This PDF file contains the front matter associated with SPIE Proceedings Volume 9638, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

In this paper, we study and analyze the influence of the presence of pollutants on the electromagnetic (EM) signature of sea surface. We firstly analyze the pollutant effect on the geometrical and dielectric properties of the sea surface. Then we evaluate the EM scattering coefficients of a sea surface polluted by petrol emulsion or contaminated by oil layer observed in bistatic configuration. The bistatic scattering coefficients of a clean and a polluted sea surface are computed from the rigorous Forward-Backward Method (FBM) and the asymptotic models Small Slope Approximation (SSA) and Two Scale Model (TSM). The models used for the numerical simulation of bistatic scattering coefficients of clean and polluted sea surface have been analyzed as a function of various acquisition parameters such as (sea state, pollutant type, incidence angle, scattering angle, radar frequency and polarizations).

An assessment of the agreement between the ERS scatterometers (ERS-1 and ERS-2) and the Metop scatterometers (ASCAT-A and ASCAT-B) is essential for the consistency of the C-band scatterometry dataset. ERS-1, ERS-2, ASCAT-A and ASCAT-B are C-band fan-beam radar scatterometers covering a range of common incidence angles. During these C-band scatterometry missions, different calibration campaigns have been carried out mainly relying on active ground transponders and natural distributed targets such as the rainforest. Additionally, these missions differ in time with some overlapping periods. Therefore, an assessment of the agreement between ERS and ASCAT measurements is an important and challenging task. This assessment is usually performed over the rainforest but only considering the common incidence angles. In order to perform the comparison over the whole incidence angle range of both radars, a Geophysical Model Function (GMF) is needed. An empirical correction of the CMOD5.n GMF has been suggested recently by KNMI resulting in a new GMF called CMOD6. This correction was derived from the comparison of the ASCAT backscatter measurements and the CMOD5.n model. Taking ASCAT’s measurements as reference, the differences between the CMOD5.n and ASCAT measurements were attributed to GMF errors. Additionally, an overview of the existing C-band models is given. The comparison of these models shows relatively large differences. The aim of this paper is the assessment of the CMOD6 GMF using ERS-1 and ERS-2 ocean backscatter measurements and the validation of the applicability of the corrected GMF to the whole C-band scatterometry dataset. Finally, a method is suggested to calibrate the residual bias of all the C-band scatterometers w.r.t CMOD6. It is shown that after calibration a consistent scatterometer data model is obtained.

The measure of sea ice surface variability provides a fundamental information on the climatology of the Arctic region. Sea ice extension is conventionally measured by two parameters, i.e. Sea Ice Extent (SIE) and Sea Ice Area (SIA), both parameters being derived from Sea Ice Concentration (SIC) data sets. In this work a new parameter (CSIA) is introduced, which takes into account only the compact sea-ice, which is defined as the sea-ice having concentration at least equal the 70%. Aim of this study is to compare the performances of the two parameters, SIA and CSIA, in analyzing the trends of three monthly time-series of the whole Arctic region. The SIC data set used in this study was produced by the Institute of Environmental Physics of the University of Bremen and covers the period January 2003 – December 2014, i.e. the period in which the data set is built using the new AMSR passive microwave sensor.

In this paper, an efficient sea surface generation is described for the fast and realistic simulation of the infrared emissivity and reflectivity of clean and contaminated seas. The clean sea surface is modelled by the Elfouhaily et al. spectrum model. For describing the surface damping due to the oil film at the sea surface, the model of local balance (MLB) is used. Thus, these surface models are used as the basis for calculating the emissivity and reflectivity. The numerical efficient computation is tested by comparison with the reference statistical computation for its validation.

