• Title/Summary/Keyword: 우주탐사

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The Estimation of Gross Primary Productivity over North Korea Using MODIS FPAR and WRF Meteorological Data (MODIS 광합성유효복사흡수율과 WRF 기상자료를 이용한 북한지역의 총일차생산성 추정)

  • Do, Na-Young;Kang, Sin-Kyu;Myeong, Soo-Jeong;Chun, Tae-Hun;Lee, Ji-Hye;Lee, Chong-Bum
    • Korean Journal of Remote Sensing
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    • v.28 no.2
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    • pp.215-226
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    • 2012
  • NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.

Characteristic Response of the OSMI Bands to Estimate Chlorophyll $\alpha$ (클로로필 $\alpha$ 추정시 OSMI 밴드의 광학 반응 특성)

  • 서영상;이나경;장이현;황재동;유신재;임효숙
    • Korean Journal of Remote Sensing
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    • v.18 no.4
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    • pp.187-199
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    • 2002
  • Correlation between chlorophyll a in the East China Sea and spectral bands (412, 443, 490, (510), 555, (676, 765)nm) of Ocean Scanning Multi-Spectral Imager (OSMI) including the profile multi-spectral radiometer (PRR-800) was studied. The values of remote sensing reflectance (Rrs) at the bands corresponding to the field chlorophyll $\alpha$ in the East China Sea were much higher than those in clear waters off California, USA. In case of the particle absorptions related to the chlorophyll a concentration at the spectral bands (440, 670nm) were much higher in the East China Sea than the ones in the clean waters off California. The normalized water leaving radiances (nLw) at 412, 443, 490, 555 nm of OSMI and the field chlorophyll a in the East China Sea were correlated each other. According to the results, the relationship between field chlorophyll $\alpha$ and nLw 410 nm in OSMI bands was the lowest, whereas that between field chlorophyll a and nLw 555 nm in the bands was the highest. Reciprocal action between the field chlorophyll a and the band ratio of the OSMI bands (nLw410/nLw555, nLw443/nLw555, nLw490/nLw555) was also studied. Relationship between the chlorophyll $\alpha$ and the band ratio (nLw490/nLw555) was highest in the OSMI bands. Relationship between the chlorophyll $\alpha$ and the ratio (nLw490/nLw555) was higher than one in the nLw410/nLw555. The difference in the estimated chlorophyll $\alpha$ (mg/m$^3$) between OSMI and SeaWiFS (Sea Viewing Wide Field-of-View Sensor) at the special observing stations in the northern eastern sea of Jeju Island in February 25, 2002 was about less than 0.3 mg/m$^3$ within 3 hours. It is suggested that OC2 (ocean color chlorophyll 2 algorithm) be used to get much better estimation of chlorophyll $\alpha$ from OSMI than the ones from the updated algorithms as OC4.

Detection of Forest Fire Damage from Sentinel-1 SAR Data through the Synergistic Use of Principal Component Analysis and K-means Clustering (Sentinel-1 SAR 영상을 이용한 주성분분석 및 K-means Clustering 기반 산불 탐지)

  • Lee, Jaese;Kim, Woohyeok;Im, Jungho;Kwon, Chunguen;Kim, Sungyong
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1373-1387
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    • 2021
  • Forest fire poses a significant threat to the environment and society, affecting carbon cycle and surface energy balance, and resulting in socioeconomic losses. Widely used multi-spectral satellite image-based approaches for burned area detection have a problem in that they do not work under cloudy conditions. Therefore, in this study, Sentinel-1 Synthetic Aperture Radar (SAR) data from Europe Space Agency, which can be collected in all weather conditions, were used to identify forest fire damaged area based on a series of processes including Principal Component Analysis (PCA) and K-means clustering. Four forest fire cases, which occurred in Gangneung·Donghae and Goseong·Sokcho in Gangwon-do of South Korea and two areas in North Korea on April 4, 2019, were examined. The estimated burned areas were evaluated using fire reference data provided by the National Institute of Forest Science (NIFOS) for two forest fire cases in South Korea, and differenced normalized burn ratio (dNBR) for all four cases. The average accuracy using the NIFOS reference data was 86% for the Gangneung·Donghae and Goseong·Sokcho fires. Evaluation using dNBR showed an average accuracy of 84% for all four forest fire cases. It was also confirmed that the stronger the burned intensity, the higher detection the accuracy, and vice versa. Given the advantage of SAR remote sensing, the proposed statistical processing and K-means clustering-based approach can be used to quickly identify forest fire damaged area across the Korean Peninsula, where a cloud cover rate is high and small-scale forest fires frequently occur.

