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Relevant bibliographies by topics / Ocean synoptic feature extraction

Academic literature on the topic 'Ocean synoptic feature extraction'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Ocean synoptic feature extraction"

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Chen, Xi, Shaojie Sun, Jun Zhao, and Bin Ai. "Spectral Discrimination of Pumice Rafts in Optical MSI Imagery." Remote Sensing 14, no. 22 (November 18, 2022): 5854. http://dx.doi.org/10.3390/rs14225854.

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Pumice rafts are considered to be a long-range drifting agent that promotes material exchange and the dispersal of marine species. Large ones can also interfere with vessel navigation and have a negative impact on the social economy and marine ecosystems. Synoptic observations from the Multispectral Instrument (MSI) on-board Sentinel-2, with a spatial resolution of up to 10 m, provide an excellent means to monitor and track pumice rafts. In this study, the use of a Spectral-Feature-Based Extraction (SFBE) algorithm to automatically discriminate and extract pumice on the ocean surface from submarine volcano eruptions was proposed. Specifically, a Pumice Raft Index (PRI) was developed based on the spectral signatures of pumice in MSI imagery to identify potential pumice features. After pre-processing, the PRI image was then subjected to a series of per-pixel and object-based processes to rule out false-positive detections, including shallow water, striped edges, mudflats, and cloud edges. The SFBE algorithm showed excellent performance in extracting pumice rafts and was successfully applied to extract pumice rafts near the Fiji Yasawa islands in 2019 and Hunga Tonga island in 2022, with an overall pumice extraction accuracy of 95.5% and a proportion of pixels mis-extracted as pumice of <3%. The robustness of the algorithm has also been tested and proved through applying it to data and comparing its output to results from previous studies. The timely and accurate detection of pumice using the algorithm proposed here is expected to provide important information to aid in response actions and ecological assessments, and will lead to a better understanding of the fate of pumice.

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Shaji, C., and A. Gangopadhyay. "Synoptic Modeling in the Eastern Arabian Sea during the Southwest Monsoon Using Upwelling Feature Models." Journal of Atmospheric and Oceanic Technology 24, no. 5 (May 1, 2007): 877–93. http://dx.doi.org/10.1175/jtech1984.1.

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Abstract Hydrographic observations along the western coast of India during the southwest (SW) monsoon season reveal upwelling in the equatorward surface flow and downwelling below the thermocline with a weak poleward undercurrent. Observations made previously during the peak of the SW monsoon in boreal summer showed that upwelling temperatures are much cooler (<23°C) than compared to the available climatology data in this region. A feature modeling technique is used to describe the temperature distribution associated with the West India Coastal Current (WICC) upwelling. This kind of formulation captures the upwelling and downwelling associated with the WICC reasonably well, though it requires the specification of a few observed offshore and nearshore temperature profiles. The temperature–salinity relationship from the Levitus climatology data is further used to obtain a compatible salinity distribution for the feature model. The efficiency of this feature model is further validated via a dynamical model simulation: here, the temperature–salinity feature model profiles are objectively melded with the Levitus climatology to create the synoptic initial condition. The WICC’s local circulation and simulated upwelling temperatures are more realistic in the dynamical model simulation with the feature model than in a simulation that does not utilize the upwelling feature model. The advantage of the feature modeling technique used herein is that it provides additional or new information that the OGCMs or prognostic ocean models can adapt to improve the latter’s initial condition and for synoptic forecasting. Furthermore, the generalized formulation of the upwelling feature model developed here may be used in other regional coastal oceans as well.

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Ma, Hualin, and Liyan Zhang. "Ocean SAR Image Segmentation and Edge Gradient Feature Extraction." Journal of Coastal Research 94, sp1 (September 9, 2019): 141. http://dx.doi.org/10.2112/si94-028.1.

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Wang, Xiong Liang, and Chun Ling Wang. "Extraction of Ocean Fronts Based on Empirical Mode Decomposition." Applied Mechanics and Materials 701-702 (December 2014): 303–7. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.303.

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Ocean front is a narrow transitional zone that the penetration of sea is obviously different between two or more waters there. It is an important feature of geophysical turbulence which plays an important role in ocean dynamics. Ocean fronts become visible on radar images because they are associated with a variable surface current which modulates the sea surface roughness and thus the backscattered radar power. This paper propose a new integrated method to extract ocean fronts based on two-dimensional Empirical Mode Decomposition (EMD), image edge detection and mathematical morphology processing. Experimental results show that this integrated method can be effective in ocean front feature extraction.