Marine slicks are one of the most common features on the sea surface and a significant part of the slicks is a result of accidental or deliberate oil spills. The shape of oil slicks is their important characteristic that can be used to identify the nature of slick signatures in radar or optical images of the sea surface and possibly to describe them quantitatively. Nowadays, however, there is a lack of systematic experiments with slicks, and the very physical mechanisms of slick spreading are still not well understood. This paper presents results of controlled experiments with spills of surfactants, and a possible physical mechanism of slick asymmetry is discussed. Experiments with artificial film slicks were carried out in different environmental conditions: from an Oceanographic Platform on the Black Sea, and from a vessel on the Gorky Water Reservoir. Slick shape and its evolution were studied using photographic methods, and satellite radar imagery. In the satellite experiments surfactants were poured on the surface at certain time intervals before the satellite overpass. It is obtained that film spreading is not axial symmetric, and the spills are stretched along the wind, a long-to-short slick axis ratio weakly depends on spreading time and grows with wind speed. A physical mechanism of slick deformation due to mean surface currents induced by wind waves is proposed. Namely, drift currents induced by oblique propagating surface waves increase in film slicks due to enhanced wave damping and these currents result in reduced spreading rate in the cross wind direction. Theoretical analysis of slick spreading accounting for the effect of surface waves is presented, and theoretical estimates are shown to be consistent with experiment.

Slicks on the sea surface are characterized by attenuation of short wind waves and appeаr in radar imagery at moderate incidence angles as areas of reduced intensity. In the proximity of oil platforms, ship routes, fish farms, etc. marine slicks are often identified as oil spills or biogenic films. However, probability of false alarm when detecting film slicks is very high because of the occurrence of structures in radar images looking similar but not related to surface films (“lookalikes”). One of the most frequent "look-alikes" is wind depression areas (WDAs) where the wind excitation of short surface waves is reduced compared to the ambient background. Results of field observations of films slicks and WDA are described and differences in character of wind wave attenuation in different parts of the wind wave spectrum are revealed. Model calculations of wave damping degree (contrast) in film slick and in WDA are carried out and are shown to be in general agreement with experiment. Capabilities of dual-polarization and multi-band microwave radar for discrimination between film slicks and “look-alikes” are analyzed based on experiment and model results.

We propose to apply the compressive sensing technique to the design of satellite radar altimeter for increasing the sampling time window (STW) while keeping the same data rate so as to enhance the tracking robustness of an altimeter. A satellite radar altimeter can measure the range between the satellite platform where it is aboard and the averaged sea surface with centimeter level accuracy. The rising slope of the received waveform by altimeter contains important information about the sea surface, e.g. the larger the slope of the waveform, means the smoother the sea surface. Besides, the half-power point of the slope refers to the range information. For satellite altimeter, due to the rising slope just occupies fewer range bins compared with the whole range bins illuminated by the long pulse signal, i.e. the signal is sparse in this sense, thus compressive sensing technique is applicable. Altimeter echoes are simulated and the waveforms are constructed by using the traditional method as well as by compressive sensing (CS) method, they are very well agreed with each other. The advantage of using CS is that we can increase the sampling time window without increasing the data, thus the tracking capability can be enhanced without sacrificing the resolution.

Standard blue-green ratio algorithms do not usually work well in turbid productive waters because of the contamination of the blue and green bands by CDOM absorption and scattering by non-algal particles. One of the alternative approaches is based on the two- or three band ratio algorithms in the red/NIR part of the spectrum, which require 665, 708, 753 nm bands (or similar) and which work well in various waters all over the world. The critical 708 nm band for these algorithms is not available on MODIS and VIIRS sensors, which limits applications of this approach. We report on another approach where a combination of the 745nm band with blue-green-red bands was the basis for the new algorithms. A multi-band algorithm which includes ratios Rrs(488)/Rrs(551)and Rrs(671)/Rrs(745) and two band algorithm based on Rrs671/Rrs745 ratio were developed with the main focus on the Chesapeake Bay (USA) waters. These algorithms were tested on the specially developed synthetic datasets, well representing the main relationships between water parameters in the Bay taken from the NASA NOMAD database and available literature, on the field data collected by our group during a 2013 campaign in the Bay, as well as NASA SeaBASS data from the other group and on matchups between satellite imagery and water parameters measured by the Chesapeake Bay program. Our results demonstrate that the coefficient of determination can be as high as R² > 0.90 for the new algorithms in comparison with R² = 0.6 for the standard OC3V algorithm on the same field dataset. Substantial improvement was also achieved by applying a similar approach (inclusion of Rrs(667)/Rrs(753) ratio) for MODIS matchups. Results for VIIRS are not yet conclusive.

