Bathymetry Model Research Articles

Usporedba i analiza javno dostupnih batimetrijskih modela na području istočnog Jadranskog mora

In this paper the latest versions of six publicly available bathymetry models: DTU10bat, EMODnet 2018, ETOPO1, GEBCO 2020, Smith and Sandwell V20.1 and SRTM15+ V.2.1. are compared and evaluated in the area of continental shelf of Croatia settled along well intended east Adriatic coast. Survey data in the area is not available through open access data bases, but publicly accessible in agreement with data holders (hydrographic institute, research centres and industry). These grids provide alternative sources of information about seafloor topography. Marine researchers should be acquainted with the main characteristics as well as pros and cons of bathymetry models in order to choose the best one for a specific purpose. In this paper the most important characteristics and information about grids are presented: resolution, coverage, release date, horizontal and vertical datum, data source, registration method, producer and link to website with an emphasis on the underlying source data. The underlying source data is one of the most important parameters that determine the quality of the bathymetric model. Hypsometry curve that is describing the area distribution of depth is calculated for each bathymetry model over the test area of the east Adriatic. For pixel to pixel comparison, grids were resampled to same one-minute resolution and absolute differences between models are calculated in identical points. Absolute differences between models show level of mutual compatibility between models as well as areas of highest disagreements that indicate the presence of outliers or systematic errors within models. In order to demonstrate how well publicly available bathymetry models fit the true topography of the sea floor, grids were compared to high-resolution digital bathymetry model interpolated from the multibeam survey in the area of Murter Sea. This paper should assist in the choice of a most suited bathymetry grid in future maritime studies in the Adriatic.

GIS-linked tidal range energy resource assessment

A technique is applied for the estimation of tidal power in estuaries using geostatistical methods. Tidal data of 9 years for six different locations in creek region of Pakistan is utilized for the first time, to develop four different geostatistical models for tidal range energy resource assessment. Validation for all models is performed and best-fitted model is selected for estimation of tidal data at un-observed locations. Results obtained from selected model are found well-matched with the observed data. Finally, the tidal power density model is developed showing tidal potential power density ranges between 0.634 and 1.124 W/m2. Since bathymetry is essential to identify regions with adequate water depth for tidal impoundment, sluices, and turbine installation, thus, bathymetry model is also developed. With projected basin area, adequate bathymetry, and suitable turbine, three sites are proposed for harnessing tidal potential energy. Total estimated output power from this regime is 358.29 MW.

Refining Altimeter-Derived Gravity Anomaly Model from Shipborne Gravity by Multi-Layer Perceptron Neural Network: A Case in the South China Sea

Shipborne gravity can be used to refine altimeter-derived gravity whose accuracy is low in shallow waters and areas with complex submarine topography. As altimeter-derived gravity only within a small radius around the shipborne data can be corrected by traditional methods, a new method based on multi-layer perceptron (MLP) neural network is proposed to refine the altimeter-derived gravity. Input variables of MLP include the positional information at observation points and geophysical information (from our own South China Sea gravity anomaly model (SCSGA) V1.0 and bathymetry model ETOPO1) at grid points around observation points. Output variables of MLP are the refined residual gravity anomalies at observation points. Training shipborne data are classified into four cases to train four MLP models, which are used to predict the refined gravity anomaly model SCSGA V1.1. Then all of the training shipborne data are used for training an MLP model to predict the refined gravity anomaly model SCSGA V1.2. Assessed by testing shipborne data, the accuracy of SCSGA V1.2 is 0.14 mGal higher than that of SCSGA V1.0, and similar to that of SCSGA V1.1. Compared with the original gravity anomaly model (SCSGA V1.0), the accuracy of the refined gravity anomaly model (SCSGA V1.2) by MLP is improved by 4.4% in areas where the training data are concentrated, and also improved by 2.2% in other areas. Therefore, the method of MLP can be used to refine the altimeter-derived gravity model by shipborne gravity, overcoming the problem of limited correction radius for traditional methods.