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Ibebuchi, Chibuike Chiedozie, and Itohan-Osa Abu. "Relationship between synoptic circulations and the spatial distributions of rainfall in Zimbabwe." AIMS Geosciences 9, no. 1 (2022): 1–15. http://dx.doi.org/10.3934/geosci.2023001.

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<abstract> <p>This study examines how the atmospheric circulation patterns in Africa south of the equator govern the spatial distribution of precipitation in Zimbabwe. The moisture circulation patterns are designated by an ample set of eight classified circulation types (CTs). Here it is shown that all wet CTs over Zimbabwe features enhanced cyclonic/convective activity in the southwest Indian Ocean. Therefore, enhanced moisture availability in the southwest Indian Ocean is necessary for rainfall formation in parts of Zimbabwe. The wettest CT in Zimbabwe is characterized by a ridging South Atlantic Ocean high-pressure, south of South Africa, driving an abundance of southeast moisture fluxes, from the southwest Indian Ocean into Zimbabwe. Due to the proximity of Zimbabwe to the Agulhas and Mozambique warm current, the activity of the ridging South Atlantic Ocean anticyclone is a dominant synoptic feature that favors above-average rainfall in Zimbabwe. Also, coupled with a weaker state of the Mascarene high, it is shown that a ridging South Atlantic Ocean high-pressure, south of South Africa, can be favorable for the southwest movement of tropical cyclones into the eastern coastal landmasses resulting in above-average rainfall in Zimbabwe. The driest CT is characterized by the northward track of the Southern Hemisphere mid-latitude cyclones leading to enhanced westerly fluxes in the southwest Indian Ocean, limiting moist southeast winds into Zimbabwe.</p> </abstract>

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Dai, Panxi, and Ji Nie. "A Global Quasigeostrophic Diagnosis of Extratropical Extreme Precipitation." Journal of Climate 33, no. 22 (November 15, 2020): 9629–42. http://dx.doi.org/10.1175/jcli-d-20-0146.1.

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AbstractThis paper presents a global picture of the dynamic processes and synoptic characteristics of extratropical extreme precipitation events (EPEs), defined as annual maximum daily precipitation averaged over 7.5° × 7.5° regional boxes. Based on the quasigeostrophic omega equation, extreme precipitation can be decomposed into components forced by large-scale adiabatic disturbances and amplified by diabatic heating feedback. The spatial distribution of the diabatic feedback parameter is largely controlled by atmospheric precipitable water and captured by a simple model. Most spatial heterogeneities of EPEs in the middle and high latitudes are due to the spatial variations of large-scale adiabatic forcing. The adiabatic component includes the processes of vorticity advection, in which the synoptic vorticity advection by background wind dominates; temperature advection, in which the total meridional temperature advection by synoptic wind dominates; and boundary forcing. The synoptic patterns of EPEs in all extratropical regions can be classified into six clusters using the self-organizing map method: two clusters in low latitudes and four clusters in middle and high latitudes. Synoptic disturbances are characterized by strong pressure anomalies throughout the troposphere over the coastal regions and oceans and feature upper-level shortwave disturbances and a large westward tilt with height over land. Synoptic configurations favor moisture transport from ocean to land over coastal regions.

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Jinkerson, Richard A., Stephen L. Abrams, Leonidas Bardis, Chryssostomos Chryssostomidis, Andre Cldment, Nicholas M. Patrikalakis, and Franz-Erich Wolter. "Inspection and Feature Extraction of Marine Propellers." Journal of Ship Production 9, no. 02 (May 1, 1993): 88–106. http://dx.doi.org/10.5957/jsp.1993.9.2.88.

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Localization is the process of determining the rigid-body translations and rotations that must be performed on the set of points measured on a manufactured surface to move those points into closest correspondence with the ideal design surface. In unconstrained localization all points have equal effect on the determination of the rigid-body transformation, while constrained localization allows a subset of the points to have stronger influence on the transformation. The measured points are physical points in space obtained by direct measurement of a manufactured marine propeller blade. The ideal design surface is the surface description of the propeller blade provided by the blade designer. Given that the measured blade is manufactured from the design surface description, the localization determines a Euclidean motion that brings the measured points of the manufactured surface as close as possible to the design surface. An additional option is to determine an offset distance, such that the Euclidean motion brings the measured points as close as possible to the offset of the design surface. For this optimization problem the offset distance is a seventh parameter that must be determined in addition to the six parameters of the Euclidean motion. After localization, the offset of the design surface that was determined can be used to extract the gross geometric features of the manufactured blade. These features have important hydrodynamic functions and include the camber surface, section thickness function, pitch, rake, skew, chord length, maximum thickness, maximum camber, and the leading-edge curve. The approximation of the camber surface, which is the basis of most of the remaining features, is an intricate problem relying on an extension of the concept of a Brooks ribbon. It requires the solution of a system of nonlinear differential equations and a complicated error evaluation scheme.