New approaches are described that use of the Ocean Color Remote Sensing Reflectance readings (OC Rrs) available from the existing Visible Infrared Imaging Radiometer Suite (VIIRS) bands to detect and retrieve Karenia brevis (KB) Harmful Algal Blooms (HABs) that frequently plague the coasts of the West Florida Shelf (WFS). Unfortunately, VIIRS, unlike MODIS, does not have a 678 nm channel to detect Chlorophyll fluorescence, which is used with MODIS in the normalized fluorescence height (nFLH) algorithm which has been shown to help in effectively detecting and tracking KB HABs. We present here the use of neural network (NN) algorithms for KB HABS retrievals in the WFS. These NNs, previously reported by us, were trained, using a wide range of suitably parametrized synthetic data typical of coastal waters, to form a multiband inversion algorithm which models the relationship between Rrs values at the 486, 551 and 671nm VIIRS bands against the values of phytoplankton absorption (a_ph), CDOM absorption (a_g), non-algal particles (NAP) absorption (a_NAP) and the particulate backscattering bb_p coefficients, all at 443nm, and permits retrievals of these parameters. We use the NN to retrieve a_ph443 in the WFS. The retrieved a_ph443 values are then filtered by applying known limiting conditions on minimum Chlorophyll concentration [Chla] and low backscatter properties associated with KB HABS in the WFS, thereby identifying, delineating and quantifying the a_ph443 values, and hence [Chl] concentrations representing KB HABS. Comparisons with in-situ measurements and other techniques including MODIS nFLH confirm the viability of both the NN retrievals and the filtering approaches devised.

The paper discusses the results of a research on the influence of various hydrometeorological factors on distribution of suspended matter carried by rivers into the sea. The research is based on remote sensing data received in different bands of electromagnetic spectrum. Suspended matter concentration and integral water turbidity were estimated based on data from MODIS, MERIS, ETM+, TM and OLI sensors. The study was performed for two regions with very different characteristics: the semi-enclosed Gulf of Gdańsk of the Baltic Sea and eastern part of the Black Sea. It is shown that the plume fraction with highest suspended matter concentration of the lowland River Vistula spreads primarily under the impact of wind. Low concentration plume fraction is driven by the longshore current. In case of extraordinary floods, turbid Vistula waters spread in the upper sea layer almost all over the Gulf. The situation in the eastern part of the Black Sea with its narrow shoal and abrupt shelf edge wherein flow highly turbid mountain rivers is quite different. Here, the dominating role is played by runoff. Its intensity determines both plume shape and dimensions. A strong easterly wind can change plume configuration, cause formation of jet-like plumes.

Airborne, Satellite and In-Situ optical and acoustical imaging provides a means to characterize surface and subsurface water conditions in shallow marine systems. An important research topic to be studied during dredging operations in harbors and navigable waterways is the movement of fluidized muds before, during and after dredging operations. The fluid movement of the surficial sediments in the form of flocs, muck and mud is important to estimate in order to model the transport of solids material during dredging operations. Movement of highly turbid bottom material creates a lutocline or near bottom nephelometric layers, reduces the penetration of light reaching the water bottom. Monitoring and measurement systems recently developed for use in shallow marine areas, such as the Indian River Lagoon are discussed. Newly developed passive sondes and subsurface imaging are described. Methods and techniques for quantifying the mass density flux of total particulate matter demonstrate the use of multiple sensor systems for environmental monitoring and provide directional fluxes and movement of the fluidized solids. Airborne imaging of dredge site provide wide area surveillance during these activities. Passive sondes, optical imaging and acoustical sensors are used to understand horizontal and vertical mass flux processes. The passive sondes can be directionally oriented and are deployed during optical particle velocimetry system (OPVS) imaging of the flocs, particles and colloidal material motion. Comparison of the image based particle velocities are compared to electromagnetic and acoustic velocity imaging results. The newly developed imaging system provides a pathway for integration of subsurface hyperspectral imaging for particle compositional analysis.