Introduction on the Products and the Quality Management Plans for GOCI-II (천리안 해양위성 2호 산출물 및 품질관리 계획)

  • Lee, Sun-Ju;Lee, Kyeong-Sang;Han, Tae Hyun;Moon, Jeong-Eon;Bae, Sujung;Choi, Jong-kuk
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1245-1257
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    • 2021
  • GOCI-II, succeeding the mission of GOCI, was launched in February 2020 and has been in regular operation since October 2020. Korea Institute of Ocean Science and Technology (KIOST) processes and produces in real time Level-1B and 26 Level-2 outputs, which then are provided by Korea Hydrographic and Oceanographic Agency (KHOA). We introduced current status of regular GOCI-II operation and showed future improvement. Basic GOCI-II products including chlorophyll-a, total suspended materials, and colored dissolved organic matter concentration, are induced by OC4 and YOC algorithms, which were described in detail. For the full disk (FD), imaging schedule was established considering solar zenith angle and sun glint during the in-orbital test, but improved by further considering satellite zenith angle. The number of slots satisfying the condition 'Best Ocean' significantly increased from 15 to 78. GOCI-II calibration requirements were presented based on that by European Space Agency (ESA) and candidate fixed locations for calibrating local observation area were. The quality management of FD uses research ships and overseas bases of KIOST, but it is necessary to establish an international calibration/validation network. These results are expected to enhance the understanding of users for output processing and help establish detailed plans for future quality management tasks.

Detection of Surface Changes by the 6th North Korea Nuclear Test Using High-resolution Satellite Imagery (고해상도 위성영상을 활용한 북한 6차 핵실험 이후 지표변화 관측)

  • Lee, Won-Jin;Sun, Jongsun;Jung, Hyung-Sup;Park, Sun-Cheon;Lee, Duk Kee;Oh, Kwan-Young
    • Korean Journal of Remote Sensing
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    • v.34 no.6_4
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    • pp.1479-1488
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    • 2018
  • On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

Improvement of Mid-Wave Infrared Image Visibility Using Edge Information of KOMPSAT-3A Panchromatic Image (KOMPSAT-3A 전정색 영상의 윤곽 정보를 이용한 중적외선 영상 시인성 개선)

  • Jinmin Lee;Taeheon Kim;Hanul Kim;Hongtak Lee;Youkyung Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1283-1297
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    • 2023
  • Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.

Analysis of Applicability of RPC Correction Using Deep Learning-Based Edge Information Algorithm (딥러닝 기반 윤곽정보 추출자를 활용한 RPC 보정 기술 적용성 분석)

  • Jaewon Hur;Changhui Lee;Doochun Seo;Jaehong Oh;Changno Lee;Youkyung Han
    • Korean Journal of Remote Sensing
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    • v.40 no.4
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    • pp.387-396
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    • 2024
  • Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

A Study on the Legislation for the Commercial and Civil Unmanned Aircraft System Operation (국내 상업용 민간 무인항공기 운용을 위한 법제화 고찰)

  • Kim, Jong-Bok
    • The Korean Journal of Air & Space Law and Policy
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    • v.28 no.1
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    • pp.3-54
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    • 2013
  • Nowadays, major advanced countries in aviation technology are putting their effort to develop commercial and civil Unmanned Aircraft System(UAS) due to its highly promising market demand in the future. The market scale of commercial and civil UAS is expected to increase up to approximately 8.8 billon U.S. dollars by the year 2020. The usage of commercial and civil UAS covers various areas such as remote sensing, relaying communications, pollution monitoring, fire detection, aerial reconnaissance and photography, coastline monitoring, traffic monitoring and control, disaster control, search and rescue, etc. With the introduction of UAS, changes need to be made on current Air Traffic Management Systems which are focused mainly manned aircrafts to support the operation of UAS. Accordingly, the legislation for the UAS operation should be followed. Currently, ICAO's Unmanned Aircraft System Study Group(UASSG) is leading the standardization process of legislation for UAS operation internationally. However, some advanced countries such as United States, United Kingdom, Australia have adopted its own legislation. Among these countries, United States is most forth going with President Obama signing a bill to integrate UAS into U.S. national airspace by 2015. In case of Korea, legislation for the unmanned aircraft system is just in the beginning stage. There are no regulations regarding the operation of unmanned aircraft in Korea's domestic aviation law except some clauses regarding definition and permission of the unmanned aircraft flight. However, the unmanned aircrafts are currently being used in military and under development for commercial use. In addition, the Ministry of Land, Infrastructure and Transport has a ambitious plan to develop commercial and civil UAS as Korea's most competitive area in aircraft production and export. Thus, Korea is in need of the legislation for the UAS operation domestically. In this regards, I personally think that Korea's domestic legislation for UAS operation will be enacted focusing on following 12 areas : (1)use of airspace, (2)licenses of personnel, (3)certification of airworthiness, (4)definition, (5)classification, (6)equipments and documents, (7)communication, (8)rules of air, (9)training, (10)security, (11)insurance, (12)others. Im parallel with enacting domestic legislation, korea should contribute to the development of international standards for UAS operation by actively participating ICAO's UASSG.

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CAS 500-1/2 Image Utilization Technology and System Development: Achievement and Contribution (국토위성정보 활용기술 및 운영시스템 개발: 성과 및 의의)

  • Yoon, Sung-Joo;Son, Jonghwan;Park, Hyeongjun;Seo, Junghoon;Lee, Yoojin;Ban, Seunghwan;Choi, Jae-Seung;Kim, Byung-Guk;Lee, Hyun jik;Lee, Kyu-sung;Kweon, Ki-Eok;Lee, Kye-Dong;Jung, Hyung-sup;Choung, Yun-Jae;Choi, Hyun;Koo, Daesung;Choi, Myungjin;Shin, Yunsoo;Choi, Jaewan;Eo, Yang-Dam;Jeong, Jong-chul;Han, Youkyung;Oh, Jaehong;Rhee, Sooahm;Chang, Eunmi;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.867-879
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    • 2020
  • As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.