• Korean Journal of Remote Sensing
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• 제37권6_1호
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• pp.1573-1587
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• 2021

A Drone image is an ultra-high-resolution image that is several or tens of times higher in spatial resolution than a satellite or aerial image. Therefore, drone image-based remote sensing is different from traditional remote sensing in terms of the level of object to be extracted from the image and the amount of data to be processed. In addition, the optimal scale and size of data used for model training is different depending on the characteristics of the applied deep learning model. However, moststudies do not consider the size of the object to be found in the image, the spatial resolution of the image that reflects the scale, and in many cases, the data specification used in the model is applied as it is before. In this study, the effect ofspatial resolution and image size of drone image on the accuracy and training time of the semantic segmentation deep learning model of six wintering vegetables was quantitatively analyzed through experiments. As a result of the experiment, it was found that the average accuracy of dividing six wintering vegetablesincreases asthe spatial resolution increases, but the increase rate and convergence section are different for each crop, and there is a big difference in accuracy and time depending on the size of the image at the same resolution. In particular, it wasfound that the optimal resolution and image size were different from each crop. The research results can be utilized as data for getting the efficiency of drone images acquisition and production of training data when developing a winter vegetable segmentation model using drone images.

• Korean Journal of Remote Sensing
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• 제37권3호
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• pp.577-589
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• 2021

Drone mapping systems can be applied to many fields such as disaster damage investigation, environmental monitoring, and construction process monitoring. To integrate individual sensors attached to a drone, it was essential to undergo complicated procedures including time synchronization. Recently, a variety of composite sensors are released which consist of visual sensors and GPS/INS. Composite sensors integrate multi-sensory data internally, and they provide geotagged image files to users. Therefore, to use composite sensors in drone mapping systems, mapping accuracies from composite sensors should be examined. In this study, we analyzed the mapping accuracies of a composite sensor, focusing on the data acquisition area and pre-calibration effect. In the first experiment, we analyzed how mapping accuracy varies with the number of ground control points. When 2 GCPs were used for mapping, the total RMSE has been reduced by 40 cm from more than 1 m to about 60 cm. In the second experiment, we assessed mapping accuracies based on whether pre-calibration is conducted or not. Using a few ground control points showed the pre-calibration does not affect mapping accuracies. The formation of weak geometry of the image sequences has resulted that pre-calibration can be essential to decrease possible mapping errors. In the absence of ground control points, pre-calibration also can improve mapping errors. Based on this study, we expect future drone mapping systems using composite sensors will contribute to streamlining a survey and calibration process depending on the data acquisition circumstances.

• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1479-1488
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• 2022

Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.

• Korean Journal of Remote Sensing
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• 제39권6_1호
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• pp.1451-1466
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• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.

• Korean Journal of Materials Research
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• 제10권1호
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• pp.49-54
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• 2000

The new green $Al_3GdB_4O_{12}:Tb^{3+} and red Al_3GdB_4O_{12}:Eu_{3+}$ phosphors were synthesized and then characterized their optical properties for PDP application. And also the photoluminescence properties of these phosphors were compared with the commercial green $Zn_2SiO_4:Mn^{2+} and (Y,Gd)BO_3: Eu^{3+}$ red PDP phosphors. The phosphors were synthesized by solid state reaction at 115$0^{\circ}C$ for 4hr. It was found that the emitting brightness of $Al_3GdB_4O_{12}:Tb^{3+}$(15mol%) green phosphor under 147nm excitation was higher than that of commercial $Zn_2SiO_4: Mn^{2+}$ green PDP phosphor. However, the color coordinate of this new green phosphor was inferior to the commercial one. On the other hand, the emitting intensity of $Al_3GdB_4O_{12}:Eu^{3+}$(15mol%) red phosphor was smaller than the $commercial(Y,Gd)BO_3: Eu^{3+}$ red one, but the CIE coordinate was slightly improved. The excitation spectrum showed that $Al_3GdB_4O_{12}$ phosphors had a strong excitation band at $\lambda=160nm$ associated with the host absorption. And the photoluminance excitation (PLE) intensity in VUV range for $Al_3GdB_4O_{12}:Tb^{3+}$ green phosphor was higher than that of $Zn_2SiO_4: Mn^{2+}$, but the PLE intensity of $Al_3GdB_4O_{12}:Eu^{3+}$ red phosphor was smaller than $(Y,Gd)BO_3: Eu^{3+}$.