Partition satellite derived bathymetry for coral reefs based on spatial residual information

ABSTRACT Satellite imagery with high spatial and temporal resolutions provides strong support for remote sensing bathymetry. Heterogeneous underwater environments such as complex bottom types represent the main factor affecting accuracy of satellite derived bathymetry. Segmenting imagery can enhance geospatial adaptability and improve the accuracy. Conventionally, satellite imagery can be subdivided based on bottom types confirmed by a priori knowledge gained from in situ observations (e.g. video and photos); however, this process poses challenges concerning some politically sensitive or unreachable areas. Besides, water depth in coral reef areas is generally shallow (depth range: 0 to 5 m) and complex, and it has proved difficult to improve bathymetric mapping accuracy with passive multispectral imagery in such areas using traditional models. With the spatial distribution of the residuals of discrete points to realize regional segmentation, this study developed an effective partition model for satellite derived bathymetry without the need for a priori knowledge of bottom types. WorldView-2 high resolution (2 m) imagery of Dongdao Island (China) was used in the study. The results of a practical application of the model revealed the following. (1) The developed partition bathymetry model reflected underwater topographical changes and features more clearly than a comparative global model, especially in certain areas of complex terrain. (2) The accuracy of the residual partition model (Mean Absolute Error (MAE): 0.96 m, Mean Relative Error (MRE): 11.04%, and Root Mean Square Error (RMSE): 1.36 m) is greater than the global model and the conventional partition model. (3) In different water depth intervals, the residual partition model has always the best accuracy. Subregion models corresponding to the proposed models are more stable and more accurate than those to the conventional partition model. In areas of shallow water (depth: 0 to 5 m), the MRE of a subregion-A model using the residual partition method is 14.09%, i.e. better than the global model (19.45%). The findings demonstrate that the developed model can largely overcome the problem of poor precision in shallow water associated with conventional models.

BATHYMETRIC AND GEOLOGICAL PROPERTIES OF THE ADRIATIC SEA

Advance in the visualization of the bathymetric and geological data from charted to digital maps and models opened the possibility to analyse data within Geographic Information System (GIS) functionalities. In this paper, bathymetric and geological properties of the Adriatic Sea were analysed using the General Bathymetric Chart of the Ocean (GEBCO) 2020 digital bathymetric model (DBM) and data from the European Marine Observation and Data Network (EMODnet). The bathymetric analysis includes depth statistics, area and volume calculation, hypsometry, and analysis of the heterogeneity of bathymetric data from the GEBCO 2020 DBM within the limits of the Adriatic defined by the International Hydrographic Organization (IHO) and 3 sub-basins delineated according to the bathymetry. The geological analysis includes seabed substrate map from EMODnet data and kilometre-scale seabed variability in the Adriatic. The GEBCO 2020 DBM shows that the Adriatic Sea is a shallow sea with a mean depth of -253 metres and over 50% of area shallower than 100 metres. The area of the Adriatic Sea is 138 516 km2 with a total volume of 35 521 km3. Patterns describing morphological variability coincide with the heterogeneity of the underlying source data of the GEBCO 2020 digital bathymetry model and major structures in the Adriatic Sea.

Способ оценки точности метода интерполяции в батиметрических цифровых моделях рельефа

Разработан способ оценки точности метода интерполяции для ЦМР GEBCO_08 и Global Topography. Точность метода интерполяции оценивается по точности значений глубин в ЦМР в зависимости от расстояния до ближайшей ячейки ЦМР, значения глубин которой основаны на измеренных исходных данных. В результате, наблюдается сходное распределение ошибок в обеих ЦМР: ближе к исходным данным точность ЦМР ниже, чем вдали от исходных точек данных. Расстояние, на котором уменьшаются ошибки, контролируется плотностью исходных данных, количеством точек данных внутри полигонов, а также параметром натяжения, используемым в алгоритме сплайн. Плотность распределения исходных данных в пределах полигонов исследования относительно высока для оценки точности предсказанного рельефа с заявленным пространственным разрешением 20–160 км.