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Spensberger, Clemens, and Thomas Spengler. "Feature-Based Jet Variability in the Upper Troposphere." Journal of Climate 33, no. 16 (August 15, 2020): 6849–71. http://dx.doi.org/10.1175/jcli-d-19-0715.1.

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AbstractJets in the upper troposphere constitute a cornerstone of both synoptic meteorology and climate dynamics, providing a direct link between weather and midlatitude climate variability. Conventionally, jet variability is often inferred indirectly through the variability of geopotential or sea level pressure. As recent findings pointed to physical discrepancies of this interpretation for the Southern Hemisphere, this study presents a global overview of jet variability based on automated jet detections in the upper troposphere. Consistent with previous studies, most ocean basins are dominated by variability patterns comprising either a latitudinal shift of the jet or a so-called pulsing, a broadening/narrowing of the jet distribution without a change in the mean position. Whereas previous studies generally associate a mode of storm track variability with either shifting or pulsing, jet-based variability patterns frequently represent a transition from shifting to pulsing, or vice versa, across the respective ocean basin. In the Northern Hemisphere, jet variability is consistent with geopotential variability, confirming earlier analyses. In the Southern Hemisphere, however, the variability of geopotential and jets often indicates different modes of variability. Notable exceptions are the consistent dominant modes of jet and geopotential variability in the South Pacific and, to a lesser extent, the south Indian Ocean during winter, as well as the dominant modes in the South Atlantic and south Indian Ocean during summer. Finally, tropical variability is shown to modulate the jet distribution in the Northern Hemisphere, which is in line with previous results. The response in the Southern Hemispheric, however, is shown to be markedly different.

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MATSUOKA, Daisuke, Fumiaki ARAKI, Shinichiro KIDA, Hideharu SASAKI, and Bunmei TAGUCHI. "J013024 Feature Extraction and Visualization of Ocean Currents via Cluster Analysis." Proceedings of Mechanical Engineering Congress, Japan 2013 (2013): _J013024–1—_J013024–3. http://dx.doi.org/10.1299/jsmemecj.2013._j013024-1.

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González-Alemán, Juan J., Francisco Valero, Francisco Martín-León, and Jenni L. Evans. "Classification and Synoptic Analysis of Subtropical Cyclones within the Northeastern Atlantic Ocean*." Journal of Climate 28, no. 8 (April 7, 2015): 3331–52. http://dx.doi.org/10.1175/jcli-d-14-00276.1.

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Abstract Since more research is needed on subtropical cyclones (STCs) formed within the North Atlantic eastern basin, this survey analyzes them from a synoptic point of view, on a climatological basis, with the main aims of studying their common features, complementing other studies of these storms in the North Atlantic, and aiding the forecasting community. Fifteen cases of STCs were identified during the period 1979–2011 by applying a set of criteria from two databases. Composite analysis reveals that an extratropical depression acts as a precursor when it is isolated from the westerlies and then suffers a deepening when becoming subtropical instead of decaying through occlusion. This process is accompanied by an atmospheric circulation, within the North Atlantic, whose main feature is characterized by notable departures from the climatological pattern with a statistically significant anomalous high pressure to the north of the STCs. Three conceptual models of synoptic pattern of subtropical cyclogenesis are derived and show that these departures appeared because the westerly circulation moves poleward and/or the flow has a great meridional component, with the possibility of a blocked flow pattern occurring. Moreover, the identified STCs predominantly formed in a highly sheared (>10 m s−1) environment with low sea surface temperature values (<25°C), which differs from the dominant features of STCs in the North Atlantic, especially within its western region. Finally, a recent (2010) STC, identified by the authors, is synoptically discussed in order to achieve a better interpretation of the general results.

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Dissertations / Theses on the topic "Ocean synoptic feature extraction"

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Jastram, Michael Oliver. "Inspection and feature extraction of marine propellers." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/42632.