Taking the advantages of remotely sensed data for mapping and monitoring of water boundaries is of particular importance in many different management and conservation activities. Imagery data are classified using automatic techniques to produce maps entering the water bodies’ analysis chain in several and different points. Very commonly, medium or coarse spatial resolution imagery is used in studies of large water bodies. Data of this kind is affected by the presence of mixed pixels leading to very outstanding problems, in particular when dealing with boundary pixels. A considerable amount of uncertainty inescapably occurs when conventional hard classifiers (e.g., maximum likelihood) are applied on mixed pixels.

In this study, Linear Spectral Mixture Model (LSMM) is used to estimate the proportion of water in boundary pixels. Firstly by applying an unsupervised clustering, the water body is identified approximately and a buffer area considered ensuring the selection of entire boundary pixels. Then LSMM is applied on this buffer region to estimate the fractional maps. However, resultant output of LSMM does not provide a sub-pixel map corresponding to water abundances. To tackle with this problem, Pixel Swapping (PS) algorithm is used to allocate sub-pixels within mixed pixels in such a way to maximize the spatial proximity of sub-pixels and pixels in the neighborhood.

The water area of two segments of Tagliamento River (Italy) are mapped in sub-pixel resolution (10m) using a 30m Landsat image. To evaluate the proficiency of the proposed approach for sub-pixel boundary mapping, the image is also classified using a conventional hard classifier. A high resolution image of the same area is also classified and used as a reference for accuracy assessment. According to the results, sub-pixel map shows in average about 8 percent higher overall accuracy than hard classification and fits very well in the boundaries with the reference map.

Satellite remote sensing is an efficient tool to identify buoyant river plumes in the coastal ocean, formed by interaction between the river and the ambient sea waters. The observed spatial extent, shape and orientation of the plume are indicative of the respective river discharge. A new method of reconstructing the volume of river discharge using satellite imagery and numerical modelling is presented in this article. At the first step of the procedure, we use a high resolution satellite image of the coastal area adjacent to the examined river estuary to identify the buoyant plume. Then a number of required river, atmospheric and sea parameters (including river discharge) are prescribed for the hydrological model to simulate the spread of river discharge under this configuration. The characteristics of the simulated river plume are compared with the corresponding characteristics of the plume identified at the satellite image. Varying model forcing conditions and iteratively improving the accordance between these plumes we consequently specify the value of river discharge. The developed method was applied for the eastern coast of the Black Sea to evaluate the influence of the short-term and annual precipitation conditions on the variability of river discharge inflowing from the Russian coast to the Black Sea.

Concentration of suspended sediment directly affects the optical properties such as transparency and water color, and aquatic environment as well. This paper selects the Taiwan Strait as study area, establishes inversion mode of suspended sediment by coupling field data with remote sensing reflectance from MODIS data. Monthly-averaged concentrations and seasonal changes of suspended sediment from 2003 to 2012 were calculated and analyzed by the mode. The main results are as follows:(1) remote sensing reflectance at 555nm from MODIS data has high relativity with the field observed turbidity by regression equation of Y =0.8931e^123.93x in which Y is TSM concentration, X is R_rs555 and R² is 0.6836. (2)Suspended sediment in the Taiwan Strait has obviously spatial and temporal distribution characteristics, that higher concentration of suspended sediment is in coastal water and decreases from shore to sea, and highest concentration happens in winter.