Analysis of water balance in Aral Sea and the influencing factors from 1990 to 2019

咸海地处中亚，气候和人类的双重影响下湖面急剧萎缩引发区域生态危机，定量解析其水量平衡互动关系及影响因素对咸海地区水资源管理和生态保护有重要意义.基于1990—2019年密集时序Landsat影像、T/P卫星、Jason1/2测高卫星及咸海数字测深模型（DBM），提取近30年咸海面积、水位变化信息，重建咸海水位-面积-库容曲线，探明咸海水量变化特征；建立水量平衡模型，定量分析研究区水量平衡要素变化及时空差异，探讨其互动关系与影响机制.结果表明：（1）1990—2019年间，咸海水量减少了2271.6×10⁸ m³（约75.15%），年平均变化率达-78.3×10⁸ m³/a；南咸海水量变化趋势与咸海整体基本一致，北咸海除1999年出现了极小值外，其余年份水量变化趋势均呈波动上升状态，至2019年水位已恢复至1984年水平.（2）1990s以来，南、北咸海水量平衡结构变化时空差异显著，阿姆河入湖径流量呈波动减少趋势，随着咸海持续退缩水体蒸发不断减小，区域水量支出收入比由1990年的2.46降低到2015年的0.87；近年来丰水年份南咸海地下水可由亏损转化为盈余状态，水域变化进入相对平缓的状态.北咸海入湖径流量波动增加，蒸散发随水域面积增加而增加，1990s初以来水量收入超过水量支出，区域地下水盈余，湖泊水位不断抬升.（3）湖区尺度上，入湖径流量和水域蒸发量是咸海水量变化的主导因素.流域尺度上，气候变化与人类活动共同影响咸海入湖水量，南咸海入湖水量与阿姆河上游来水、流域耕地面积显著相关，而北咸海入湖水量主要与锡尔河上游来水相关.;The Aral Sea is located in Central Asia. Under the impact of climate change and human activity, the lake surface has shrunk sharply and triggered a regional ecological crisis. It is of great significance to study the changes of water balance and their driving factors for water resources management and ecological protection in the Aral Sea region. Based on the dense time-series Landsat imagery from 1990 to 2019, T/P satellite, Jason1/2 altimetry satellite, and digital bathymetry model (DBM) of the Aral Sea, time serieses of the Aral Sea area and water level in the past 30 years were extracted, to reconstruct the Aral Sea water level-area-volume capacity curve and explore the characteristics of the Aral Sea volume changes. A water balance equation was also established to quantitatively analyze the spatiotemporal changes of the water balance elements in the study area and their impacts on the Aral Sea volume. The results show that the water volume decreased by 2271.6×10⁸ m³ (about 75.15%) with an average decreasing rate of 78.3×10⁸ m³/a from 1990 to 2019 in the Aral Sea, a similar variation trend was detected in the South Aral Sea. Except for the minimum value in 1999, the water volume in other years showed a fluctuating and rising state in the North Aral Sea. By 2019, the water level had returned to the level of 1984. Since the 1990s, the inflow from the Amu Darya River to the Aral Sea showed a decreasing trend, and the spatiotemporal differences in the water balance structure of the South and the Nouth Aral Sea are significant. As the Aral Sea continues to shrink, and water evaporation continues to decrease, the regional water expenditure and income ratio decreases from 2.46 in 1990 to 0.87 in 2015. In recent years, the groundwater in the South Aral Sea changed from deficit to surplus, and the water area changed into a relatively stable state. The evapotranspiration of the North Aral Sea increased with the increase of the water area. Since the early 1990s, the water income has exceeded its expenditure, regional groundwater has bacome surplus, and the lake water level has been constantly rising. On the regional scale of the Aral Sea, the inflow and evaporation are the main factors affecting the change of the water volume in the Aral Sea. On the catchment scale, climate change and human activities jointly affect the inflow of the Aral Sea. The inflow of the South Aral Sea is significantly correlated with the runoff from the upper Amu Darya River and the cultivated land area of the basin, while the inflow of the North Aral Sea is mainly correlated with the runoff from the upper Syr River.

