In this study, a two-dimensional numerical model (Nays2DH) was applied to analyze the process of morphological changes in the river channel bed depending on the changes in the amount of flooding after fully opening the Sejong weir, which was constructed upstream of the Geum River. For this, numerical simulations were performed by assuming the flow conditions, such as a non-uniform flow (NF), unsteady flows (single flood event, SF), and a continuous flood event (CF). Here, in the cases of the SF and CF, the normalized hydrograph was calculated from real flood events, and then the hydrograph was reconfigured by the peak flow discharge according to the scenario, and then it was employed as the flow discharge at the upstream boundary condition. In this study, to quantitatively evaluate the morphological changes, we analyzed the time changes in the bed deformation the bed relief index (BRI), and we compared the aerial photographs of the study area and the numerical simulation results. As simulation results of the NF, when the steady flow discharge increases, the ratio of lower width to depth decreases and the speed of bar migration increases. The BRI initially increases, but the amount of change decreased with time. In addition, when the steady flow discharge increases, the BRI increased. In the case of SF, the speed of bar migration decreased with the change of the flow discharge. In terms of the morphological response to the peak flood discharge, the time lag also indicated. In other words, in the SF, the change of channel bed indicates a phase lag with respect to the hydraulic condition. In the result of numerical simulation of CF, the speed of bar migration depending on the peak flood discharges decreased exponentially despite the repeated flood occurrences. In addition, as in the result of SF, the phase lag indicated, and the speed of bar migration decreased exponentially. The BRI increased with time changes, but the rate of increase in the BRI was modest despite the continuous peak flooding. Through this study, the morphological changes based on the hydrological characteristics of the river were analyzed numerically, and the methodology suggested that a quantitative prediction for the river bed change according to the flow characteristic can be applied to the field.
Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.
Kim, Cheolwook;Lim, Pyeong-chae;Chi, Junhwa;Kim, Taejung;Rhee, Sooahm
Korean Journal of Remote Sensing
/
v.38
no.6_1
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pp.1125-1139
/
2022
In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.
KIM, Seoung-Hyeon;PARK, Kyung-Hun;LEE, Su-Ah;SONG, Bong-Geun
Journal of the Korean Association of Geographic Information Studies
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v.25
no.1
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pp.28-43
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2022
This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the TMRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.
Min-Jun, Park;Chan-Seok, Ryu;Ye-Seong, Kang;Hye-Young, Song;Hyun-Chan, Baek;Ki-Su, Park;Eun-Ri, Kim;Jin-Ki, Park;Si-Hyeong, Jang
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.4
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pp.295-304
/
2022
The purpose of this study is to detect the sorghum panicle using YOLOv5 based on RGB images acquired by a unmanned aerial vehicle (UAV) system. The high-resolution images acquired using the RGB camera mounted in the UAV on September 2, 2022 were split into 512×512 size for YOLOv5 analysis. Sorghum panicles were labeled as bounding boxes in the split image. 2,000images of 512×512 size were divided at a ratio of 6:2:2 and used to train, validate, and test the YOLOv5 model, respectively. When learning with YOLOv5s, which has the fewest parameters among YOLOv5 models, sorghum panicles were detected with mAP@50=0.845. In YOLOv5m with more parameters, sorghum panicles could be detected with mAP@50=0.844. Although the performance of the two models is similar, YOLOv5s ( 4 hours 35 minutes) has a faster training time than YOLOv5m (5 hours 15 minutes). Therefore, in terms of time cost, developing the YOLOv5s model was considered more efficient for detecting sorghum panicles. As an important step in predicting sorghum yield, a technique for detecting sorghum panicles using high-resolution RGB images and the YOLOv5 model was presented.
Park, Kiwoong;Prasanajit, Naik Sambit;Gwon, Ohsang;Shin, Hyeon-Cho;Kim, Young-Seog
Journal of the Korean earth science society
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v.43
no.1
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pp.151-164
/
2022
According to the records of historical and instrumental earthquakes, the southeastern part of the Korean Peninsula is considered the highest seismic activity area. Owing to recent reports of numerous Quaternary faults along the Yangsan and Ulsan fault zones, paleoseismological studies are being actively conducted in these areas. The study area is located in the central part of the Ulsan fault zone, where the largest number of active faults have been reported. Based on lineament and geomorphic analysis using LiDAR images and aerial photographs, fault-related landforms showing topographic relief were observed and a trench survey was conducted. The trench length 20 m, width 5 m, depth 5 m is located approximately 300 m away to the northeast from the previously reported Malbang fault. From the trench section, we interpreted the geometric and kinematic characteristics of the fault based on the deformed features of the Quaternary sedimentary layers. The attitude of the reverse fault, N26°W/33°NE, is similar to those of the reported faults distributed along the Ulsan fault zone. Although a single apparent displacement of approximately 40 cm has been observed, the true displacement could not be calculated due to the absence of the slickenline on the fault plane. Based on the geochronological results of the cryogenic structure proposed in a previous study, the most recent faulting event has been estimated as being earlier than the late Wurm glaciation. We interpreted the thrust fault system of the study area as an imbrication structure based on the previous studies and the fault geometry obtained in this additional trench. Although several previous investigations including many trench surveys have been conducted, they found limited success in obtaining the information on fault parameters, which could be due to complex characteristics of the reverse fault system. Additional paleoseismic studies will contribute to solving the mentioned problems and the comprehensive fault evolution.
