• Title/Summary/Keyword: Satellites data

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Sentinel-1 SAR image-based waterbody detection technique for estimating the water storage in agricultural reservoirs (농업저수지의 저수량 추정을 위한 Sentinel-1 SAR 영상 기반 수체탐지 기법)

  • Jeong, Jaehwan;Oh, Seungcheol;Lee, Seulchan;Kim, Jinyoung;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.54 no.7
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    • pp.535-544
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    • 2021
  • Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

Change Detection for High-resolution Satellite Images Using Transfer Learning and Deep Learning Network (전이학습과 딥러닝 네트워크를 활용한 고해상도 위성영상의 변화탐지)

  • Song, Ah Ram;Choi, Jae Wan;Kim, Yong Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.3
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    • pp.199-208
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    • 2019
  • As the number of available satellites increases and technology advances, image information outputs are becoming increasingly diverse and a large amount of data is accumulating. In this study, we propose a change detection method for high-resolution satellite images that uses transfer learning and a deep learning network to overcome the limit caused by insufficient training data via the use of pre-trained information. The deep learning network used in this study comprises convolutional layers to extract the spatial and spectral information and convolutional long-short term memory layers to analyze the time series information. To use the learned information, the two initial convolutional layers of the change detection network are designed to use learned values from 40,000 patches of the ISPRS (International Society for Photogrammertry and Remote Sensing) dataset as initial values. In addition, 2D (2-Dimensional) and 3D (3-dimensional) kernels were used to find the optimized structure for the high-resolution satellite images. The experimental results for the KOMPSAT-3A (KOrean Multi-Purpose SATllite-3A) satellite images show that this change detection method can effectively extract changed/unchanged pixels but is less sensitive to changes due to shadow and relief displacements. In addition, the change detection accuracy of two sites was improved by using 3D kernels. This is because a 3D kernel can consider not only the spatial information but also the spectral information. This study indicates that we can effectively detect changes in high-resolution satellite images using the constructed image information and deep learning network. In future work, a pre-trained change detection network will be applied to newly obtained images to extend the scope of the application.

A Long-term Variability of the Extent of East Asian Desert (동아시아 사막 면적의 경년변화분석)

  • Han, Hyeon-Gyeong;Lee, Eunkyung;Son, Sanghun;Choi, Sungwon;Lee, Kyeong-Sang;Seo, Minji;Jin, Donghyun;Kim, Honghee;Kwon, Chaeyoung;Lee, Darae;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.869-877
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    • 2018
  • The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.

Estimation for Ground Air Temperature Using GEO-KOMPSAT-2A and Deep Neural Network (심층신경망과 천리안위성 2A호를 활용한 지상기온 추정에 관한 연구)

  • Taeyoon Eom;Kwangnyun Kim;Yonghan Jo;Keunyong Song;Yunjeong Lee;Yun Gon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.207-221
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    • 2023
  • This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

Evaluation of the Utilization Potential of High-Resolution Optical Satellite Images in Port Ship Management: A Case Study on Berth Utilization in Busan New Port (고해상도 광학 위성영상의 항만선박관리 활용 가능성 평가: 부산 신항의 선석 활용을 대상으로)

  • Hyunsoo Kim ;Soyeong Jang ;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1173-1183
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    • 2023
  • Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.

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.

Development of Cloud Detection Method Considering Radiometric Characteristics of Satellite Imagery (위성영상의 방사적 특성을 고려한 구름 탐지 방법 개발)

  • Won-Woo Seo;Hongki Kang;Wansang Yoon;Pyung-Chae Lim;Sooahm Rhee;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1211-1224
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    • 2023
  • Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

A Study on Sea Surface Temperature Changes in South Sea (Tongyeong coast), South Korea, Following the Passage of Typhoon KHANUN in 2023 (2023년 태풍 카눈 통과에 따른 한국 남해 통영해역 수온 변동 연구)

  • Jae-Dong Hwang;Ji-Suk Ahn;Ju-Yeon Kim;Hui-Tae Joo;Byung-Hwa Min;Ki-Ho Nam;Si-Woo Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.30 no.1
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    • pp.13-19
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    • 2024
  • An analysis of the coastal water temperature in the Tongyeong waters, the eastern sea of the South Sea of Korea, revealed that the water temperature rose sharply before the typhoon made landfall. The water temperature rise occurred throughout the entire water column. An analysis of the sea surface temperature data observed by NOAA(National Oceanic and Atmospheric Administration) satellites, indicated that sea water with a temperature of 30℃ existed in the eastern waters of the eastern South Sea of Korea before the typhoon landed. The southeastern sea of Korea is an area where ocean currents prevail from west to east owing to the Tsushima Warm Current. However, an analysis of the satellite data showed that seawater at 30℃ moved from east to west, indicating that it was affected by the Ekman transport caused by the typhoon before landing. In addition, because the eastern waters of the South Sea are not as deep as those of the East Sea, the water temperature of the entire water layer may remain constant owing to vertical mixing caused by the wind. Because the rise in water temperature in each water layer occurred on the same day, the rise in the bottom water temperature can be considered as owing to vertical mixing. Indeed, the southeastern sea of Korea is a sea area where the water temperature can rise rapidly depending on the direction of approach of the typhoon and the location of high temperature formation.