UNCERTAINTY OF BATHYMETRY MODELS AND EFFECT ON TSUNAMI MODELS

We describe the uncertainties of altimetry-predicted bathymetry models and then quantify the impact of this uncertainty in tsunami hazard assessments. The study consists of three stages. First, we study the statistics of errors of altimetry-predicted bathymetry models. Second, we employ these statistics to propose a random field model for errors anywhere. Third, we use bathymetry samples to conduct a Monte Carlo simulation and describe the tsunami response uncertainty. We found that bathymetry uncertainties have a greater impact in shallow areas. We also noted that tsunami leading waves are less affected by uncertainties.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/zzL_XWWAQ7o

Seafloor Topography Estimation from Gravity Anomaly and Vertical Gravity Gradient Using Nonlinear Iterative Least Square Method

Currently, seafloor topography inversion based on satellite altimetry gravity data provides the principal means to predict the global seafloor topography. Researchers often use sea surface geoid height or gravity anomaly to predict sea depth in the space domain. In this paper, a comprehensive discussion on seafloor topography inversion formulas in the space domain is presented using sea surface geoid height, gravity anomaly and introduces an approach that uses vertical gravity gradient. This would be the first study to estimate seafloor topography by vertical gravity gradient in the space domain. Further, a nonlinear iterative least-square inversion process is discussed. Using the search area for the Malaysia Airlines Flight MH370 as study site, we used the DTU17 gravity anomaly model and SIO V29.1 vertical gravity gradient to generate the seafloor topography. The results of the proposed bathymetric models were analyzed and compared with the DTU18 and SIO V20.1 bathymetric models. The experimental results show that the gravity anomaly and vertical gravity gradient in the study area are strongly correlated with the seafloor topography in the 20–200 km wavelength range. The optimal initial iteration values for seafloor topography variance and correlation length are 0.6365 km2 and 10.5′, respectively. Shipborne measurements from SONAR data were used as external checkpoints to evaluate the bathymetric models. The results show that the RMS for BAT_VGG_ILS (inversion model constructed by vertical gravity gradient) is smaller than for BAT_GA_ILS (inversion model constructed by gravity anomaly) and BAT_GA_VGG_ILS (inversion model constructed by gravity anomaly and vertical gravity gradient). The relative accuracy of the DTU18 bathymetry model was 9.27%, while the relative accuracy of the proposed seafloor models was higher than 4%. Within the 200 m difference range, the proportion of checkpoints for BAT_VGG_ILS was close to 95%, about 80% for BAT_GA_ILS and BAT_GA_VGG_ILS, and less than 50% for the DTU18. The results show that the nonlinear iterative least square method in the space domain is feasible.

Validation of VDatum in Southeastern Louisiana and Western Coastal Mississippi

We present a novel study to utilize US Geological Survey water level gauges that were not meant for tidal studies to diagnose errors in the National Oceanic and Atmospheric Administration (NOAA) Vdatum tool in southeastern Louisiana and western coastal Mississippi. The US NOAA developed a Vertical Datum Transformation tool (VDatum) that allows for conversions between geodetic, orthometric, and tidal vertical datums. However, in southeastern Louisiana and western Mississippi, VDatum uncertainties have been reported by NOAA to be perhaps as high as 0.20–0.50 m (https://vdatum.noaa.gov/). These uncertainties exceed IHO S44 special order and order 1. We performed validation measurements for VDatum in the region of concern at three USGS water level gages (CSX Railroad, Delacroix, and Rigolets) and one offshore location (Chandeleur East) utilizing a HydroLevel buoy. Tidal datums estimated using Modified Range Ratio method at these stations were compared with the corresponding tidal datums determined using VDatum. We hypothesize that the errors in VDatum are due to errors in: the tuning of the model or in the model bathymetry and coastline resulting in an incorrect tidal range, and in the topography of the sea surface in that region.

