• Title/Summary/Keyword: Satellites data

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Analysis of the GPS Error Effect through Simulation (시뮬레이션을 통한 GPS 오차의 영향 분석)

  • Jeon, Jae-Han;Kwon, Jay-Hyoun;Lee, Ji-Sun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.4
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    • pp.397-405
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    • 2008
  • The position accuracy is primarily dependent on the satellite position and signal delay caused by several elements. To know the effect of the delay on the estimated positions, we simulated GPS raw data (RINEX) with GPS errors using Bernese ver5.0. GPS errors used in this paper are Ionospheric delay, Cycle slip, Troposphere, DOP and Random error. If the baseline is short, the position error according to TEC is not large, since the ionospheric delay effect can be removed by ion-free combination. However, if the baseline is long, 3 dimensional position error up to 10cm is occurred. The 3D position error of coordinates with cycle slip is hardly ever changed up to 60% of cycle slip. Because the simulated cycle slips are equally distributed on satellites, the positioning was not seriously affected by the cycle slip. Also, if percentage of cycle slip is 60%, three dimensional error is sharply increased over 1m. The position error is calculated by using the observation data (2 hours) which was selected by DOP less than 3. And its accuracy is more improved about $3{\sim}4cm$.

The Study on the Possibility of Using Satellite in Monitoring Precursor of Magma Activity in the Baegdusan Volcano (인공위성을 이용한 백두산 화산 마그마 활동의 전조현상 인지 가능성 연구)

  • Lee, Deok-Su;Choi, Sung-Chan;Oh, Chang-Whan;Seo, Min-Ho;Ryu, In-Chang
    • The Journal of the Petrological Society of Korea
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    • v.22 no.1
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    • pp.35-47
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    • 2013
  • The Baegdusan Volcano which erupted violently at 1000 AD is still have possibility of eruption. Therefore, it is necessary to monitor regularly the possibility of eruption. However, it is very difficult to install regular monitoring system or to get regularly monitored data due to geopolitic problems. This is why we have to develop regular monitoring technique using satellite. The geoid in the Baegdusan Volcanic area calculated from gravity data obtained from GRACE satellite, decreased from 2002 to 2005. The period of decreasing is well matched with time when magma activities were recognized in the Baegdusan Volcanic area. The decrease in geoid is interpreted to be caused by the decrease of water storage. Considering that the amount of rainfall from 2002 and 2005 is almost constant, the decrease in geoid may be related to the magma activity under the Baegdusan Volcano. The geomagnetic total force in the Baegdusan Volcanic area measured by CHAMP satellite, decreased from 2000 to 2005 and increased after 2005. The period of decrease is well matched with the time with increased activity of magma chamber under the Baegdusan Volcano indicating that the decrease of geomagnetic total force is caused by demagnetization of surrounding rocks due to the increase of temperature of magma chamber. These data indicate the possbility of using change of geoid and geomagnetic total force observed by GRACE and CHAMP satellites for the monitoring of magma activity under the Baegdusan Volcano.

Correlation Between Social Distancing Levels and Nighttime Light (NTL) during COVID-19 Pandemic in Seoul, South Korea Based on The Day-Night Band (DNB) Onboard The Suomi National Polar-Orbiting Partnership (S-NPP) Satellite (코로나19 팬데믹 기간의 서울의 사회적 거리두기 단계 변화와 The Suomi National Polar-Orbiting Partnership (S-NPP) 위성 영상을 이용한 Nighttime Light (NTL) 간의 상관관계)

  • Nur, Arip Syaripudin;Lee, Seulki;Ramayanti, Suci;Han, Ju
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1647-1656
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    • 2021
  • In order to reduce the spread of infection due to COVID-19, South Korea has established a four-step social distancing standard and implemented it by changing the steps based on the rate of confirmed cases. The implementation of social distancing brought about a change in the amount of activity of citizens by limiting social contact such as movement and gathering of people. One of the data that can intuitively confirm this is Night Time Light (NTL). NTL is a variable that can measure the size of the national economy measured using lights captured by satellites, and can be used to understand people's social activities during the night. The NTL visible data is obtained via the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. 1023 of Suomi data from 1 January 2019 until 26 October 2021 were collected to generate time series of NTL radiance change over Seoul to analyze the correlation with social distancing policy. The results show that implementing the level of social distancing generally decreased the NTL radiance both in spatial disparities and temporal patterns. The higher level of policy, limiting human activities combined with the low number of people who have been vaccinated and the closure of various facilities. Because of social distancing, the differences in human activities affected the nighttime light during the COVID-19 pandemic, especially in Seoul, South Korea. Therefore, this study can be used as a reference for the government in evaluating and improving policies related to efforts reducing the transmission of COVID-19.

Application and Analysis of Remote Sensing Data for Disaster Management in Korea - Focused on Managing Drought of Reservoir Based on Remote Sensing - (국가 재난 관리를 위한 원격탐사 자료 분석 및 활용 - 원격탐사기반 저수지 가뭄 관리를 중심으로 -)

  • Kim, Seongsam;Lee, Junwoo;Koo, Seul;Kim, Yongmin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1749-1760
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    • 2022
  • In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.

