• Title/Summary/Keyword: Mission software

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Current Status and Results of In-orbit Function, Radiometric Calibration and INR of GOCI-II (Geostationary Ocean Color Imager 2) on Geo-KOMPSAT-2B (정지궤도 해양관측위성(GOCI-II)의 궤도 성능, 복사보정, 영상기하보정 결과 및 상태)

  • Yong, Sang-Soon;Kang, Gm-Sil;Huh, Sungsik;Cha, Sung-Yong
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1235-1243
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    • 2021
  • Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

Development of CanSat System for Collecting Weather Information With Autorotating Science Payload Ejection Function (자동회전 과학 탑재체 사출 기능을 갖춘 기상정보 수집용 캔위성 체계 개발)

  • Kim, Youngjun;Park, Junsoo;Nam, Jaeyoung;Lee, Junhyuck;Choi, Yunwon;Yoo, Seunghoon;Lee, Sanghyun;Lee, Younggun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.573-581
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    • 2022
  • This paper deals with the development of CanSat system, which ejects two maple seed-type autorotating science payloads and collects weather information. The CanSat consists of two autorotating science payloads and a container. The container is equipped with devices for launching science payloads and communication with the ground station, and launches science payloads one by one at different designated altitudes. The science payload consists of a space for loading and a large wing, and rotates to generate lift for slowing down the fall speed. Specifically, after being ejected, it descends at a speed of 20 m/s or less, measures the rotation rate, atmospheric pressure, and temperature, and transmits the measured value to the container at a rate of once per second. The communication system is a master-slave structure, and the science payload transmits all data to the master container, which aggregates both the received data and its own data, and transmits it to the ground station. All telemetry can be checked in real time using the ground station software developed in-house. A simulation was performed in the simulation environment, and the performance of the CanSat system that satisfies the mission requirements was confirmed.

Experimental Performance Validation of an Unmanned Surface Vessel System for Wide-Area Sensing and Monitoring of Hazardous and Noxious Substances (HNS 광역 탐지 및 모니터링을 위한 부유식 무인이동체 시스템의 실험적 성능 검증)

  • Jinwook Park;Jinsik Kim;Jinwhan Kim;Yongmyung Kim;Moonjin Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.spc
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    • pp.11-17
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    • 2022
  • In this study, we address the development of a floating platform system based on a unmanned surface vessel for wide-area sensing and monitoring of hazardous and noxious substances (HNSs). For long endurance, a movable floating platform with no mooring lines was used and modified for HNS sensing and monitoring. The floating platform was equipped with various sensors such as optical and thermal imaging cameras, marine radar, and sensors for detecting HNSs in water and air. Additionally, for experiment validation in real outdoor environments, a portable gas-exposure system (PGS) was built and installed on the monitoring system. The software for carrying out the mission was integrated with the Robot Operating System (ROS) framework. The practical feasibility of the developed system was verified through experimental tests conducted in inland water and real-sea environments.

Soil Moisture Estimation Using KOMPSAT-3 and KOMPSAT-5 SAR Images and Its Validation: A Case Study of Western Area in Jeju Island (KOMPSAT-3와 KOMPSAT-5 SAR 영상을 이용한 토양수분 산정과 결과 검증: 제주 서부지역 사례 연구)

  • Jihyun Lee;Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1185-1193
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    • 2023
  • The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.