• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.598-600
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• 2004

In Europe most Earth Observation (EO) data users rely on several EO missions, both to increase sustainability of their service and to widen the range of observation parameters. In addition to its own missions such as ERS 1 &2, ENVISAT and the Earth Explorers, ESA therefore offers access to the scientific and applications community to so-called 'Third Party Missions'. Third Party (TP) missions are complementing the observations of ESA missions, are used to prepare for future ESA missions including cross-calibration and create synergy to favor a wider use of EO data within ESA Member States.

• Journal of Environmental Science International
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• v.10 no.6
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• pp.431-436
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• 2001

Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer In the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentration of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll_a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDl. We studied In find out the relationship between the measured chlorophyll_a from the ship and the estimated chlorophyll_a from the SeaWiFs satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) In the northern part of the East China Sea. Chlorophyll_a =0.121Ln(X) + 0.504, R²= 0.73 (1) We also determined total suspended sediment mass (55) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-.situ data and the ratio (L/sub WN/(490 ㎚)L/sub WN/(555 ㎚) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS = -0.703 Ln(X) + 2.237, R²= 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMl, Terra/MODIS and Orbview/SeaWiFS.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.551-566
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• 2016

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. Especially, the degradation gives bad influence in the analysis of images collected over the scene with complicate surface structure such as urban area. This study proposes a multi-stage image restoration to improve the accuracy of detailed analysis for the images collected over the complicate scene. The proposed method assumes a Gaussian additive noise, Markov random field of spatial continuity, and blurring proportional to the distance between the pixels. Point-Jacobian Iteration Maximum A Posteriori (PJI-MAP) estimation is employed to restore a degraded image. The multi-stage process includes the image segmentation performing region merging after pixel-linking. A dissimilarity coefficient combining homogeneity and contrast is proposed for image segmentation. In this study, the proposed method was quantitatively evaluated using simulation data and was also applied to the two panchromatic images of super-high resolution: Dubaisat-2 data of 1m resolution from LA, USA and KOMPSAT3 data of 0.7 m resolution from Daejeon in the Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution panchromatic imagery.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1095-1106
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• 2019

Damage of forest fire should be investigated quickly and accurately for recovery, compensation and prevention of secondary disaster. Using remotely sensed data, burn severity is investigated based on the difference of reflectance or spectral indices before and after forest fire. Recently, the use of high resolution satellite and UAV imagery is increasing, but it is not easy to obtain an image before forest fire that cannot be predicted where and when. This study tried to analyze availability of high-resolution images and supervised classifiers on the burn severity classification. Two supervised classifiers were applied to the KOMPSAT-3A image and the UAV multispectral image acquired after the forest fire. The maximum likelihood (MLH) classifier use absolute value of spectral reflectance and the spectral angle mapper (SAM) classifier use pattern of spectra. As a result, in terms of spatial resolution, the classification accuracy of the UAV image was higher than that of the satellite image. However, both images shown very high classification accuracy, which means that they can be used for classification of burn severity. In terms of the classifier, the maximum likelihood method showed higher classification accuracy than the spectral angle mapper because some classes have similar spectral pattern although they have different absolute reflectance. Therefore, burn severity can be classified using the high resolution multispectral images after the fire, but an appropriate classifier should be selected to get high accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.325-331
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• 2015

This paper suggests an intersection method to improve the accuracy of three-dimensional position from heterogeneous satellite stereo images, and addresses validation of the suggested method following the experimental results. The three-dimensional position is achieved by determining an intersection point of two rays that have been precisely adjusted through the sensor orientation. In case of conventional homogeneous satellite stereo images, the intersection point is generally determined as a mid-point of the shortest line that links two rays in at least square fashion. In this paper, a refined method, which determines the intersection point upon the ray adjusted at the higher resolution image, was used to improve the positioning accuracy of heterogeneous satellite images. Those heterogeneous satellite stereo pairs were constituted using two KOMPSAT-2 and QuickBird images of covering the same area. Also, the positioning results were visually compared in between the conventional intersection and the refined intersection, while the quantitative analysis was performed. The results demonstrated that the potential of refined intersection improved the positioning accuracy of heterogeneous satellite stereo pairs; especially, with a weak geometry of the heterogeneous satellite stereo, the greater effects on the accuracy improvement.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of Astronomy and Space Sciences
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• v.35 no.3
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• pp.175-183
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• 2018

