This PDF file contains the front matter associated with SPIE Proceedings Volume 12263, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

In High-Frequency Surface Wave Radar applications (HFSWR), targets at close range are often masked by very strong sea clutter returns in the range-Doppler spectrum. The clutter is highly non-homogeneous in the Doppler dimension, presenting two peaks at resonance Doppler frequencies, referred to as Bragg lines, and several smaller side peaks. Due to this complex scattering mechanism, a Gaussian assumption for clutter returns does not hold, and several works propose modeling sea clutter returns in HF range-Doppler spectra as a Weibull distribution. This work presents an analysis of the performance of a cell-averaging constant false alarm rate (CA-CFAR) algorithm designed for Weibull-distributed clutter. A closed-form probability of detection of the Weibull CACFAR is compared to a numerical simulation of sea clutter based on a physical model of sea radar cross-section (RCS). The clutter model takes into consideration wind conditions, as well as the operating parameters of the radar. It is demonstrated through numerical simulation of the physical model that the clutter echo distribution, depending on the sampling position in the range-Doppler spectrum and proximity to a Bragg line, can take the form of an exponential or a Rayleigh distribution. Thus, the overall distribution of clutter returns can be represented by a Weibull model. Results indicate that the closed-form analytical expression act as an upper bound for detector performance, that is, in practice, degraded by the strong peaks of the clutter power.

This paper reports the recent progress of sea-level rise (SLR) over the critical region of Southeast Asia (SEA) that is vulnerable to climate change. While many papers report the SLR on local scales (e.g., Malaysia, Indonesia, Vietnam, etc.), studies on understanding the SEA regional impact of SLR have yet to be reported, which has become the motivation of this paper. A literature review has been adopted to formulate the recent progress of SLR in the studied region. Besides global factors, we identified five (5) local factor drivers contributing to the SLR over SEA: 1) El-Nino and La-Nina, 2) seasonal monsoon, 3) wind-driven circulation variability/North Pacific Decadal Oscillation, 4) Indian Ocean dipole, 5) tectonic uplift and subsidence due to earthquake. The satellite altimeters and tide gauges have become major techniques for estimating SLR in the region due to the long-term data availability, except in regions with active seismic (e.g., Indonesia), tide gauge data gaps are crucial. Based on the Jason series altimeters (2002-2018), the SEA relative SLR is reported to be accelerating (2-6 mm/yr), which is critically beyond the global mean SLR (3.6 mm/yr between 2006 to 2015). Celebes Sea (6.05 ± 0.78 mm/yr), Sulu Sea (5.64 ± 0.64 mm/yr) and South China Sea (3.88 ± 0.49 mm/yr) record high SLR exceeding the global value, while Malacca Strait (2.67 ± 0.81 mm/yr) records slightly lower. Several cities (e.g., Surabaya, Jakarta, Benoa, Semarang Indonesia, and Ko Sichang and Ko Mattaphon Thailand) record extremely high SLR beyond 5 mm/yr.

Marine eddies observed in radar, optical and radiometric panoramas of the sea surface play an important role in the processes of ocean local and global mixing, suspended and organic matter redistribution, propagation of pollutant waters, biological processes et al. Meanwhile, in-situ investigations of the statistical characteristics of generating vortices in the water areas are difficult to conduct. The widespread method of marine eddies investigation is based on the remote sensing data. However, the relation between the characteristics of spiral structures and the marine eddies which lead to their manifestation is poorly studied. In order to investigate this relation, we apply the well-known MCC-method. Investigation of the horizontal fields related to the manifestation of spiral structures revealed new peculiarities which can be described analytically. The analytical model describes the velocity field composed of a marine eddy and a homogeneous current, the results are confirmed by the velocity fields obtained using satellite data, the new features of upper ocean currents associated with marine eddies are discussed. The described approach allows to retrieve inner structure of the genuine velocity field related to marine eddy.

An increasing number of underwater structures require regular, highly accurate inspections to maintain a safe and sustainable operation. Conventional sonar systems often lack the necessary resolution and precision, and camera-based systems are easily disturbed by turbid water. A technology which can bridge this gap is pulsed time-of-flight ranging. It provides higher resolution and precision compared to acoustic methods and tolerates turbid water. In this paper, we present a specialized underwater LiDAR (light detection and ranging) system which is capable of recording camera-like planar scenes using a two-dimensional beam-deflection unit. This is achieved using a combination of two rotating wedge-prisms mounted into custom-build motor modules which allows configurable linear, circular, and planar scan-patterns. Its compact design, paired with a large 33° deflection angle and 45 mm clear aperture makes it ideal for challenging underwater conditions.