Korean Journal of Agricultural and Forest Meteorology
/
v.25
no.1
/
pp.17-27
/
2023
Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.
We analyzed the distribution area of debris slopes in Mudeungsan (Mt. Mudeung) National Park by comparing aerial photos of the past (1966) and the present (2017) and identified the vegetation characteristics that affect the change in the area of the debris slopes by investigating the vegetation status of the debris slopes and the surrounding areas. The area of debris slopes in Mt. Mudeung appears to have been reduced to a quarter of what it used to be. Debris slopes here have decreased at an average rate of 2.3 ha/yr over 51 years by vegetation covers. Notably, most of the small-area debris slopes in the low-inclination slopes disappeared due to active vegetation coverage. However, there are still west-facing, south-west-facing, south-facing, and large-area debris slopes remaining because the sun's radiant heat rapidly raises the surface temperature of rock blocks and dries moisture, making tree growth unfavorable. Because of these locational characteristics, the small-scale vegetation in the middle of Deoksan Stony Slope, which is the broadest area, showed distinct characteristics from the adjacent forest areas. Sunny places and tree species with excellent drying resistance were observed frequently in Deoksan Stony Slope. However, tree species with high hygropreference that grow well in valleys with good soil conditions also prevailed. In some of these places, the soil layer has been well developed due to the accumulation of fine materials and organic matter between the crevices of the rock blocks, which is likely to have provided favorable conditions for such tree species to settle and grow. At the top of Mt. Mudeung, on the other hand, the forest covered the debris slopes, where Mongolian oaks (Quercus mongolica) and royal azaleas (Rhododendron schlippenbachii), which typically grow in the highlands, prevailed. This area was considered favorable for the development of vegetation for the highlands because the density of rock blocks was lower than in Deoksan Stony Slope, and the soil was exposed. Moreover, ash trees (Fraxinus rhynchophylla) and Korean maple trees (Acer pseudosieboldianum) that commonly appear in the valley areas were dominant here. It is probably due to the increased moisture content in the soil, which resulted from creating a depressive landform with a concave shape that is easy to collect rainwater as rock blocks in some areas fell and piled up in the lower region. In conclusion, the area, density of the rock blocks, and distribution pattern of rock block slopes would have affected the vegetation development and species composition in the debris slope landform.
Lee, Ka Youn;Min, Ji Yun;Kim, Mi Sun;Moon, Byeong Cheol;Kang, Young Min
Journal of agriculture & life science
/
v.50
no.2
/
pp.33-43
/
2016
Pinellia tripartita(Blume) Schott is a herbaceous perennial plant belonging to the Araceae and distributed on Asia including of Korea, Japan, and China. P. tripartita is often used for gardening but has not been developed mass-breeding methods. In this study, we compared the tuber growth in different combinations of mixed soils used six compositions. Tubers used to study was cultured in vitro and divided into two groups. Type I was diameter more than 1cm and the group of Type II was diameter below than 1cm. Enlargement of tubers and growth of aerial parts were measuring the plant height, number of fresh leaves and dead leaves, number of bullets, tuber size, and fresh / dry weight. The size/weight and numbers of tubers from the mixed soil B (coir 68.0%, peat moss 14.7%, perlite 3.0%, vermiculite 7.0% and zeolite 7.0%) were the best grown up for eight weeks. In case of Type I, GI (Growth index) of tuber size and weight were 45% and 101%, respectively. The difference of growth was doubled compared to the bad growth treatment as the mixed soil E(Coir 14.3%, peat moss 14.3%, perlite 42.9%, vermiculite 14.3%, and zeolite 14.3%). These results could be used as the basic information for the similar experimental design for the P. ternata.
Journal of Korean Society of Coastal and Ocean Engineers
/
v.35
no.6
/
pp.109-120
/
2023
The High-Frequency Radar (HFR) is an equipment designed to measure real-time surface ocean currents in broad maritime areas.It emits radio waves at a specific frequency (HF) towards the sea surface and analyzes the backscattered waves to measure surface current vectors (Crombie, 1955; Barrick, 1972).The Seasonde HF Radar from Codar, utilized in this study, determines the speed and location of radial currents by analyzing the Bragg peak intensity of transmitted and received waves from an omnidirectional antenna and employing the Multiple Signal Classification (MUSIC) algorithm. The generated currents are initially considered ideal patterns without taking into account the characteristics of the observed electromagnetic wave propagation environment. To correct this, Antenna Pattern Measurement (APM) is performed, measuring the strength of signals at various positions received by the antenna and calculating the corrected measured vector to radial currents.The APM principle involves modifying the position and phase information of the currents based on the measured signal strength at each location. Typically, experiments are conducted by installing an antenna on a ship (Kim et al., 2022). However, using a ship introduces various environmental constraints, such as weather conditions and maritime situations. To reduce dependence on maritime conditions and enhance economic efficiency, this study explores the possibility of using unmanned aerial vehicles (drones) for APM. The research conducted APM experiments using a high-frequency radar installed at Dangsa Lighthouse in Dangsa-ri, Wando County, Jeollanam-do. The study compared and analyzed the results of APM experiments using ships and drones, utilizing the calculated radial currents and surface current fields obtained from each experiment.
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