• Title/Summary/Keyword: earth system science

Search Result 1,607, Processing Time 0.029 seconds

Ship Detection from SAR Images Using YOLO: Model Constructions and Accuracy Characteristics According to Polarization (YOLO를 이용한 SAR 영상의 선박 객체 탐지: 편파별 모델 구성과 정확도 특성 분석)

  • Yungyo Im;Youjeong Youn;Jonggu Kang;Seoyeon Kim;Yemin Jeong;Soyeon Choi;Youngmin Seo;Yangwon Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.5_3
    • /
    • pp.997-1008
    • /
    • 2023
  • Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

Design and Manufacture of FMCW Radar with Multi-Frequency Bandwidths (다중 대역폭을 갖는 FMCW 레이다 송수신기 설계 및 제작)

  • Hwang, Ji-hwan;Kim, Seung Hee;Kang, Ki-mook;Kim, Duk-Jin
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.27 no.4
    • /
    • pp.377-387
    • /
    • 2016
  • Design of X-band frequency FMCW based imaging radar with multi-resolutions and performances of the self-manufactured radar system are presented in this study. In order to implement the multi-bandwidths, a ramp sequence of the FMCW signal is consisting of two kinds of 'saw-tooth' waveform with different bandwidth, and a receiver circuit consisting of L-band source and frequency converter circuit is used to effectively extract spectra of beat-frequency from the received signal of X-band frequency. The system setups for performance measurement of self-manufactured radar system are maximum output power of 35 dBm, sampling frequency of 1.2 MHz and sweep time of 1 ms. Then, the measured resolutions of the modulated signal having bandwidth of 500 MHz and 300 MHz in range & azimuth-direction are (0.28 m, 0.26 m) and (0.44 m, 0.27 m), respectively.

Prediction of Daily PM10 Concentration for Air Korea Stations Using Artificial Intelligence with LDAPS Weather Data, MODIS AOD, and Chinese Air Quality Data

  • Jeong, Yemin;Youn, Youjeong;Cho, Subin;Kim, Seoyeon;Huh, Morang;Lee, Yangwon
    • Korean Journal of Remote Sensing
    • /
    • v.36 no.4
    • /
    • pp.573-586
    • /
    • 2020
  • PM (particulate matter) is of interest to everyone because it can have adverse effects on human health by the infiltration from respiratory to internal organs. To date, many studies have made efforts for the prediction of PM10 and PM2.5 concentrations. Unlike previous studies, we conducted the prediction of tomorrow's PM10 concentration for the Air Korea stations using Chinese PM10 data in addition to the satellite AOD and weather variables. We constructed 230,639 matchups from the raw data over 3 million and built an RF (random forest) model from the matchups to cope with the complexity and nonlinearity. The validation statistics from the blind test showed excellent accuracy with the RMSE (root mean square error) of 9.905 ㎍/㎥ and the CC (correlation coefficient) of 0.918. Moreover, our prediction model showed a stable performance without the dependency on seasons or the degree of PM10 concentration. However, part of coastal areas had a relatively low accuracy, which implies that a dedicated model for coastal areas will be necessary. Additional input variables such as wind direction, precipitation, and air stability should also be incorporated into the prediction model as future work.

Revisit the Cause of the Cold Surge in Jeju Island Accompanied by Heavy Snow in January 2016 (2016년 1월 폭설을 동반한 제주도 한파의 원인 재고찰)

  • Han, Kwang-Hee;Ku, Ho-Young;Bae, Hyo-Jun;Kim, Baek-Min
    • Atmosphere
    • /
    • v.32 no.3
    • /
    • pp.207-221
    • /
    • 2022
  • In Jeju, on January 23, 2016, a cold surge accompanied by heavy snowfall with the most significant amount of 12 cm was the highest record in 32 years. During this period, the temperature of 850 hPa in January was the lowest in 2016. Notably, in 2016, the average surface temperature of January on the Polar cap was the highest since 1991, and 500 hPa geopotential height also showed the highest value. With this condition, the polar vortex in the northern hemisphere meandered and expanded into the subtropics regionally, covering the Korean Peninsula with very high potential vorticity up to 7 Potential Vorticity Unit. As a result, the strong cold advection, mostly driven by a northerly wind, around the Korean Peninsula occurred at over 2𝜎. Previous studies have not addressed this extreme synoptic condition linked to polar vortex expansion due to the unprecedented Arctic warming. We suggest that the occurrence of a strong Ural blocking event after the abrupt warming of the Barents/Karas seas is a major cause of unusually strong cold advection. With a specified mesoscale model simulation with SST (Sea Surface Temperature), we also show that the warmer SST condition near the Korean Peninsula contributed to the heavy snowfall event on Jeju Island.