Many recent satellites have mission periods longer than 10 years; thus, satellite-based local space weather monitoring is becoming more important than ever. This article describes the instruments and data applications of the Korea Space wEather Monitor (KSEM), which is a space weather payload of the GeoKompsat-2A (GK-2A) geostationary satellite. The KSEM payload consists of energetic particle detectors, magnetometers, and a satellite charging monitor. KSEM will provide accurate measurements of the energetic particle flux and three-axis magnetic field, which are the most essential elements of space weather events, and use sensors and external data such as GOES and DSCOVR to provide five essential space weather products. The longitude of GK-2A is $128.2^{\circ}E$, while those of the GOES satellite series are $75^{\circ}W$ and $135^{\circ}W$. Multi-satellite measurements of a wide distribution of geostationary equatorial orbits by KSEM/GK-2A and other satellites will enable the development, improvement, and verification of new space weather forecasting models. KSEM employs a service-oriented magnetometer designed by ESA to reduce magnetic noise from the satellite in real time with a very short boom (1 m), which demonstrates that a satellite-based magnetometer can be made simpler and more convenient without losing any performance.

• Aerospace Engineering and Technology
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• v.5 no.2
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• pp.213-219
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• 2006

Korea Aerospace Research Institute(KARI) performed field campaigns for absolute radiometric calibration with overpassing of satellite Orbview-3 on Cal/ Val site in Goheung and Daejeon. The performed Cal/Val method is the reflectance-based of vicarious calibration methods. We collected ground-based and meteology data such as temperature, surface pressure and reflectance of targets, and radiosonde data only collected on Goheung. Data collected on each field served as input to radiative transfer codes to generate a top-of-atmosphere(TOA) radiance. Derived TOA is compared with DN of overpassing satellite Orbview-3 to calculate calibration coefficient of gain and offset. Also, This study proposed a proper method to prepare absolute radiometic calibration of KOMPSAT-2 by using experience of Field campaign.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.195-203
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• 2008

Burn severity is an important role for rehabilitation of burned forest area. This factor led to the pilot study to determine if high resolution IKONOS images could be used to classify and delinenate the bum severity over burned areas of Samchock Fire and Cheongyang-Yesan Fire. The results of this study can be summarized as follows: 1. The modified Normalized Bum Ratio (NBR) for IKONOS imagery can be evaluated using burn severity mapping. 2. IKONOS-derived NBR imagery could provide fire scar and detail mapping of burned areas at Samchock fire and Cheongyang-Yesan Burns.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.104-113
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• 2012

Followed by that HTML5(Hypertext Markup Language5) was introduced, many kinds of program and services based on this have been developed and released. HTML5 is technical standard specifications for cross platform for personal computers and mobile devices so that it is expected that continuing progress and wide application in the both sides of the academic and the industrial fields increase. This study is to design and implement a mobile application program for overlay rendering with DEM and other geo-based image sets using HTML5 WebGL for 3D graphic processing on web environment. Particularly, the blending technique was used for overlay processing with multiple images. Among available WebGL frameworks, CubicVR.js was adopted, and various blending techniques were provided in the user interface for general users. For the actual application in the study area around the Sejong city, serveral types of geo-based data sets were used and processed: KOMPSAT-2 images, ALOS PALSAR SAR images, and grid data by environment measurements. While, DEM for 3D viewing with these geo-based images was produced using contour information of the digital map sets. This work demonstrates possibilities that new types of contents and service system using geo-based images can be extracted and applied.