in the future, it is expected that the video-based facility modeling and inspection will be effectively conducted.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.347-354
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• 2022

Since the era of the 4th industrial revolution has been ripe, the use of artificial intelligence(AI) based on massive data is beginning to be actively applied in various fields. However, as the process of analyzing forest species is carried out manually, many errors are occurring. Therefore, in this paper, about 60,000 pieces of AI learning data were automatically analyzed for pine, larch, conifer, and broadleaf trees of aerial photographs and pseudo images in the metropolitan area, and an AI model was developed to distinguish tree species. Through this, it is expected to increase in work efficiency by using the tree species division image as basic data when producing forest change detection and forest field topics.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.638-651
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• 2023

The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m². The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition. The 43 raw training images selected randomly out of 320 segmented images were flipped to create 86 images, and then these images were further augmented by rotating them in 5-degree increments to create a total of 6,192 images. The increased 6,192 images are further augmented by applying three random color transformations to each image, resulting in 24,768 datasets. The occupancy rate of corn in the field was estimated efficiently using You Only Look Once (YOLO). As of the first day of observation (day 2), it was evident that almost all the corn had disappeared by the ninth day. When grazing 20 sows in a 50 × 100 m² cornfield (250 m²/sow), it appears that the animals should be rotated to other grazing areas to protect the cover crop after at least five days. In agricultural technology, most of the research using machine and deep learning is related to the detection of fruits and pests, and research on other application fields is needed. In addition, large-scale image data collected by experts in the field are required as training data to apply deep learning. If the data required for deep learning is insufficient, a large number of data augmentation is required.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.131-140
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• 2014

Lava caves could be useful as outposts for the human exploration of the Moon. Lava caves or lava tubes are formed when the external surface of the lava flows cools more quickly to make a hardened crust over subsurface lava flows. The lava flow eventually ceases and drains out of the tube, leaving an empty space. The frail part of the ceiling of lava tube could collapse to expose the entrance to the lava tubes which is called a pit crater. Several pit craters with the diameter of around 100 meters have been found by analyzing the data of SELENE and LRO lunar missions. It is hard to use these pit craters for outposts since these are too large in scale. In this study, small scale pit craters which are fit for outposts have been investigated using the NAC image data of LROC. Several topographic patterns which are believed to be lunar caves have been found and the similar pit craters of the Earth were compared and analyzed to identify caves. For this analysis, the image data of satellites and aerial photographs are collected and classified to construct a database. Several pit craters analogous to lunar pit craters were derived and a morphological pit crater model was generated using the 3D printer based on this database.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.149-156
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• 2006

Existing method of landuse classification using aerial photographs or field survey requires relatively higher amount of time and cost due to necessary manual work. Especially in urban area where the pattern of landuse is densely aggregated, a landuse classification using satellite image is more complex. In this background, this study proposes a landuse classification method to utilize 1:1,000 digital topographic data and IKONOS satellite image. To prove the possibility of this method, the method was applied to Seoul metropolitan area. The results shows the total accuracy of approximately 95% and 14 landuse classes extracted. Based on the results from the pilot study, this method is applicable to landuse classification in urban area.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.591-597
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• 2014

A wide variety of image application methods, such as aerial image, terrestrial image, terrestrial laser, and stereo image point are currently under investigation to develop three-dimensional 3D geospatial information. In this study, matching points, which are needed to build a 3D model, were examined under diverse weather conditions by analyzing the stereo images recorded by closed circuit television (CCTV) cameras installed in the U-City. The tests on illuminance and precipitation conditions showed that the changes in the number of matching points were very sensitively correlated with the changes in the illuminance levels. Based on the performances of the CCTV cameras used in the test, this study was able to identify the optimal values of the shutter speed and iris. As a result, compared to an automatic control mode, improved matching points may be obtained for images filmed using the data obtained through this test in relation to different weather and illuminance conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.81-91
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• 2021

Drone related research has been increasing recently due to the development and distribution of commercial unmanned aerial vehicles. However, most of the previous studies focused on the accuracy and utility of drone surveying. For drones, the resolution of the result is determined according to the flight altitude, but since 70% of Korea is mountainous, it is necessary to analyze the quality of the drone image according to the flight plan. In this study, the quality of drone photogrammetry results according to flight plans was analyzed. The flight plan was established by fixed altitude and considering the height of the terrain. Images were acquired for both cases and data was processed to generate ortho images. As a result of evaluating the accuracy of the generated ortho image, the accuracy was found to be -0.07 ~ 0.09m. The accuracy of Case I and Case II did not show a significant difference, but for RMSE, Case I showed a good value. These results indicate that the drone flight plan affects the quality of the results. Also, when flying at a fixed altitude, II showed a lower value than the originally set overlap according to the altitude of the object. In future surveys using drones, flight planning taking into account the height of the object will contribute to the improvement of the quality of the results.