Advanced Geoscience Remote Sensing

Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations

Internal Waves at the UK Continental Shelf: Automatic Mapping Using the ENVISAT ASAR Sensor

Oceanic internal waves occur within stratified water along the boundary between water layers of different density and are generated when strong tidal currents flow over seabed topography. Their amplitude can exceed 50 m and they transport energy over long distances and cause vertical mixing when the waves break. This study presents the first fully automated methodology for the mapping of internal waves using satellite synthetic aperture radar (SAR) data and applies this to explore their spatial and temporal distribution within UK shelf seas. The new algorithm includes enhanced edge detection and spatial processing to target the appearance of these features on satellite images. We acquired and processed over 7000 ENVISAT ASAR scenes covering the UK continental shelfbetween2006and2012,toautomaticallygeneratedetailedmapsofinternalwaves. Monthlyand annual internal wave climatology maps of the continental shelf were produced showing spatial and temporal variability, which can be used to predict where internal waves have the most impact on the seabed environment and ecology in UK shelf seas. These observations revealed correlations between thetemporalpatternsofinternalwavesand theseasonswhenthecontinentalshelfwatersweremore stratified. The maps were validated using well-known seabed topographic features. Concentrations of internal waves were automatically identified at Wyville-Thomson Ridge in June 2008, at the continental shelf break to the east of Rosemary Bank in January 2010 and in the Faroe-Shetland Channel in June 2011. This new automated methodology has been shown to be robust for mapping internalwavesusingalargeSARdatasetandisrecommendedforstudiesinotherregionsworldwide and for SAR data acquired by other sensors

SAR-Mode altimetry observations of internal solitary waves in the tropical ocean part 2: a method of detection

It is demonstrated that the synthetic aperture radar altimeter (SRAL) on board of the Sentinel-3A can detect short-period internal solitary waves (ISWs) with scales of the order of a kilometer. A variety of signatures owing to the surface manifestations of the ISWs are apparent in the SRAL Level-2 products over the ocean. These signatures are identified in several geophysical parameters, such as radar backscatter ( σ0 ) and sea level anomaly (SLA). Radar backscatter is the primary parameter in which ISWs can be identified owing to the measurable sea surface roughness perturbations in the along-track direction resulting from the sharpened SRAL footprint. The SRAL footprint is sufficiently small (300 m in the along-track direction) to capture radar power fluctuations over successive wave crests and troughs, which produce rough and slick surface patterns arrayed in parallel bands with scales of a few kilometers along-track. Furthermore, it was possible to calculate the mean square slope ( s2¯¯¯ ) for the dual-band (Ku and C bands) altimeter of Sentinel-3, which made the ISW signatures unambiguously identified because of the large s2¯¯¯ variations in exact synergy with ocean and land color instrument (OLCI) images. Hence, the detection method is validated in cloud-free sun glint OLCI images. It is shown that both σ0 and SLA yield realistic estimates for routine observation of ISWs with the SRAL. The detection method that is used relies on the parameter s2¯¯¯ which is calculated from σ0 . This is a significant improvement from previous observations recently reported for conventional pulse-limited altimeters (Jason-2). An algorithm is developed to be used in any ocean region. Wavelets were applied for a first analysis of the s2¯¯¯ variations because ISWs can be readily identified in high-frequency signals. Other geophysical parameters such as SLA were used to exclude phenomena that are unlikely to be ISWs

Oceanic Internal Waves and Internal Tides in the East Asian Marginal Seas

Oceanic internal waves (IWs) at frequencies from local inertial (e.g., near-inertial internal waves) to buoyancy frequencies (nonlinear internal waves or internal solitary waves), sometimes including diurnal and semidiurnal tidal frequencies, play an important role in redistributing heat, momentum, materials, and energy via turbulent mixing. IWs are found ubiquitously in many seas, including East Asian marginal seas (Indonesian Seas, South China Sea, East China Sea, Yellow Sea, and East Sea or Japan Sea), significantly affecting underwater acoustics, coastal and offshore engineering, submarine navigation, biological productivity, and the local and global climate. Despite decades of study on the IWs in some regions, our understanding of the IWs in the East Asian marginal seas is still in a primitive state and the mechanisms underlying every stage (generation, propagation, evolution, and dissipation) of IWs are not always clear. This Special Issue includes papers related to all fields of both low- and high-frequency IW studies in the specified region, including remote sensing, in situ observations, theories, and numerical models

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

On the determination of characteristics of the interior ocean dynamics from radar signatures of oceanic internal solitary waves

In this paper we discuss two different methods of inferring characteristics of the interior ocean dynamics from radar signatures of internal solitary waves visible on synthetic aperture radar (SAR) images. The first one consists in the recognition and the interpretation of sea surface patterns of internal solitary waves; the second one consists in the analysis of the modulation depth of the normalized radar backscattering cross section (NRCS) associated with internal solitary waves. For this purpose we consider a data set composed of SAR and in situ measurements carried out from 1991 to 1997 in the region of the Strait of Messina. The recognition and the interpretation of sea surface patterns of internal solitary waves in the Strait of Messina can be used to study characteristics of the density distribution in the area: The internal wave field varies with seasonal variations in the vertical density stratification and with remotely induced variations, i.e., variations induced by the larger-scale circulation, in the horizontal density distribution. In order to inquire into the possibility of inferring parameters of the interior ocean dynamics by analyzing the modulation of the NRCS associated with internal solitary waves, several numerical simulations are carried out using a radar imaging model. These simulations are performed by assuming different wind conditions and internal wave parameters. It is shown that an accurate knowledge of wind conditions is crucial for deriving internal wave parameters and hence parameters of the interior ocean dynamics from the modulation of measured NRCS associated with internal solitary waves

Anomaly detection in hyperspectral signatures using automated derivative spectroscopy methods

The goal of this research was to detect anomalies in remotely sensed Hyperspectral images using automated derivative based methods. A database of Hyperspectral signatures was used that had simulated additive Gaussian anomalies that modeled a weakly concentrated aerosol in several spectral bands. The automated pattern detection system was carried out in four steps. They were: (1) feature extraction, (2) feature reduction through linear discriminant analysis, (3) performance characterization through receiver operating characteristic curves, and (4) signature classification using nearest mean and maximum likelihood classifiers. The Hyperspectral database contained signatures with various anomaly concentrations ranging from weakly present to moderately present and also anomalies in various spectral reflective and absorptive bands. It was found that the automated derivative based detection system gave classification accuracies of 97 percent for a Gaussian anomaly of SNR -45 dB and 70 percent for Gaussian anomaly of SNR -85 dB. This demonstrates the applicability of using derivative analysis methods for pattern detection and classification with remotely sensed Hyperspectral images