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为提高我国水下地形地貌探测技术水平,促进对海洋的科学认知和高效开发利用,文章综述高精度和高分辨率水下地形地貌探测技术研发进展,并分析关键技术发展方向。研究结果表明:采用机载激光、多波束、侧扫声呐、浅地层剖面、双频识别声呐、合成孔径声呐和水下三维扫描声呐等探测技术以及无人船、水下机器人和海底观测网等探测平台,可获取高精度和高分辨率水下地形地貌信息;应在提高设备性能、减小探测误差和完善数据算法等方面加大研究力度,重点发展综合探测技术,从而全面和清晰地反映水下地形地貌。 相似文献
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相位差测深声呐(Phase Differencing Bathymetric Sonar,PDBS),也被称作干涉式声呐(Interferometric Sonar),可以同步采集水深点云数据和双频侧扫声呐图像,完全适用于大范围的近海人工鱼礁探测。本文采用基于PDBS原理的Edge Tech 6205地形地貌一体化测量设备对莱州湾某海域海洋牧场投礁区进行全覆盖探测,获取了高精度水深数据以及双频侧扫声呐图像。对水深数据进行地形特征变量计算,精细刻画了研究区的微地形地貌特征,并结合侧扫声呐图像通过多数据融合实现了对鱼礁边界的精准识别。在此基础上利用地理信息系统中的空间分析方法对人工鱼礁的水下物理参数进行计算和统计,并探讨了研究区地形地貌的成因及其演化模式,最后论证了基于PDBS的近海人工鱼礁探测技术具有高效率、低成本、高精度等诸多优势。研究结果表明,研究区水深介于4.1~7.3 m,鱼礁分布区有较大的海底起伏且在礁体周围存在明显的沉降和冲刷现象;鱼礁总占地面积约占研究区的14.04%,总空方量共计2 528.22 m3,鱼礁高度介于1.26~3.63 m且呈正态分布。本研究为近海人工鱼礁探测提供了数据和技术支撑,具有较强的实践意义。 相似文献
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在系统收集和分析南海海底冷泉资料基础上,应用浅剖和多波束水体影像技术识别海底冷泉,结合地质条件综合研究南海冷泉分布特征,进而分析探讨其油气地质意义。研究结果表明,南海冷泉分布广泛,神狐、东沙西南部、东沙东北部、琼东南、西沙海槽、南沙南部和越南沿岸等海域均发现冷泉,冷泉分布水深为200~3 000m。海底冷泉与深部油气乃至浅层天然气水合物资源有着密切的成因联系。冷泉及其伴生物(冷泉碳酸盐岩)的探测与识别对海洋油气勘探,尤其是天然气水合物勘查的指示作用明显。浅剖和多波束水体影像技术不仅可以探测和识别冷泉,而且两者结合可实现低成本、高效率的海底地质异常体(冷泉碳酸盐岩、泥底辟及气烟囱等)的声学异常探测,极大地提高了海洋油气勘探及天然气水合物勘查的成功率。 相似文献
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针对海底地形复杂程度分类问题,在考虑传统水深均值的基础上引入坡度和起伏度两个地形因子作为表征海底地形复杂程度的分类指标并进行量化,对水深数据空间分辨率进行统一,建立包含18种典型海底特征的海底地形复杂度分类库,利用BP神经网络对建立的分类库进行训练学习。为验证该方法的有效性和适用性,选取地形复杂度不同的4块实验区分别采用统计学方法和BP神经网络算法进行海底地形复杂度进行分类,对比发现该方法可以实现海区海底平坦、一般、复杂三种地形的自动识别与分类,并保留实验区海底地形复杂度细节信息。 相似文献
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针对目前"数字海底"建设中存在海底调查数据集成管理与三维可视化表达不足等问题,本文采用GIS技术,以黄河水下三角洲埕北海域为研究对象,利用地理空间数据集成理论与三维建模方法,建立了埕北海域三维海底空间数据库,实现了研究区域地形数据、地层数据、钻孔数据、表层沉积物数据的有效组织管理与可视化,并在此基础上,采用ArcGIS Engine 10.0,结合.NET平台,在Visual Studio 2010开发环境下,利用C#语言进行了二次开发,实现了基于C/S (Client/Server)架构的三维海底虚拟仿真系统的开发,设计了一套面向埕北海域的三维海底虚拟仿真原型系统。 相似文献
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T. Bekkby H.C. Nilsson F. Olsgard B. Rygg P.E. Isachsen M. Isus 《Estuarine, Coastal and Shelf Science》2008,79(4):631-636
Macrofauna composition and diversity in soft sediments are commonly used as “health indicators” in various pollution monitoring programmes worldwide. Hence, finding a modelling method for predicting the presence of soft sediments and enable production of digital maps of where soft sediments are likely to be found would be valuable for developing a cost-effective sampling design. This study presents a first-generation model that can predict where to find soft sediments in coastal areas with a complex topography and a mosaic of seabed habitat types. We used geophysical data that were quantitative, objectively defined (through GIS modelling) and integrated over time. We analysed, using a Generalised Additive Model (GAM) and the model-selection approach Akaike Information Criterion (AIC), the influence of in-situ measured depth and GIS-modelled terrain structures, wave exposure and current speed on the distribution of soft sediment measured using a Sediment Profile Image (SPI) camera. Our analyses showed that the probability of finding soft sediment was best determined by depth, terrain curvature and median current speed at the seafloor. These predictors were used to develop a spatial predictive GIS-model/-map (for parts of Skagerrak, Norway, with a spatial resolution of 25 m × 25 m) of the probability of soft seabed occurrence. 相似文献
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David C. Mosher 《Marine Geophysical Researches》2011,32(1-2):25-35