Spatial Gap-filling of GK-2A/AMI Hourly AOD Products Using Meteorological Data and Machine Learning (기상모델자료와 기계학습을 이용한 GK-2A/AMI Hourly AOD 산출물의 결측화소 복원)

  • Youn, Youjeong;Kang, Jonggu;Kim, Geunah;Park, Ganghyun;Choi, Soyeon;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.953-966
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    • 2022
  • Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

Assessment of Stand-alone Utilization of Sentinel-1 SAR for High Resolution Soil Moisture Retrieval Using Machine Learning (기계학습 기반 고해상도 토양수분 복원을 위한 Sentinel-1 SAR의 자립형 활용성 평가)

  • Jeong, Jaehwan;Cho, Seongkeun;Jeon, Hyunho;Lee, Seulchan;Choi, Minha
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.571-585
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    • 2022
  • As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

Application of convolutional autoencoder for spatiotemporal bias-correction of radar precipitation (CAE 알고리즘을 이용한 레이더 강우 보정 평가)

  • Jung, Sungho;Oh, Sungryul;Lee, Daeeop;Le, Xuan Hien;Lee, Giha
    • Journal of Korea Water Resources Association
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    • v.54 no.7
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    • pp.453-462
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    • 2021
  • As the frequency of localized heavy rainfall has increased during recent years, the importance of high-resolution radar data has also increased. This study aims to correct the bias of Dual Polarization radar that still has a spatial and temporal bias. In many studies, various statistical techniques have been attempted to correct the bias of radar rainfall. In this study, the bias correction of the S-band Dual Polarization radar used in flood forecasting of ME was implemented by a Convolutional Autoencoder (CAE) algorithm, which is a type of Convolutional Neural Network (CNN). The CAE model was trained based on radar data sets that have a 10-min temporal resolution for the July 2017 flood event in Cheongju. The results showed that the newly developed CAE model provided improved simulation results in time and space by reducing the bias of raw radar rainfall. Therefore, the CAE model, which learns the spatial relationship between each adjacent grid, can be used for real-time updates of grid-based climate data generated by radar and satellites.

Operational Ship Monitoring Based on Multi-platforms (Satellite, UAV, HF Radar, AIS) (다중 플랫폼(위성, 무인기, AIS, HF 레이더)에 기반한 시나리오별 선박탐지 모니터링)

  • Kim, Sang-Wan;Kim, Donghan;Lee, Yoon-Kyung;Lee, Impyeong;Lee, Sangho;Kim, Junghoon;Kim, Keunyong;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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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.

Assessment of the Relationship between Air Temperature and TOA Brightness Temperature in Different Seasons Using Landsat-8 TIRS (Landsat-8 위성의 열적외 센서를 활용한 대기온도와 밝기온도의 계절별 상관관계 분석)

  • CHOUNG, Yun-Jae;CHUNG, Youn-In;CHOI, Soo-Young
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.2
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    • pp.68-79
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    • 2018
  • In general, Top Of Atmosphere(TOA) brightness temperature is closely related to air temperature. Brightness temperature can be derived from the Thermal Infra-Red Sensors (TIRS) of the earth observation satellites such as the Landsat series. The TIRS instrument of the Landsat-8 satellite collects the two spectral bands (Bands 10 and 11) that measure brightness temperature. In this research, the relationship between the air temperature data measured by the weather stations in Seoul, South Korea and the brightness temperature data separately derived from Bands 10 and 11 of the Landsat-8 satellite were assessed in the different seasons through the correlation analysis. The statistical results led to the following conclusions. First, brightness temperature is closely related to air temperature in order of Spring, Autumn, Winter and Summer. Second, when air temperature increases, brightness temperature also increases in Spring, Autumn and Winter but decreases in Summer. Third, Band 10 has a closer relationship to air temperature than Band 11.

Automated Improvement of RapidEye 1-B Geo-referencing Accuracy Using 1:25,000 Digital Maps (1:25,000 수치지도를 이용한 RapidEye 위성영상의 좌표등록 정확도 자동 향상)

  • Oh, Jae Hong;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.5
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    • pp.505-513
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    • 2014
  • The RapidEye can acquire the 6.5m spatial resolution satellite imagery with the high temporal resolution on each day, based on its constellation of five satellites. The image products are available in two processing levels of Basic 1B and Ortho 3A. The Basic 1B image have radiometric and sensor corrections and include RPCs (Rational Polynomial Coefficients) data. In Korea, the geometric accuracy of RapidEye imagery can be improved, based on the scaled national digital maps that had been built. In this paper, we present the fully automated procedures to georegister the 1B data using 1:25,000 digital maps. Those layers of map are selected if the layers appear well in the RapidEye image, and then the selected layers are RPCs-projected into the RapidEye 1B space for generating vector images. The automated edge-based matching between the vector image and RapidEye improves the accuracy of RPCs. The experimental results showed the accuracy improvement from 2.8 to 0.8 pixels in RMSE when compared to the maps.