• Korean Journal of Remote Sensing
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• 제36권2_2호
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Journal of Environmental Health Sciences
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• 제37권4호
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• pp.267-278
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• 2011

Objectives: A great number of hazardous agents can be emitted from various types of art-creation in a fine arts college, but little data on exposure assessment has been published. A variety of processes encompassing toxic or non-toxic materials, tools, and components are involved in a sculptor work at a fine art college. The aim of this study was to assess exposure levels to particulates and noise during sculpture classes in a college of fine arts. Methods: Students in sculpture classes participated in this study. Mass, number, and surface area concentrations of particulates, noise level, temperature and relative humidity were monitored by both personal and area sampling during the tasks of metal, wood, and stone sculpting. Results: The number and surface concentration of particulates was the highest in the task of wood sculpting, followed by metal and stone work. The mass concentration of particulates was the highest in stone sculpting (personal GM 3.0 mg/$m^3$, GSD 3.0), followed by wood (personal GM 1.5 mg/$m^3$, GSD 1.8) and metal work (personal GM 0.95 mg/$m^3$, GSD 1.51) in that order. Occupational exposure limits (OEL) for particulates depends on the type of particulate. For wood dust, 86% (six subjects) of the personal samples and all area samples exceeded the Korean OEL for wood dust (1 mg/$m^3$), while 20% (two subjects) among stone sculpting students were exposed above the Korean OEL (10 mg/$m^3$). In contrast, metal sculpting did not exceed the OEL (5 mg/$m^3$). For noise level, metal sculpting students (Leq 95.1 dB(A) in the morning, 85.3 dB(A) in the afternoon) were exposed the most, followed by stone sculpting (88.3 dB(A)), and wood sculpting (84.8 dB(A)) in that order. Compared with the 90 dB(A) of the Korean OEL and 85 dB(A) of the American Conference of Governmental Industrial Hygienists' threshold limit value (ACGIH-TLV) for noise, 100% of the subjects (five subjects) and area samples during metal sculpting in the morning session exceeded both OELs, but only three subjects (60%) exceeded the ACGIH-TLV in the afternoon session. For stone sculpting, 50% (one subject) and 100% (two subjects) exceeded the Korean OEL and ACGIH-TLV, respectively, but the area sample did not exceed either OEL. During wood sculpting, two subjects (40%) exceeded ACGIH TLV. Conclusions: This work evaluated the sculptors' exposure to particulate matter and noise in fine art college, and revealed a poor working environment for the participating students. Effective measures should be supplemented by the administration of colleges.

• Journal of the Korean Institute of Landscape Architecture
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• 제40권6호
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• pp.140-147
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• 2012

This study was conducted to investigate optimum planting density for apartment complex. The validity of Landscape Architecture Criteria of Korea was checked for it. We compared our field data with Landscape Architecture Criteria. In this step, the tree density of urban forest was regarded as standard. Field study was examined in 3 apartment complexes located in capital area, especially completed during these 10 years. 10 sites in each complex were selected and tree density per unit area were calculated. This field study data was divided standard size and large size which received weight. And, it was compared and analyzed. And crown projected area(CPA) was calculated considering proper growth of low vegetation and sufficient shade. The outcome shows that minimum size of Landscape Architecture Criteria is rational. But, in the case of planting large size tree received weight, tree density was short comparing with the tree density of urban forest and CPA was less than 50%. By the result of field study in 3 apartment complex, the tree density of apartment complex satisfied or exceeded Landscape Architecture Criteria. But, in the case of planting large size tree, tree density and CPA show high density due to addition planting for deficient landscape. Therefore, the revision of the Landscape Architecture Criteria was required such as deletion or minimization of the weighted clause about the large size tree and regulate the limit CPA not less than 50% and not more than 100%.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제64권4호
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• pp.441-451
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• 2019

This study was conducted to investigate the crop characteristics of 181 sweetpotato germplasms collected from Korea and overseas. The longest shoot vine length was observed in IT232211 (354.8 cm) and the shortest shoot vine length was observed in IT232185 (32 cm). The maximum numbers of shoot branches and nodes were produced by IT232091 (23.0) and IT232174 (67.8), respectively. Differences in Rapid Visco Analyser profiles were observed for pasting parameters such peak, trough, final, breakdown, and setback viscosities; and pasting temperature. The peak and breakdown viscosities were highest in IT232050 and IT232010, at 338.3 and 207.2 Rapid Visco Unit (RVU), respectively. The trough viscosity was lowest in IT232019 at 103.8 RVU. IT232101 had the highest final viscosity (284.6 RVU), and IT232192 had the highest setback viscosity (81.7 RVU). IT232197 had the highest pasting temperature at 86.8℃, and that of IT232134 was lowest at 72.7℃. To evaluate functional substance content, we analyzed 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity and total polyphenol content. The highest frequency proportion of starch was in the 10%-15% range (50.8% of the plants), followed by the 5%-10% range (38.1% of the germplasms). Sugar content ranged from 13.5 to 33.3% (23.2% on average); the highest frequency proportion of sugar was in the 20%-25% range (56.9% of the germplasms), followed by the 25%-30% range (25.4% of the germplasms). The highest frequency proportion of water was in the 70%-80% range (52.5% of the germplasms), followed by the 60%-70% range (44.2% of the germplasms). Our results provide basic data for the selection of useful resources and for the development of new sweetpotato varieties.