Most modern submarine geohazard investigations rely heavily on multibeam sonar data, yet there are limitations to these data that must be respected. Disregard of fundamental aspects of spatial sampling, averaging and interpolation, and statistical parameters that accompany all forms of measurement, can lead to over-interpretation of data. Beam spreading and sounding density govern spatial resolution and therefore limit seafloor features that are resolved and interpreted as indicative of geohazards. These resolution limitations are shown with a synthetic model of the seafloor convolved with a spherically spreading wavefront approximated with a spherical smoothing algorithm. This simulation shows the inability to resolve metrics of objects, as well as determine critical parameters such as slope angles with increasing water depth. As well, real case examples are presented showing these effects on identification of targets, slope angles and pockmarks. Misinterpretation of seafloor features is common in multibeam data, particularly without the benefit of coincident subbottom data. Thus it is critical to image the third dimension below the seafloor. Finally, seafloor mapping for geohazards is just one step in a geohazard assessment: it is critical to know frequency of recurrence of geohazard events and their modern geologic context in order to appropriately assess risk. 相似文献
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Scheirer Daniel S. Fornari Daniel J. Humphris Susan E. Lerner Steven 《Marine Geophysical Researches》2000,21(1-2):121-142
High-resolution, side-looking sonar data collected near the seafloor (100 m altitude) provide important structural and topographic information for defining the geological history and current tectonic framework of seafloor terrains. DSL-120 kHz sonar data collected in the rift valley of the Lucky Strike segment of the Mid-Atlantic Ridge near 37° N provide the ability to quantitatively assess the effective resolution limits of both the sidescan imagery and the computed phase-bathymetry of this sonar system. While the theoretical, vertical and horizontal pixel resolutions of the DSL-120 system are <1 m, statistical analysis of DSL-120 sonar data collected from the Lucky Strike segment indicates that the effective spatial resolution of features is 1–2 m for sidescan imagery and 4 m for phase-bathymetry in the seafloor terrain of the Mid-Atlantic Ridge rift valley. Comparison of multibeam bathymetry data collected at the sea-surface with deep-tow DSL-120 bathymetry indicates that depth differences are on the order of the resolution of the multibeam system (10–30 m). Much of this residual can be accounted for by navigational mismatches and the higher resolving ability of the DSL-120 data, which has a bathymetric footprint on the seafloor that is 20 times smaller than that of hull-mounted multibeam at these seafloor depths (2000 m). Comparison of DSL-120 bathymetry with itself on crossing lines indicates that residual depth values are ±20 m, with much of that variation being accounted for by navigational errors. A DSL-120 survey conducted in 1998 on the Juan de Fuca Ridge with better navigation and less complex seafloor terrain had residual depth values half those of the Lucky Strike survey. The quality of the bathymetry data varies as a function of position within the swath, with poorer data directly beneath the tow vehicle and also towards the swath edges.Variations in sidescan amplitude observed across the rift valley and on Lucky Strike Seamount correlate well with changes in seafloor roughness caused by transitions from sedimented seafloor to bare rock outcrops. Distinct changes in sonar backscatter amplitude were also observed between areas covered with hydrothermal pavement that grade into lava flows and the collapsed surface of the lava lake in the summit depression of Lucky Strike Seamount. Small features on the seafloor, including volcanic constructional features (e.g., small cones, haystacks, fissures and collapse features) and hydrothermal vent chimneys or mounds taller than 2 m and greater than 9 m2 in surface area, can easily be resolved and mapped using this system. These features at Lucky Strike have been confirmed visually using the submersible Alvin, the remotely operated vehicle Jason, and the towed optical/acoustic mapping system Argo II. 相似文献