It is very hard to access cloud-free remote sensing data, especially for the ocean color images. A cloud removal approach from ocean color satellite images based on numerical modeling is introduced. The approach removes cloud-contaminated portions and then reconstructs the missing data utilizing model simulated values. The basic idea is to create the relationship between cloud-free patches and cloud-contaminated patches under the assumption that both of them are influenced by the same marine hydrodynamic conditions. Firstly, we find cloud-free GOCI (the Geostationary Ocean Color Imager) retrieved suspended sediment concentrations (SSC) in the East China Sea before and after the time of cloudy images, which are set as initial field and validation data for numerical model, respectively. Secondly, a sediment transport model based on COHERENS, a coupled hydrodynamic-ecological ocean model for regional and shelf seas, is configured. The comparison between simulated results and validation images show that the sediment transport model can be used to simulate actual sediment distribution and transport in the East China Sea. Then, the simulated SSCs corresponding to the cloudy portions are used to remove the cloud and replace the missing values. Finally, the accuracy assessments of the results are carried out by visual and statistical analysis. The experimental results demonstrate that the proposed method can effectively remove cloud from GOCI images and reconstruct the missing data, which is a new way to enhance the effectiveness and availability of ocean color data, and is of great practical significance.

Particulate Organic Carbon (POC) plays an important role in sink of atmospheric CO2, global carbon cycle, etc. Around river estuary, POC is sourced from terrestrial ecosystem and aquatic ecosystem; its distribution features might be complex and likely to change with time. Based on in-situ samples from four seasonal cruises, we discussed spatial-temporal distribution and remote sensing monitoring of POC concentration in the Pearl River Estuary (PRE). Being affected by larger discharge from the Pearl River, surface POC concentrations in summer were usually higher than those in other three seasons, similar, in the PRE. However, because of sediment resuspension, POC concentrations at the bottom layer were higher than those at the surface layer. Taking the PRE as an example, remote sensing monitoring of POC concentration in case II water around estuary was also discussed. On the one hand, on the basis of Chlorophyll-a (Chl-a) and Total Suspended Matter (TSM) concentrations inversed by published algorithms, we can estimate surface POC concentration through multiple linear regression equation: POC=0.042*Chl-a+0.014*TSM+0.1595, R=0.9156. On the other hand, great relationships between surface POC concentrations and total particle absorption coefficient at 667nm (TPabs(667)) and 678nm (TPabs(678)) were also found: POC=3.813*TPabs(667)+0.0684, R=0.8769 and POC=3.9175*TPabs(678)+0.0624, R=0.8745. They implied the possibility of estuarine POC monitoring from space through remote sensing reflectance at 667nm or 678nm.

In this study, a 3-hourly time resolution gap free sea surface temperature (SST) analysis is generated to resolve the diurnal cycle in the South China Sea (SCS, 0°–25°N, 100°–125°E).It takes advantage of hourly geostationary satellite MTSAT observations and combines three infrared and two microwave polar satellite observations at different local times. First, all the data are classified into eight SST datasets at 3 hour intervals and then remapped to 0.05°resolution grids. A series of critical quality control is done to remove the outliers.Then bias adjustment is applied to the polar satellite observations with reference to the MTSAT data. Finally, the six satellites SST data are blended by using the optimal interpolated algorithm. The 3-hourly blended SST is compared against buoy measurements. It shows a good agreement that the biases do not exceed 0.2 °C and root mean square errors range from 0.5 to 0.65 °C. A typical diurnal cycle similar to sine wave is observed. The minimum SST occurs at around 0600h and warming peak occurring between 1300h and 1500h local solar time and then decrease in the late afternoon, tapering off at night on March 13, 2008 for example. The frequency of diurnal warming events derived from four years of the blended SST provides solid statistics to investigate the seasonal and spatial distributions of the diurnal warming in the SCS. The sea surface diurnal warming tends to appear more easily in spring, especially in the coastal regions than other seasons and the central regions.