EVALUASI HASIL PEMODELAN BATIMETRI DARI BEBERAPA KOMBINASI SATELIT ALTIMETRI PADA LAUT NATUNA DAN LAUT SULAWESI

Indonesia is an archipelago country where 77% of its territory is waters. National marine mapping has been carried out based on depth measurement data obtained using echosounders. However, this method requires a lot of time and cost. One solution to provide Indonesian bathymetry data is by utilizing altimetry satellite data to model the bathymetry of the seafloor. This study aims to evaluate bathymetric model generated from three combinations of five altimetry satellites in shallow and deep seas. We use least square collocation gravity anomaly and geological gravity for bathymetry modeling. The results of the model show variations in deviations with sounding data available at the Geospatial Information Agency (BIG) . The resulting residual trend differs between shallow and deep sea. The optimum results in shallow area is obtained by the combination of Cryosat-2, Jason-1/C, and SARAL while in deep area is obtained by the combination of ERS-1/E-F and Geosat GM. In general, the bathymetry model produced in this study has a similar profile with the sounding data.

GEOGRAPHICALLY WEIGHTED REGRESSION APPROACH FOR SHALLOW WATER DEPTH ESTIMATION USING MULTISPECTRAL SATELLITE IMAGERIES

Abstract. Shallow water depth is essential for coastal planning, monitoring, and research. Bathymetry data is mostly produced from hydrographic survey using echosounder. The generic result from those measurements is discrete values while the desired output is a continuous depth model. To fill the gaps in the sounding data, we use Satellite Derived Bathymetry (SDB) approach with Geographically Weighted Regression (GWR). This study aims to investigate the feasibility of GWR to model bathymetry of shallow water in the eastern part of Indonesia. We explore the correlation between the number of training data and the predicted result. Two different satellites images are used, namely: Sentinel-2A and Landsat 8 OLI/TIRS with 10 and 30 m resolutions respectively. For the experiment, in-situ data are set into training and validation in three different ratios. The model is developed using adaptive GWR approach in which the parameter of regression would adapt the local data set within different kernel sizes. Finally, we compute RMSE (Root Mean Square Error), R2, and TVU (Total Vertical Uncertainty) to assess the quality of our model. In general, Sentinel-2A produces more detailed information due to higher resolution than Landsat 8 OLI/TIRS. Sentinel-2A also obtains more accurate results based on RMSE values. The percentage number of the estimated depth that fulfils TVU requirements is up to 83%. These assessment quality results give us an insight that the SDB approach using GWR is promising. Thus, the GWR method may be able to provide an estimate of bathymetry for many coastal areas in Indonesia.

Sensitivity assessment of bathymetry and choice of tidal constituents on tidal-stream energy resource characterisation in the Gulf of California, Mexico

There has been a significant increase in the number of published tidal-stream energy resource assessments in recent years due to the growing availability of open-source hydrodynamic models, and freely available data for model bathymetry (e.g. GEBCO_2014 and ETOPO) and boundary conditions (e.g. TPXO, FES, EOT). This study examines how the choice of bathymetry and tidal constituents affects the quantification of a tidal-stream energy resource, by conducting sensitivity tests for the Gulf of California. We find that the mean KPD (Kinetic Power Density) and annual mean power are significantly underestimated when using just GEBCO_2014 or ETOPO bathymetry data sources on their own. For the Midriff region, between San Lorenzo and San Esteban Islands (herein the San Lorenzo Passage), the annual mean power potential was estimated to be around 50 MW when using freely available bathymetry data, while the annual mean power increased to ~200 MW when using a bespoke dataset that was a combination of GEBCO and higher-resolution bathymetry provided by CICESE (The Centre for Scientific Research and Higher Education at Ensenada). Current speeds reduce from 2.4 m/s when using high-resolution to around 1.2 m/s and 0.8 m/s when using open source bathymetry products. Finally, we compared the estimated energy using tidal levels predicted from 29 tidal constituents compared with simulations that included just the principal semi-diurnal lunar (M2) and solar (S2) constituents. The annual mean KPD reduced by almost 1/3rd in the San Lorenzo Passage, when just considering M2 and S2 constituents, suggesting that diurnal and higher order harmonic constituents are important for accurate resource assessments in this region.