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Guo, Da 1976. "Automated feature extraction in oceanographic visualization." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/33438.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaves 141-147).
The ocean is characterized by a multitude of powerful, sporadic biophysical dynamical events; scientific research has reached the stage that their interpretation and prediction is now becoming possible. Ocean prediction, analogous to atmospheric weather prediction but combining biological, chemical and physical features is able to help us understand the complex coupled physics, biology and acoustics of the ocean. Applications of the prediction of the ocean environment include exploitation and management of marine resources, pollution control such as planning of maritime and naval operations. Given the vastness of ocean, it is essential for effective ocean prediction to employ adaptive sampling to best utilize the available sensor resources in order to minimize the forecast error. It is important to concentrate measurements to the regions where one can witness features of physical or biological significance in progress. Thus automated feature extraction in oceanographic visualization can facilitate adaptive sampling by presenting the physically relevant features directly to the operation planners. Moreover it could be used to help automate adaptive sampling. Vortices (eddies and gyres) and upwelling, two typical and important features of the ocean, are studied.
(cont.) A variety of feature extraction methods are presented, and those more pertinent to this study are implemented, including derived field generation and attribute set extraction. Detection results are evaluated in terms of accuracy, computational efficiency, clarity and usability. Vortices, a very important flow feature is the primary focus of this study. Several point-based and set-based vortex detection methods are reviewed. A set-based vortex core detection method based on geometric properties of vortices is applied to both classical vortex models and real ocean models. The direction spanning property, which is a geometric property, guides the detection of all the vortex core candidates, and the conjugate pair eigenvalue method is responsible for filtering out the false positives from the candidate set. Results show the new method to be analytically accurate and practically feasible, and superior to traditional point-based vortex detection methods. Detection methods of streamlines are also discussed. Using the novel cross method or the winding angle method, closed streamlines around vortex cores can be detected.
(cont.) Therefore, the whole vortex area, i.e., the combination of vortex core and surrounding streamlines, is detected. Accuracy and feasibility are achieved through automated vortex detection requiring no human inspection. The detection of another ocean feature, upwelling, is also discussed.
by Da Guo.
S.M.

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Lambhate, Devyani. "Deep Convolutional and Generative Networks for Ocean Synoptic Feature Extraction and Super Resolution from Remotely Sensed Images." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5683.

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Accurate extraction of Synoptic Ocean Features and Downscaling of Ocean Features is crucial for climate studies and the operational forecasting of ocean systems. With the advancement of space and sensor technologies, the amount of remote-sensing ocean data is rising sharply. There is a need for precise and reliable algorithms to extract information from such remotely sensed datasets. Deep learning algorithms have shown significant superiority over traditional physical or statistical methods for several remote-sensing applications. Two important applications are ocean synoptic feature extraction (needed to extract useful information submerged in data) and downscaling of satellite images (needed due to insufficient resolution of current imaging sensors). This thesis introduces two novel deep learning algorithms: W-Net (for Ocean Feature Extraction) and PF-GAN-SR (for Downscaling of Sea Surface Temperature Satellite Images). Ocean Synoptic Feature Extraction: For operational regional models of the North Atlantic, skilled human operators visualize and extract the Gulf Stream and Rings (Warm and Cold Eddies) through a time-consuming manual process. There is a need for an automated dynamics-inspired system to extract Gulf Stream and Rings. We have developed a deep learning system (W-Net) that extracts the Gulf Stream and Rings from concurrent satellite images of sea surface temperature (SST) and sea surface height (SSH). Our approach's novelty is that the above extraction task is posed as a multi-label semantic image segmentation problem solved by developing and applying a deep convolutional neural network with two parallel Encoder-Decoder networks (one branch for SST and the other for SSH), implemented as a WNet. W-Net is the first neural architecture and deep learning system developed for automated synoptic ocean feature segmentation. For the Gulf Stream, we obtain 82.7% raw test accuracy and a low error of 4.39% in the detected path length. For the Rings, we obtain more than 71% raw eddy detection accuracy. Downscaling of Sea Surface Temperature Satellite Images: The unavailability of high-resolution remotely sensed images affects the quality of ocean forecasting and ocean feature extraction. Typical downscaling for geophysical applications is achieved using bi-linear/ bicubic interpolation, which is not good for large downscaling ratios. To improve the current state of the art, we developed a Bayesian algorithm for Super-Resolution (Downscaling) of lower resolution geophysical fields observed by satellites. The key novelty is the development and use of Generative Adversarial Networks (GAN) to learn the prior probability distribution of the high-resolution geophysical fields from historical data and/or model forecasts. The trained GAN is used to sample from the high-resolution prior and a Particle Filter along with the low resolution data (observation) is used to obtain the posterior high-resolution geophysical field. The resultant algorithm has been named the Particle Filter Generative Adversarial Network super-resolution (PF-GAN-SR) algorithm. PF-GAN-SR is applied to downscale sea surface temperature fields in the northwest Atlantic Ocean. Results show consistent performance across different downscaling ratios. Notably, the high-resolution fields obtained from PF-GAN-SR have a better similarity score with the true high-resolution field as compared to existing Super- Resolution methods.