Monte Carlo model and results are shown for applications to modeling the light field shallow coastal waters. The synthetic image of the water surface and water wave facets are models and the subsurface transfer of light throughout the water wave surface boundary and the subsurface transmission of simulation light is presented. The model demonstrates the influence of sensor related viewing geometry and illumination effects upon the simulated profiles of the shape factors under different wave and wind conditions. Methods used to obtain the model inputs from measurements are described. The results are applicable to predicting radiometric variables measured by satellite, airborne and drone imaging systems.

Regression-based models are widely used for retrieving water quality parameters from optical imagery. However, developing robust and accurate models in inland and nearshore coastal waters remains challenging, particularly when transferring the models in space or time. This study builds upon a machine learning regression model called extreme gradient boosting (XGBoost) to retrieve total suspended matter (TSM) concentration in optically-complex waters. XGBoost is an ensemble of decision tree models that benefits from a boosting mechanism to compensate for the prediction errors by adding more trees. We employ the trending XGBoost method for the first time for TSM retrieval. The dark spectrum fitting (DSF) atmospheric correction method is first performed on multitemporal Sentinel-2 imagery of our study area in San Francisco Bay. Then, the XGBoost-based model is trained considering samples distributed in space and time. For training, the atmospherically-corrected spectral bands of Sentinel-2 at the visible and near-infrared portion of the spectrum are used, along with the collocated in-situ measurements of TSM. We examine the temporal transferability of the proposed model by retrieving TSM for images acquired after the training period. The results are assessed based on independent in-situ matchups (70 samples). Moreover, we compare the TSM estimates with a standard optimal band ratio analysis (OBRA) model. The in-situ matchup analysis indicates a high potential of XGBoost in providing temporally robust retrievals of TSM (R² ≈ 0.77; RMSE ≈ 6 g/m³ for estimates up to 70 g/m³). On the contrary, OBRA provides poor results when transferring the model in time. Moreover, the XGBoost demonstrated to be robust to sun-glint effects.

Microatolls are massive corals on flat reefs with the colony dying in the center or there is a hole in the middle due to erosion by algae or other micro-borers. This study aims to measure the ability of UAV RGB imagery to identify micro atolls located on reef flats and objects associated with them on small islands. High resolution satellite images were also used to compare their accuracy in estimating the size of micro atolls. Some of the important steps carried out are field surveys, aerial and google earth photo acquisitions as well as mosaics, classification with segmentation based on, shape and color, texture, and shape of object proximity. RGB UAV is used to collect data and it is processed by object-based image analysis (OBIA) classification algorithm and supervised classification. This paper represents the result of UAV data analysis is more accurate and precise than high resolution satellite image data analysis. The diameter of the micro atoll can be calculated and the associated community around it. This technology allows it to be used for monitoring shallow water ecosystems bordering community activities on the mainland of small islands and producing a higher scale.

This paper and the research results presented involves the analysis and understanding of how viewing geometry and illumination geometry influences the ability to sense and correct for the presence and effects of water surface gravity waves in shallow marine waters. This paper will present results of analyses performed using imagery obtained from the WV3 satellite system. Techniques have been developed and applied to the WV3 multispectral imagery to evaluate the influence of sensor viewing geometry upon detection and removal small gravity surface water wave sun glint. The paper will discuss the approach of analysis of multiangle remote sensing for subsurface feature detection in shallow marine waters in the Space Coast Florida region.

The VIIRS sensors onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 spacecraft have provided high-quality data to the scientific community for over a decade and four years, respectively. VIIRS has 7 Thermal Emissive Bands (TEB) whose central wavelengths cover the 3.7 μm to 12.0 μm spectra. These channels are calibrated on-orbit using observations from its on-board blackbody. In the past, the efficacy of the prelaunch-derived response-versus-scan-angle (RVS) of the VIIRS TEB has been assessed postlaunch using on-orbit data from a deep space pitch maneuver and was found to be reasonable. However, vicarious calibration practices involving Earth targets can also be used to track the long-term stability of the RVS for both VIIRS instruments in orbit. This manuscript focuses on evaluating the VIIRS TEB RVS stability using an in situ ocean target – moored buoy located in the Pacific Ocean that belongs to the NOAA’s National Data Buoy Center – as reference. Cloud-free VIIRS TEB retrievals are used in this study. A normalization methodology is applied to standardize the VIIRS data to the in situ data. Results indicate that the S-NPP VIIRS TEB on-orbit performance appears to be quite stable with display marginal change rates (≤ 0.006 K/yr), while the N20 VIIRS TEB display change rates no larger than -0.013 K/yr (except for bands M13, M14, and I5). The onorbit RVS assessment demonstrates stable long-term trends that remain under the radiometric requirements (0.5 K) for most VIIRS TEB and angles-of-incidence with a few exceptions at the close-to- or edge-of-scan angles-of-incidence. Analogous methods can be used to assess the TEB on-orbit RVS stability of the VIIRS instruments that will be onboard the to-be-launched Joint Polar Satellite System-2 (JPSS-2), JPSS-3, and JPSS-4 satellites.