Bathymetry Beneath Ice Shelves of Western Dronning Maud Land, East Antarctica, and Implications on Ice Shelf Stability

AbstractAntarctica's ice shelves play a key role in stabilizing the ice streams that feed them. Since basal melting largely depends on ice‐ocean interactions, it is vital to attain consistent bathymetry models to estimate water and heat exchange beneath ice shelves. We have constructed bathymetry models beneath the ice shelves of western Dronning Maud Land by inverting airborne gravity data and incorporating seismic, multibeam, and radar depth references. Our models reveal deep glacial troughs beneath the ice shelves and terminal moraines close to the continental shelf breaks, which currently limit the entry of Warm Deep Water from the Southern Ocean. The ice shelves buttress a catchment that comprises an ice volume equivalent to nearly 1 m of eustatic sea level rise, partly susceptible to ocean forcing. Changes in water temperature and thermocline depth may accelerate marine‐based ice sheet drainage and constitute an underestimated contribution to future global sea level rise.

Absolute Centroid Location of Submarine Earthquakes from 3D Waveform Modeling of Water Reverberations

AbstractOceanic transform faults (OTFs) represent an attractive tectonic environment to investigate how slip is accommodated within the crust. However, as most of these fault systems grow in the deep ocean, where few local seismic observations are available, characterizing their earthquake behavior is complicated and remains a formidable challenge. Here we present a novel approach for retrieving precise centroid locations of submarine earthquakes that is based on the modeling of water phases in teleseismic records. Using a hybrid method for simulating far‐field body waves with 3D source‐side structures, we demonstrate that the scattered energy generated by the continuous bounces of an earthquake's P‐wave trapped in the ocean is modelable and carries information about its source location. As a case study, we use a realistic bathymetry model of the Gofar transform fault on the East Pacific Rise and simulate the seismic wavefield at US Array stations for four of its moderate‐sized (Mw5.0+) earthquakes. Our modeling results show that water phases are sensitive to a ∼5 km change in the earthquake's horizontal location and that a remarkable agreement between observed and synthetic water phases is achieved when the location of an event is close to its true one. We then relocate three of these events by systematically computing their water phases in candidate locations until a satisfactory waveform fit is achieved. This analysis technique paves a new route for studying earthquake source properties in isolated marine environments and serves as a mean to investigate the seismic behavior of OTFs on a global scale.

Hydro-acoustic Survey and Edge-detection method in Investigation of a Passenger Vessel Accident in East Java, Indonesia

As an archipelagic country, the shipping sector in Indonesia becomes crucial in delivering goods inter-island, and due to increasing transportation demands. However, that industry encounters some challenges of the ocean environment that could lead to vessel accidents. An investigation into the accident is crucial since this is related to the properties, environment, and life disadvantages. The wrecks of sinking vessels also could harm the environment, providing an obstacle to the sea passage hence increasing the risk of a shipping operation. A proper and comprehensive investigation needs to be carried out to identify the factors that contribute to the accident, so then risk mitigation can be taken to prevent re-occurrence. In the case of missing foundered or sunken vessels, an underwater examination is a must, so the investigator understands the real condition of the vessel. Although diver and underwater robotic surveys are still prevalent in the investigation, these techniques have limitations due to visibility and location. By contrast, those limitations can be addressed using hydro-acoustic technologies, which are capable of providing high-resolution underwater images and digital elevation model (DEM) bathymetry. Thus, the use of these technologies is promising in-vessel accident investigation, both in-situ investigation, and post-processing analysis. This paper describes an examination of the use of side-scan sonar and multibeam echosounder in-vessel accident investigation. The use of slope feature and edge-detection technique are also investigated concerning the investigation. Results indicate that those acoustic systems can contribute to the inquiry effectively by portraying some underwater objects as the accident suspects. Besides, slope and edge detection methods also produce expectant outcomes to support underwater object detection and investigation.