The results of long-term satellite survey of the aquatic area of the Caspian Sea are presented. The patterns of surface oil pollution of the Caspian Sea are described and analysed. It is demonstrated that surface oil pollution is often caused by natural causes, namely by natural hydrocarbon seepages and mud volcanoes activity on the sea bottom. A combined analysis of oil film signatures in satellite radar and optical imagery data is performed. Mapping of the main types of surface pollution of the Caspian Sea is performed and areas of the heaviest pollution are outlined and analysed. Dependence of radar signatures of sea surface oil patches on the wind/wave conditions is investigated. The large amount of the data available allowed us to make some generalizations and obtain statistically significant results on a spatial and temporal variability of various sea surface film manifestations in SAR images. The impact of dynamic and circulation processes and natural factors (current meandering, vortical activity, temperature and wind patterns) on spatial and temporal distributions and intensity of oil films is studied. The connection between manifestations of natural seepages and mud volcanoes and earthquake activity in South Caspian and adjacent areas is established.

There is no agreement for the extensive of mangrove forest in Indonesia, but invarious forums it is usually used the number of 4.25 million ha for that. At approximately 9 years ago, the extensive vast of mangrove forest in Indonesia was about 4.13 million ha but now it is only 2.49 million ha (60%). Remote sensing could play an important and effective role in the assessment and monitoring of mangrove forest cover dynamics. The aim of this study is to measure change of the mangrove cover from the 1972 to 1993, from 1993 to 2003, from 2003 to 2013, and from 1972 to 2014 using multitemporal Landsat. The study site was selected in Tanakeke Island, Takalar District, South Sulawesi, Indonesia. The results of analyze shows the mangrove forest is decrease and It is caused anthropogenic impact.

The uptake of carbon dioxide (CO₂) by the Arctic Ocean has been changing because of the rapid sea-ice retreat with global warming. The Chukchi Sea is the only gateway of the warm and nutrient-rich Pacific Ocean water flowing into the North Pole, and the high productivity-water had great impact on the CO₂ uptake by the Arctic Ocean. We used the in situ underway data of aquatic partial pressure of CO₂ (pCO₂), temperature and salinity, as well as the remote sensing data of sea ice concentration, chlorophyll concentration, sea surface temperature in August in 2008, 2011 and 2012 to analyze the major controlling factors of aquatic pCO₂ in the Western Arctic Ocean. We analyzed the pCO₂ variation under the effects of thermodynamic process (temperature), mixing of water mass (salinity), biological drawdown (chlorophyll), and sea ice concentration. The aquatic pCO₂ was generally unsaturation relative to the atmospheric CO₂ in most of the Western Arctic Ocean. According to different controlling mechanisms, the study area was divided into three parts: the area affected by the Pacific Ocean water (mainly in the Chukchi Sea), the area where sea ice mostly melted with weak biological production (the southern Canada Basin and the Western Beaufort Sea), and the area mostly covered by sea ice (the Northern Canada Basin). The aquatic pCO₂ was low in the Chukchi Sea with the influence of the Pacific Ocean water. While, pCO₂ in the area where sea ice melted was up to 360-380 μatm because of warming, CO₂ invasion from the atmosphere, and a low biological production. For the Canada Basin, it was controlled by temperature change and sea ice cover. The remote sensing data in large spatial-temporal scale can help to understand the pCO₂ variation and its response to global change; and it needs to develop satellite algorithm of pCO₂ based on the quantification of controlling processes.

Coexistence of swells from distant sources and wind seas generated by local wind field results in complex surface wave condition. Identification and separation analysis of wave components of the wind sea and swell provide a more realistic depiction of the sea state and is important for understanding of the mechanisms of climate variability in the wave field. Spectral separating is one of the most important methods in partitioning waves. Two separating methods including the initial wave steepness method (STPN) and modified wave steepness method (MSTPN) that proposed by the National Data Buoy Center (NDBC) are described in this paper. And the NDBC buoy observations are applied in this study to investigate STPN and MSTPN. Although MSTPN method is improved from the STPN method, it is still not fit for the swell effect. Considering limitations mentioned above, we use spectral energy proportion (SEP) to describe the swell effect and abstract the valid data according to this index. Finally, we give a description of correlation between significant wave height (SWH) and wind speed under the wind sea condition. From results, it is shown that SWH and wind speed of wind sea have a quasiquadratic fitting relationship. In addition, it shows that MSTPN is a better performance in application as expected. Our work for spectral partitioning algorithms could provide a reference for the future work in satellite spectral data. And a practical method for deriving the SWHs from wind speed of scatterometer will be realized on the basis of the empirical wind and sea relationship.