Pontederia crassipes, commonly known as water hyacinth (WH), is a highly invasive aquatic weed and caused significant ecological and economic impact across the world. Remediation action includes manual monitoring and removal which are often time consuming and expensive. This paper proposes the use of multi-temporal multi-spectral drone imagery for WH mapping and monitoring in Patancheru Lake, Hyderabad, India. The data collection was done in two steps: 1) multi-spectral drone imagery and 2) ground optical image capturing through an Android mobile application. Data was collected in regular interval starting from January 2021. Spectral bands were used to produce the WH detection and mapping. We compare spectral signature of clean and infested water for five different sites inside the lake. Multitemporal water quality samples of these sites were also collected together with drone data to analyse the effect of WH infestation on those parameters. The multispectral data was processed using an unsupervised machine learning classifier named expectation maximisation (EM) clustering to create a segmentation map indicating WH, water and other regions.

Interoperability of data from different sources is the main purpose of this study. The survey covers the waters of the Black Sea in Bulgaria. Our country has a maritime border of 378 km, of strategic importance and is close to military conflicts (e.g. Ukraine). The use of different satellite and in situ data in hybrid models makes it possible to obtain much more information from one point or domain. Different satellite data have been used, which are collated with registers of open and spatial data from the Bulgarian Open Data Portal. Much of the ground information is extremely rich in detailed information on the chemical, environmental and climate status of the specific point or area of interest. The survey uses Copernicus data, the Open Data Portal, the Black Sea Basin Directorate and Innovative Techniques and Methods for Reducing Marine Litter in the Black Sea Coastal Areas — (BSB552 RedMarLitter and etc. These interoperable data will be useful for coastal protection and security, environmental monitoring and adequate decision-making in the administration, business and various other groups of data users. The methodology aims to support work on Digital Twins of the Earth. Information from so many sources will at one point lead to a much more effective and efficient management of territories in the event of environmental disasters (e.g. plastic and oil pollution), various military conflicts and their consequences, as well as annual monitoring of tourist areas and many others.

In existing sea surface emissivity models, the uniform temperature deviation correction is made. Yet the isotropy and anisotropy of sea surface emissivity increment are different at different temperatures, which requires that the sea surface emissivity increment signals at different temperatures should be treated differently. In this paper, an optimized sea surface emissivity model is proposed, in which the impact of temperature is comprehensive considered. Meanwhile, the temperature data was retrieved and was as input data for the following research. The result shows that, compared with the existing temperature products, the accuracy of proposed sea surface emissivity modeling using temperature derived from this paper is improved obviously, which makes the root mean squared difference (RMSD) decrease approximately 8% and 5% for V and H polarization channel, respectively. The conclusion can be drawn that the precision of the optimized sea surface emissivity model is improved obviously.

Indo-Pacific Warm Pool (IPWP) region is a key region which is sensitive to climate change. Therefore a comprehensive knowledge of the variability of sea surface salinity (SSS) for the entire IPWP region on decadal time scale is of great importance. This study mainly focuses on the spatiotemporal variability of SSS in the IPWP region, using conventional empirical orthogonal function (EOF) analysis, the lead–lag correlation analysis and long-term trend analysis. Barnett and Preisendorfer’s improved Canonical Correlation Analysis (BPCCA) is also applied to examine the covariation of SSS and freshwater flux (F) under climate change of El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). We found that SSS in most eastern Indian Ocean regions show obviously decreasing trends, whereas slightly increasing trends are found in most western Pacific Ocean regions. The leading two EOF modes both have a strong correlation with MEI and lead MEI by approximately 5 and 2 months, respectively. The spatial distribution of the canonical modes for SSS and F are very similar, except for slightly zonal deviation of the anomaly center between SSS and F, which can be explained by horizontal advection.