The Study of Docent System Improvement for Revitalization of Science Museum (과학관 활성화를 위한 도슨트 제도 개선 연구)

  • Park, Young-Shin;Lee, Jung-Hwa
    • Journal of the Korean earth science society
    • /
    • v.33 no.2
    • /
    • pp.200-215
    • /
    • 2012
  • The revitalization of science museum depends on the number of qualified docents who can meet the museum visitors' educational needs. However, the current unstructured docent system is not sufficient to meet the goal. Forty six docents currently working in science museums were surveyed about docent training program, current working conditions, and docent professional program in order to propose a viable system providing a docent profession. Data were collected through surveys with 46 docents, interviews with two experienced docents, and several artifacts from the science museum and selected docents. The surveys consisted of 47 items asking about personal biography, docent's perception, docents training program they took, current working conditions, and supplementary professional program. The conclusion of this study is as follows; First, there must be recognition about docents who can play educator's roles which are different from those of general volunteers in terms of recruiting and training system in science museum. Second, docents need to take training and supplementary professional courses that focus on observing and educating visitors in the field. Third, we need a docent management system by employing a well structured evaluating tools. A well established docent system will bring forth the enhancement of science museum education and the increase of science popularization by providing visitors with the quality educational services.

Prediction Skill of GloSea5 model for Stratospheric Polar Vortex Intensification Events (성층권 극소용돌이 강화사례에 대한 GloSea5의 예측성 진단)

  • Kim, Hera;Son, Seok-Woo;Song, Kanghyun;Kim, Sang-Wook;Kang, Hyun-Suk;Hyun, Yu-Kyung
    • Journal of the Korean earth science society
    • /
    • v.39 no.3
    • /
    • pp.211-227
    • /
    • 2018
  • This study evaluates the prediction skills of stratospheric polar vortex intensification events (VIEs) in Global Seasonal Forecasting System (GloSea5) model, an operational subseasonal-to-seasonal (S2S) prediction model of Korea Meteorological Administration (KMA). The results show that the prediction limits of VIEs, diagnosed with anomaly correlation coefficient (ACC) and mean squared skill score (MSSS), are 13.6 days and 18.5 days, respectively. These prediction limits are mainly determined by the eddy error, especially the large-scale eddy phase error from the eddies with the zonal wavenumber 1. This might imply that better prediction skills for VIEs can be obtained by improving the model performance in simulating the phase of planetary scale eddy. The stratospheric prediction skills, on the other hand, tend to not affect the tropospheric prediction skills in the analyzed cases. This result may indicate that stratosphere-troposphere dynamic coupling associated with VIEs might not be well predicted by GloSea5 model. However, it is possible that the coupling process, even if well predicted by the model, cannot be recognized by monotonic analyses, because intrinsic modes in the troposphere often have larger variability compared to the stratospheric impact.

Acoustic images of the submarine fan system of the northern Kumano Basin obtained during the experimental dives of the Deep Sea AUV URASHIMA (심해 자율무인잠수정 우라시마의 잠항시험에서 취득된 북 구마노 분지 해저 선상지 시스템의 음향 영상)

  • Kasaya, Takafumi;Kanamatsu, Toshiya;Sawa, Takao;Kinosita, Masataka;Tukioka, Satoshi;Yamamoto, Fujio
    • Geophysics and Geophysical Exploration
    • /
    • v.14 no.1
    • /
    • pp.80-87
    • /
    • 2011
  • Autonomous underwater vehicles (AUVs) present the important advantage of being able to approach the seafloor more closely than surface vessel surveys can. To collect bathymetric data, bottom material information, and sub-surface images, multibeam echosounder, sidescan sonar (SSS) and subbottom profiler (SBP) equipment mounted on an AUV are powerful tools. The 3000m class AUV URASHIMA was developed by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). After finishing the engineering development and examination phase of a fuel-cell system used for the vehicle's power supply system, a renovated lithium-ion battery power system was installed in URASHIMA. The AUV was redeployed from its prior engineering tasks to scientific use. Various scientific instruments were loaded on the vehicle, and experimental dives for science-oriented missions conducted from 2006. During the experimental cruise of 2007, high-resolution acoustic images were obtained by SSS and SBP on the URASHIMA around the northern Kumano Basin off Japan's Kii Peninsula. The map of backscatter intensity data revealed many debris objects, and SBP images revealed the subsurface structure around the north-eastern end of our study area. These features suggest a structure related to the formation of the latest submarine fan. However, a strong reflection layer exists below ~20 ms below the seafloor in the south-western area, which we interpret as a denudation feature, now covered with younger surface sediments. We continue to improve the vehicle's performance, and expect that many fruitful results will be obtained using URASHIMA.

Detection of Wildfire Burned Areas in California Using Deep Learning and Landsat 8 Images (딥러닝과 Landsat 8 영상을 이용한 캘리포니아 산불 피해지 탐지)

  • Youngmin Seo;Youjeong Youn;Seoyeon Kim;Jonggu Kang;Yemin Jeong;Soyeon Choi;Yungyo Im;Yangwon Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.6_1
    • /
    • pp.1413-1425
    • /
    • 2023
  • The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

ANALYSIS OF THE MOTION OF A TETHER-PERTURBED SATELLITE

  • Cho, Sung-Ki;Kim, Jae-Hoon
    • Journal of Astronomy and Space Sciences
    • /
    • v.20 no.4
    • /
    • pp.319-326
    • /
    • 2003
  • The motion of each satellite in a tethered satellite system is non-Keplerian in the Earth's gravitational field. In this paper, the tether perturbation force is formulated and compared with the perturbation force due to the Earth's oblateness. Also, the center of mass motion of the tethered satellite system is analyzed. The tether perturbing force on the one of satellites in a tethered satellite system is much bigger than the Earth's oblateness perturbation. The two-body motion approximation of the center of mass is acceptable to describe the motion of the system, when the libration is small.