Oceanic internal waves are often observed by SAR. So SAR provides a new technique for measuring internal wave in a large area. And it is complementary to traditional measurements. The procedures are given in this paper for extracting the direction, wavelength, amplitude, speed and depth of internal waves. ENVISAT ASAR and Radarsat-2 SAR images of South China Sea are used to extract the parameters. And HJ-1 optical images are used to assist. Then some in-situ data from buoy is used to verifying the extraction results. The times of in-situ data and SAR image are similar. The results are shown that: 1) The internal wave parameter can be extracted from SAR images, although sometime the extraction needs other data. 2) The error of wave direction between SAR and in-situ is less than 15 degree. The error of wave amplitude between SAR and in-situ is less than 15m, the relative error is less than 20%. 3) The wavelength of internal wave can’t be measured by buoy. The wave depth, measured by buoy, is the depth where the velocity of flow is maximum. It isn’t the depth of internal wave.

Airborne laser bathymetry (ALB) can be used for hydrographic surveying with relative high resolution in shallow water. In this paper, we examine the applicability of this technique based on three flight campaigns. These were conducted between 2012 and 2014 close to the island of Poel in the German Baltic Sea. The first data set was acquired by a Riegl VQ-820-G sensor in November 2012. The second and third data sets were acquired by a Chiroptera sensor of Airborne Hydrography AB in September 2013 and May 2014, respectively. We examine the 3D points classified as seabed under different conditions during data acquisition, e.g. the turbidity level of the water and the flight altitude. The analysis comprises the point distribution, point density, and the area coverage in several depth levels. In addition, we determine the vertical accuracy of the 3D seabed points by computing differences to echo sounding data. Finally, the results of the three flight campaigns are compared to each other and analyzed with respect to the different conditions during data acquisition. For each campaign only small differences in elevation between the laser and the echo sounding data set are observed. The ALB results satisfy the requirements of IHO Standards for Hydrographic Surveys (S-44) Order 1b for several depth intervals.

A experimental laboratory study of the effect of a horizontally inhomogeneous current on breaking statistics of wind waves was carried out. Were creating a current having the same direction as wind waves with positive and negative gradients and a current of the counter direction with a negative gradient. The wind speed varied from 10.4 to 20.1 m/s based on a standard height of 10 m. The maximum current velocity near the surface was 27 cm/s. The maximum current gradient was equal to 0.09 1/s. The codirected current reduces the wind wave amplitude for all wind speeds, while the frequency of the spectral density maximum of wind waves remains the same. The frequency of the recorded by radar wind-wave breaking also decreases for positive, negative, and zero gradients. In the case of counter directions, for light winds in the presence of a current the wind wave amplitude reduces, the wind wave spectrum displaces in the direction of lower frequencies. At higher wind speeds, there were neither differences in the surface wave spectra in the presence and absence of a current, however, an increase in the frequency of the recorded by radar wind-wave breaking is observed. These laboratory investigations are carried out in the interests of the remote diagnostics methods development of inhomogeneous currents at higher wind speeds.

This paper presents the prediction models which analyze and compute the CO₂ emission in Malaysia. Each prediction model for CO₂ emission will be analyzed based on three main groups which is transportation, electricity and heat production as well as residential buildings and commercial and public services. The prediction models were generated using data obtained from World Bank Open Data. Best subset method will be used to remove irrelevant data and followed by multi linear regression to produce the prediction models. From the results, high R-square (prediction) value was obtained and this implies that the models are reliable to predict the CO₂ emission by using specific data. In addition, the CO₂ emissions from these three groups are forecasted using trend analysis plots for observation purpose.