• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.221-233
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• 2000

An intertidal topography is continuously changed due to morphodynamics processes. Detection and measurement of topographic change for a tidal flat is important to make an integrated coastal area management plan as well as to carry out sedimentologic study. The objective of this study is to generate intertidal DEM using leveling data and waterlines extracted from optical and microwave remotely sensed data in a relatively short period. Waterline is defined as the border line between exposed tidal flat and water body. The contour of the terrain height in tidal flat is equivalent to the waterline. One can utilize satellite images to generate intertidal DEM over large areas. Extraction of the waterline in a SAR image is a difficult task to perform partly because of the presence of speckle and partly because of similarity between the signal returned from the sea surface and that from the exposed tidal flat surface or land. Waterlines in SAR intensity and coherence map can effectively be extracted with MSP-RoA edge detector. From multiple images obtained over a range of tide elevation, it is possible to build up a set of heighted waterline within intertidal zone, and then a gridded DEM can be interpolated. We have tested the proposed method over the Gomso Bay, and succeeded in generating intertidal DEM with relatively high accuracy.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.46.3-46.3
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• 2009

The SAR (Synthetic Aperture Radar) satellite has the advantage of implementing the imaging mission even though it is night time, cloudy weather, and all weather conditions, which is different from the satellite with the optical payload. This is the reason why the SAR satellite comes into the spotlight in the observation satellite field. The Korea Aerospace Research Institute (KARI) has been developing the first Korean SAR satellite and is currently integrating and testing the Flight Model. For the launch vehicle service, KARI finalized the selection of the launch vehicle service provider and finished Critical Design Review (CDR) of the interface between the bus and the launch vehicle. KARI and launch vehicle service provider also finished the test of the telemetry interface between the bus and the launch vehicle. The test of the telemetry interface has the purpose of checking the interface of the telemetry which is the SOH(State-of-Health) of the satellite in an early launch stage. For this test, KARI has finished the development of the spacecraft simulator which is composed of the bus simulator to generate the analog telemetry and the launch vehicle simulator to gather the telemetry. In this research, the result of the hardware implementation and the software implementation for the spacecraft simulator were described. Finally the results of the launch vehicle telemetry MUX test which were performed at the launch vehicle provider's design office by using the spacecraft simulator were summarized. It is expected that this simulator will be used in the next test after the manufacture of the launch vehicle.

• Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.38-46
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• 2015

Augmented reality based on projection, called "Spatial Augmented Reality (SAR)", is a new technology that can produce immersive contents by overlapping virtuality and real-world environment. It has been paid attention as the next generation digital contents in media art and human-computer interaction (HCI). In this paper, we present a new methodology to evaluate the product appearance design more intuitively by means of SAR technique. The proposed method first projects the high-quality rendered image considering the optical property of materials onto the mock-up of a product. We also conduct a projector-camera calibration to compensate a color distortion according to a projector, a projection surface and environment lighting. The design evaluation methodology we propose offers more flexible and intuitive evaluation environment to a designer and user (evaluator) than previous methods that are performed via a digital display. At the end of this research, we have conducted a case study for designing and evaluating appearance design of an automobile.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Journal of the Korean Vacuum Society
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• v.11 no.2
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• pp.87-96
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• 2002

Outgassing from such sources as paints, coatings, adhesives and other non-metallic surfaces can contaminate satellites, especially second surface mirror and optical lens, it cause satellite to fail in own missions. The vacuum bake-out test using high temperature(more than $85 ^{\circ}C$)and high vacuum(less than $5.0{\times}1-^{-3}$ Pa) certify that the components of satellite work properly and can survive and operate in space environment like high vacuum. In the bake-out chamber installed at SITC of KARI, Rotary vacuum pump and Booster pump produce low vacuum of 5.0 Pa, and then two cryopumps produce high vacuum of below $5.0{\times}10^{-3}$ Pa. Also 48 ceramic heaters were provided to simulate high temperature. During the vacuum bake-out test, we detected contaminants using RGA(Residual Gas Analyzer) and measure the outgassing rate of the contaminant using the TQCM(Thermoelectric Quartz Crystal Microbalance). Also, IR/UV Spectrometer and witness plate be used to certify that the components were suitable for the spacecraft. This paper includes the preparation and procedures of the bake-out test for SAR(Solar Array Regulator) and MLI(Multi Layer Insulator), which were the components of the spacecraft. Especially, we discussed the methods and results of the contamination measurement. In the bake-out for SAR, the contamination was measured continuously although it was on the decrease from TQCM results. And RCA established that it is a highly polymerized compound. In the MLI bake-out using RGA and witness plate, we didn't detect any contamination materials.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.211-219
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• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.