Mapping seafloor topography of gulf of Guinea using an adaptive meshed gravity-geologic method

An adaptive mesh form of the gravity-geologic method, known as improved Gravity-Geologic Method (iGGM), was implemented on free-air gravity anomalies and shipborne depths to obtain an improved 1′ × 1′ bathymetry model of the Gulf of Guinea (15°W–5°E, 4°S–4°N). An optimal density contrast of 8000 kg/m3 was used for the whole area. The iGGM model compared well with NGDC, ETOPO1, and SIO models; with difference standard deviations and correlation coefficients being 180.20 m, 0.9248, 184.34 m, 0.9551, and 179.84 m, 0.8886, respectively. These prove generally that iGGM is efficient for estimating bathymetry with limited shipborne depths. The influence of shipborne depths quantity and optimal density contrast on bathymetry inversion are analysed, respectively, for the whole region and three subregions (15°W–8°W, 4°S–2°N; 7°W–2°E, 2°S–2°N; and 1°E–5°E, 4°S–0°N). Results showed that, compared with the mountainous areas, higher inversion accuracy (standard deviation of test differences less than 50 m) is achievable in the low-lying region using fewer shipborne depths. With 75% of shipborne depths used for the entire model, the standard deviation of differences between iGGM and shipborne depths at test points was 184.74 m. This indicates that to further improve the region’s bathymetry, more ship sounding is required in the mountainous areas. Numerical results showed different optimal densities should be selected for different areas, especially for the mountainous areas. Using a common density contrast in the whole region may limit the accuracy of the bathymetry inversion.

Метод оценки выраженности артефактов в цифровых батиметрических моделях дна

Разработан метод оценки выраженности артефактов в ЦМР морского дна, который включает в себя метод численной оценки согласованности значений глубин в ЦМР. Метод был апробирован на тесто- вом участке шельфа Баренцева моря. В результате ЦМР GEBCO_08 является более согласованной, чем ЦМР Global Topography на тестовом участке. Стандартное отклонение изменчивости рельефа в пределах выбранного окна в ЦМР GEBCO_08 составляет 5,6 м и 1,6% глубины воды (ГВ), в ЦМР Predicted Topography составляет 8,9 м и 5,4% ГВ. Абсолютный максимум выраженности артефактов в батиметрии ЦМР Predicted Topography достигает 141% ГВ и в ЦМР GEBCO_08‒107% ГВ.

Bathymetry Model Based on Spectral and Spatial Multifeatures of Remote Sensing Image

Multispectral methods for remote sensing image have been widely applied to shallow water bathymetry by researchers. In nonideal conditions, even with the same spectral radiance, the points still have a very wide range of water depths. This means that spectral features alone are insufficient for water bathymetry. Hence, we need to extract other valuable features from a remote sensing image. This letter introduces a spatial feature for water bathymetry using remote sensing images. We propose a model that utilizes a multilayer perceptron (MLP) to integrate the spectral and spatial location features. Experimental results demonstrate that the proposed model yields a substantial performance improvement. The mean relative error is only 8.41%, and the root mean square error is reduced by 34%–68% when compared with three other models. Furthermore, the proposed model addresses well the problems caused by heterogeneous bottom types.

Desarrollo de una interfaz para el cálculo de los niveles de profundidad en cuerpos de agua a través de batimetría (TOLTECA)

Bathymetry is a method of quantifying depths to study the topography of water bodies, including oceans, seas, rivers and lakes. The measurement of bathymetry by means of satellite images is one of the fundamental investigations in the field of remote sensing (RS) of marine environment, which has a lot of applications for the coastal environment and its monitoring. The precise determination of depth water is essential for various purposes, such as the monitoring of underwater topography, the movement of deposited sediments and the production of maritime maps for navigation. Remote sensing allows the bathymetry modeling at spatial scales that are impossible to achieve with traditional methods. Bathymetry can be estimated using RS with several techniques, each with its own capacity for depth detection, accuracy, error, strengths, advantages, disadvantages and the best application environment. Before that, a GUI interface is developed in Matlab that contains enough data to be able to compute the bathymetry in multispectral images from the satellite LANDSAT 8, with the intention of being able to analyze how flooded an area will be.