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Tai, Chih-Chiang, and 戴志強. "A Study of Linear Feature Extraction on Ocean Surface Satellite Image Using Spatial Information Techniques." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/07554551120967948695.

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碩士
義守大學
資訊管理學系碩士班
95
Modern techniques of satellite image acquisition have been of great advance lately, which provide a great amount of images with a higher resolution both in spatial and spectral resolution. However, the rate of utilizing the existed images has not yet been sufficient in comparison to the rate of obtaining them. Hence, issues in using automated method of linear feature extraction for replacing manual process have drawn a great deal of attentions in this area lately. The purpose of this study is to develop an integrated method for extracting linear features of oceanic internal waves from satellite imagery using spatial information techniques, which include: wavelet transform based de-noise, Multiscale Retinex (MSR), and linear feature extraction (LEF). To evaluate the performance of the integrated method, the extracted linear features will be vectorized and overlapped with the original image in the Geographic Information System (GIS) to investigate the position discrepancy between them and the true features’ boundary. The results show that the MSR method provides enhanced image with improved color contrast and brightness, which result in a better quality of extracted linear features. Finally, we evaluate the performance of feature extraction using both the Canny method and the Wavelet Transform Modulus Maxima (WTMM) method. It is shown that the Canny method is superior to the WTMM method in terms of visualization quality and positioning accuracy.

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Book chapters on the topic "Ocean synoptic feature extraction"

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Huynh, Quyen, Walter Greene, and John Impagliazzo. "Feature Extraction and Classification of Underwater Acoustic Signals." In Full Field Inversion Methods in Ocean and Seismo-Acoustics, 183–88. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8476-0_30.

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Conference papers on the topic "Ocean synoptic feature extraction"

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Shi, Hai-Quan, Jing-He Chen, and Li-Tao Yang. "Feature Vector Generation of Underwater Acoustic Signal based on Multi-Domain Feature Extraction." In 2021 OES China Ocean Acoustics (COA). IEEE, 2021. http://dx.doi.org/10.1109/coa50123.2021.9519920.

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Gui, Feng, and QiWei Lin. "Morphological theory in image feature extraction." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Stephen G. Ungar, Shiyi Mao, and Yoshifumi Yasuoka. SPIE, 2003. http://dx.doi.org/10.1117/12.468079.

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Wang, Wenbo, Sichun Li, Jianshe Yang, Zhao Liu, and Weicun Zhou. "Feature extraction of underwater target in auditory sensation area based on MFCC." In 2016 IEEE/OES China Ocean Acoustics (COA). IEEE, 2016. http://dx.doi.org/10.1109/coa.2016.7535736.

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Xiangdong Jiang. "Noise detection and feature extraction method for underwater vehicle engine speedup radiated noise." In 2016 IEEE/OES China Ocean Acoustics (COA). IEEE, 2016. http://dx.doi.org/10.1109/coa.2016.7535629.

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Mu, Lin, Yuan Peng, Mengran Qiu, Xuemeng Yang, Chen Hu, and Fengzhen Zhang. "Study on modulation spectrum feature extraction of ship radiated noise based on auditory model." In 2016 IEEE/OES China Ocean Acoustics (COA). IEEE, 2016. http://dx.doi.org/10.1109/coa.2016.7535765.

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Zhao, Peng, Xun Yang, Yan Chen, Ling Tong, and Lei He. "Feature extraction and classification of ocean oil spill based on SAR image." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729380.

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Huan Wang and Junhui Deng. "Feature extraction of complex ocean flow field using the helmholtz-hodge decomposition." In 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW). IEEE, 2014. http://dx.doi.org/10.1109/icmew.2014.6890546.

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Ren, Huimin, Fangfang Li, Bing Han, Wen Hong, Yingbo Dong, and Bitong Wu. "Ocean Oil Spill Classification with Polarimetric SAR Based on VGG16 Multi-Feature Extraction." In 2021 SAR in Big Data Era (BIGSARDATA). IEEE, 2021. http://dx.doi.org/10.1109/bigsardata53212.2021.9574126.

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Bostater, Charles R., and Teddy Ghir. "Coastal water feature extraction using airborne hyperspectral imagery in shallow estuarine water." In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2023, edited by Charles R. Bostater and Xavier Neyt. SPIE, 2023. http://dx.doi.org/10.1117/12.2680314.

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Zhang Bentao, Chen Biao, and Gao Guoxing. "Research on the spaceborne SAR image processing and feature extraction for ocean fronts detection." In 2010 International Conference On Computer and Communication Technologies in Agriculture Engineering (CCTAE). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5544849.

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