PRC Maritime Operational Capability and the Task for the ROK Military (중국군의 해양작전능력과 한국군의 과제)

  • Kim, Min-Seok
    • Strategy21
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    • s.33
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    • pp.65-112
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    • 2014
  • Recent trends show that the PRC has stepped aside its "army-centered approach" and placed greater emphasis on its Navy and Air Force for a wider range of operations, thereby reducing its ground force and harnessing its economic power and military technology into naval development. A quantitative growth of the PLA Navy itself is no surprise as this is not a recent phenomenon. Now is the time to pay closer attention to the level of PRC naval force's performance and the extent of its warfighting capacity in the maritime domain. It is also worth asking what China can do with its widening naval power foundation. In short, it is time to delve into several possible scenarios I which the PRC poses a real threat. With this in mind, in Section Two the paper seeks to observe the construction progress of PRC's naval power and its future prospects up to the year 2020, and categorize time frame according to its major force improvement trends. By analyzing qualitative improvements made over time, such as the scale of investment and the number of ships compared to increase in displacement (tonnage), this paper attempts to identify salient features in the construction of naval power. Chapter Three sets out performance evaluation on each type of PRC naval ships as well as capabilities of the Navy, Air Force, the Second Artillery (i.e., strategic missile forces) and satellites that could support maritime warfare. Finall, the concluding chapter estimates the PRC's maritime warfighting capability as anticipated in respective conflict scenarios, and considers its impact on the Korean Peninsula and proposes the directions ROK should steer in response. First of all, since the 1980s the PRC navy has undergone transitions as the focus of its military strategic outlook shifted from ground warfare to maritime warfare, and within 30 years of its effort to construct naval power while greatly reducing the size of its ground forces, the PRC has succeeded in building its naval power next to the U.S.'s in the world in terms of number, with acquisition of an aircraft carrier, Chinese-version of the Aegis, submarines and so on. The PRC also enjoys great potentials to qualitatively develop its forces such as indigenous aircraft carriers, next-generation strategic submarines, next-generation destroyers and so forth, which is possible because the PRC has accumulated its independent production capabilities in the process of its 30-year-long efforts. Secondly, one could argue that ROK still has its chances of coping with the PRC in naval power since, despite its continuous efforts, many estimate that the PRC naval force is roughly ten or more years behind that of superpowers such as the U.S., on areas including radar detection capability, EW capability, C4I and data-link systems, doctrines on force employment as well as tactics, and such gap cannot be easily overcome. The most probable scenarios involving the PRC in sea areas surrounding the Korean Peninsula are: first, upon the outbreak of war in the peninsula, the PRC may pursue military intervention through sea, thereby undermining efforts of the ROK-U.S. combined operations; second, ROK-PRC or PRC-Japan conflicts over maritime jurisdiction or ownership over the Senkaku/Diaoyu islands could inflict damage to ROK territorial sovereignty or economic gains. The PRC would likely attempt to resolve the conflict employing blitzkrieg tactics before U.S. forces arrive on the scene, while at the same time delaying and denying access of the incoming U.S. forces. If this proves unattainable, the PRC could take a course of action adopting "long-term attrition warfare," thus weakening its enemy's sustainability. All in all, thiss paper makes three proposals on how the ROK should respond. First, modern warfare as well as the emergent future warfare demonstrates that the center stage of battle is no longer the domestic territory, but rather further away into the sea and space. In this respect, the ROKN should take advantage of the distinct feature of battle space on the peninsula, which is surrounded by the seas, and obtain capabilities to intercept more than 50 percent of the enemy's ballistic missiles, including those of North Korea. In tandem with this capacity, employment of a large scale of UAV/F Carrier for Kill Chain operations should enhance effectiveness. This is because conditions are more favorable to defend from sea, on matters concerning accuracy rates against enemy targets, minimized threat of friendly damage, and cost effectiveness. Second, to maintain readiness for a North Korean crisis where timely deployment of US forces is not possible, the ROKN ought to obtain capabilities to hold the enemy attack at bay while deterring PRC naval intervention. It is also argued that ROKN should strengthen its power so as to protect national interests in the seas surrounding the peninsula without support from the USN, should ROK-PRC or ROK-Japan conflict arise concerning maritime jurisprudence. Third, the ROK should fortify infrastructures for independent construction of naval power and expand its R&D efforts, and for this purpose, the ROK should make the most of the advantages stemming from the ROK-U.S. alliance inducing active support from the United States. The rationale behind this argument is that while it is strategically effective to rely on alliance or jump on the bandwagon, the ultimate goal is always to acquire an independent response capability as much as possible.

Intercomparing the Aerosol Optical Depth Using the Geostationary Satellite Sensors (AHI, GOCI and MI) from Yonsei AErosol Retrieval (YAER) Algorithm (연세에어로졸 알고리즘을 이용하여 정지궤도위성 센서(AHI, GOCI, MI)로부터 산출된 에어로졸 광학두께 비교 연구)

  • Lim, Hyunkwang;Choi, Myungje;Kim, Mijin;Kim, Jhoon;Go, Sujung;Lee, Seoyoung
    • Journal of the Korean earth science society
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    • v.39 no.2
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    • pp.119-130
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    • 2018
  • Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.