Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.
Kim, Ah-Leum;Song, Jung-Hwan;Kang, Seo-Li;Lee, Woo-Kyung
Korean Journal of Remote Sensing
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v.30
no.4
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pp.431-444
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2014
As applications of spaceborne SAR imagery are extended, there are increased demands for accurate registrations for better understanding and fusion of radar images. It becomes common to adopt multi-resolution SAR images to apply for wide area reconnaissance. Geometric correction of the SAR images can be performed by using satellite orbit and attitude information. However, the inherent errors of the SAR sensor's attitude and ground geographical data tend to cause geometric errors in the produced SAR image. These errors should be corrected when the SAR images are applied for multi-temporal analysis, change detection applications and image fusion with other sensor images. The undesirable ground registration errors can be corrected with respect to the true ground control points in order to produce complete SAR products. Speeded Up Robust Feature (SURF) technique is an efficient algorithm to extract ground control points from images but is considered to be inappropriate to apply to SAR images due to high speckle noises. In this paper, an attempt is made to apply SURF algorithm to SAR images for image registration and fusion. Matched points are extracted with respect to the varying parameters of Hessian and SURF matching thresholds, and the performance is analyzed by measuring the imaging matching accuracies. A number of performance measures concerning image registration are suggested to validate the use of SURF for spaceborne SAR images. Various simulations methodologies are suggested the validate the use of SURF for the geometric correction and image registrations and it is shown that a good choice of input parameters to the SURF algorithm should be made to apply for the spaceborne SAR images of moderate resolutions.
The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.
Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.
Woojin, Jeon;Donghyun, Jin;Noh-hun, Seong;Daeseong, Jung;Suyoung, Sim;Jongho, Woo;Yugyeong, Byeon;Nayeon, Kim;Kyung-Soo, Han
Korean Journal of Remote Sensing
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v.39
no.1
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pp.77-86
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2023
Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.
Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.
Journal of the Korean Association of Geographic Information Studies
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v.9
no.4
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pp.12-21
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2006
Recently, Very large and high resolution geological data from aerial or satellite imagery are available. Many researches and applications require to do realtime visualization of interest geological area or entire planet. Important operation of wide-spreaded terrain realtime visualization technique is the appropriate model resolution selection from pre-processed multi-resolution model hierarchy depend upon participant's view. For embodying such realtime rendering system with large geometric data, Preprocessing multi-resolution hierarchy from large scale geological information of interest area is required. In this research, recent Cubic multiresolution 4-8 tile hierarchy is selected for global planetary applications. Based upon the tile hierarchy, It constructs the selective terminal level tile mesh for original geological information area and starts to sample individual generated tiles for terminal level tiles. It completes the hierarchy by constructing intermediate tiles with low pass filtering in bottom-up direction. This research embodies series of efficient cubic 4-8 tile hierarchy construction mechanism with out-of-core storage. The planetary scale Mars' geographical altitude data and image data were selected for the experiment.
Land Remote Sensing' is defined as the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. Narrowly speaking, this is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information. Remote sensing technology was initially developed with certain purposes in mind ie. military and environmental observation. However, after 1970s, as these high-technologies were taught to private industries, remote sensing began to be more commercialized. Recently, we are witnessing a 0.61-meter high-resolution satellite image on a free market. While privatization of land remote sensing has enabled one to use this information for disaster prevention, map creation, resource exploration and more, it can also create serious threat to a sensed nation's national security, if such high resolution images fall into a hostile group ie. terrorists. The United States, a leading nation for land remote sensing technology, has been preparing and developing legislative control measures against the remote sensing industry, and has successfully created various policies to do so. Through the National Oceanic and Atmospheric Administration's authority under the Land Remote Sensing Policy Act, the US can restrict sensing and recording of resolution of 0.5 meter or better, and prohibit distributing/circulating any images for the first 24 hours. In 1994, Presidential Decision Directive 23 ordered a 'Shutter Control' policy that details heightened level of restriction from sensing to commercializing such sensitive data. The Directive 23 was even more strengthened in 2003 when the Congress passed US Commercial Remote Sensing Policy. These policies allow Secretary of Defense and Secretary of State to set up guidelines in authorizing land remote sensing, and to limit sensing and distributing satellite images in the name of the national security - US government can use the civilian remote sensing systems when needed for the national security purpose. The fact that the world's leading aerospace technology country acknowledged the magnitude of land remote sensing in the context of national security, and it has made and is making much effort to create necessary legislative measures to control the powerful technology gives much suggestions to our divided Korean peninsula. We, too, must continue working on the Korea National Space Development Act and laws to develop the necessary policies to ensure not only the development of space industry, but also to ensure the national security.
Han, Daehyeon;Kim, Young Jun;Jung, Sihun;Sim, Seongmun;Kim, Woohyeok;Jang, Eunna;Im, Jungho;Kim, Hyun-Cheol
Korean Journal of Remote Sensing
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v.37
no.5_1
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pp.1177-1186
/
2021
As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.31
no.6_1
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pp.503-509
/
2013
The KOMPSAT-3 (Korea Multi-Purpose Satellite-3), was launched on May 18, 2012, is an optical high-resolution observation mission of the Korea Aerospace Research Institute and provides RPC(Rational Polynomial Coefficient) for ground coordinate determination. It is however need to adjust because RPC absorbs effects of interior-exterior orientation errors. In this study, to obtain the suitable adjustment parameters of the vendor-provided RPC of the KOMPSAT-3 images, six types of adjustment models were implemented. As results, the errors of two and six adjustment parameters differed approximately 0.1m. We thus propose the two parameters model, the number of control points are required the least, to adjust the KOMPSAT-3 R PC. According to the increasing the number of control points, RPC adjustment was performed. The proposed model with a control point particularly did not exceed a maximum error 3m. As demonstrated in this paper, the two parameters model can be applied in RPC adjustment of KOMPSAT-3 stereo image.
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