• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.152-153
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• 2023

AIS has been widely used for maritime traffic assessment for its convenience. However, AIS has problems with position missing due to radio interference and transmission distance limit. On the other hand, satellite radar determines the location of ships over a wide sea regardless of the problems. This study proposes a noble method of stepwise threshold determination to detect ships from Sentinel-1. The proposed method is up to 25 times faster than the existing moving window-based threshold determination method, and the detection accuracy is similar.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.4-4
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• 2023

C-band SAR 센서를 탑재한 수자원위성은 한반도 수자원 모니터링을 위해 개발되어 2025년 발사가 계획되어 있으며, 수변환경 및 부유물 탐지 및 다양한 활용이 기대되고 있다. 그 중 수변환경은 수변 생태계 안정성을 유지하는 역할을 담당하여 이에 대한 모니터링은 중요하다. s현장 관측 기반 탐지 방법과 비교하여 위성 원격탐사는 광범위한 지역을 반복적으로 관측하여, 연속적인 수변환경 및 부유물 정보를 제공할 수 있다. 이러한 특성에 기반하여 다양한 다중분광 및 SAR (Synthetic Aperture Radar) 위성 원격탐사 자료를 바탕으로 수변환경 및 부유물의 탐지 연구가 이루어졌다. 특히 단일 영상만을 사용하는 기법에 비해 다중분광 및 SAR 영상을 융합하여 높은 정확도를 보인 바 있다. 초기 연구에서는 임계값 알고리즘 또는 현장관측 기반의 부유물 농도와 위성 자료간의 선형관계를 분석하는 단순한 알고리즘이 주를 이루었으나, 최근에는 RF, CNN 등 보다 복잡하고 다양한 인공지능 알고리즘이 적용되어 높은 정확도로 해당 문제들을 해결하고 있다. 본 연구에서는 수자원위성 활용을 위해 인공지능 기반 수변환경 및 부유물 탐지 알고리즘을 개발하고자 한다. 수자원위성의 대체 자료로 유럽우주국의 Sentinel-1 A/B 위성의 C-band SAR 영상을 이용하였으며, 보조자료로 Sentinel-2 다중분광 영상을 이용하였다. 개발된 알고리즘은 수자원 관리를 위한 환경변화 탐지에 유용한 정보로 활용될 수 있을 것으로 기대된다.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1457-1468
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• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.1
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• pp.54-62
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• 2017

For the Earth observation satellite for ISR mission, a satellite constellation can be utilized to observe a specific area periodically and ultimately increase the effectiveness of the mission. The Walker-Delta method was applied to design constellation orbits with four satellites, which could detect abnormal activities in AoI(Area of Interest). To evaluate the effectiveness of the mission, a revisiting time was selected as a key requirement. This paper presents the mission analysis process for four SAR satellites constellation as well as the result of constellation configuration design to meet the requirements. Figure of Merits analysis was performed based on algorithm developed. Finally, it was confirmed that the constellation orbit with four different orbital planes is likely to be appropriate for ISR mission.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.49-56
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• 2022

S-STEP is a small SAR satellite mission that monitors time-limited emergency targets and military anomalies in areas of interest, achieving the average revisit in less than 30 minutes by deploying a constellation of 32 satellites in low orbit at an altitude of 510 km. The mission operation mode of S-STEP is divided into normal mode, observation mode, communication mode, and orbit maintenance mode. Further,, the attitude control mode is subdivides into initial detumbling, sun pointing, target pointing, ground station pointing, and thrust direction maintenance. Based on the preliminary mission operational scenario and the satellite's characteristics, this study analyzed the attitude control performance during initial detumbling and observation modes. It verifies that each mode's attitude control accuracy requirements within the time allotted by the scenario of the S-STEP achieved.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.365-377
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• 2020

Continuous monitoring and immediate response is essential to protect the national maritime territory and maritime resources from the activities of illegal ships. Synthetic Aperture Radar (SAR) images with a wide range of images are effective for maritime surveillance asthe weather and day-night conditions rarely affect to image acquisition. However, an effective ship detection is not easy due to the huge data size of SAR images and various characteristics such as the speckle noise. In this study, the Human Visual Attention System (HVAS) algorithm was applied to KOMPSAT-5 to extract the initial targets, and the SAR-Split algorithm depending on the imaging modes was used to remove false alarms. The detected targets were finally selected by the Constant False Alarm Rate (CFAR) algorithm and matched with the ship's Automatic Identification System (AIS) information. Overall, the detected targets were well matched with AIS data, but some false alarms by ship wakes were observed. The detection rate was about 80% in ES mode and about 64% in ST mode. It is expected that the developed ship detection algorithm will contribute to the construction of a wide area maritime surveillance network.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.315-326
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• 2011

In recent years, domestic and international interests focus on climate change, and importance of forest as carbon sink have been also increased. Particularly REDD+ mechanism expanded from REDD (Reduced Emissions from Deforestation and Degradation) is expected to perform a new mechanism for reducing greenhouse gas in post 2012. To conduct this mechanism, countries which try to get a carbon credit have to certify effectiveness of their activities by MRV (Measuring, Reporting and Verification) system. This study analyzed the approaches for detecting land cover change and estimating carbon stock by remote sensing technology which is considered as the effective method to develop MRV system. The most appropriate remote sensing for detection of land cover change is optical medium resolution sensors and satellite SAR (Synthetic Aperture Radar) according to cost efficiency and uncertainty assessment. In case of estimating carbon stock, integration of low uncertainty techniques, airborne LiDAR (Light Detection and Ranging), SAR, and cost efficient techniques, optical medium resolution sensors and satellite SAR, could be more appropriate. However, due to absence of certificate authority, guideline, and standard of uncertainty, we should pay continuously our attention on international information flow and establish appropriate methods. Moreover, to apply monitoring system to developing countries, close collaboration and monitoring method reflected characteristics of each countries should be considered.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• 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.