Ecological classification of European transitional waters in the North-East Atlantic eco-region

A new methodology to classify European North-East Atlantic transitional waters into ecological types has been developed based on the most important hydrological and morphological features that are likely to determine the ecology of aquatic systems in transitional waters. Hydrological indicators help identifying if a transitional water area is dominated by fresh or sea water and/or by intertidal or subtidal areas, while morphological indicators allow an estimation of the complexity of the transitional water and the diversity of the habitats involved. Twelve transitional waters of the southern Bay of Biscay were classified using this methodology and the five hydro-morphological types obtained were validated with benthic macro-invertebrate data. Transitional waters with a complex morphology showed the highest values of species diversity, while those with a smaller tidal influence showed lower species diversity. The ‘Scrobicularia’ and ‘Abra’ assemblages, previously identified in the study area, were found to be related to different types of transitional waters. The ‘Abra’ assemblage only appeared in estuaries with a complex morphology and dominated by tidal influences, while the ‘Scrobicularia’ assemblage was detected in all the transitional waters except for a single coastal lagoon. This classification of transitional waters may therefore be useful to establish the biological reference conditions needed for European Directives.     

Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: A case study within a Basque estuary

The bathymetric LiDAR system is an airborne laser that detects sea bottom at high vertical and horizontal resolutions in shallow coastal waters. This study assesses the capabilities of the airborne bathymetric LiDAR sensor (Hawk Eye system) for coastal habitat mapping in the Oka estuary (within the Biosphere Reserve of Urdaibai, SE Bay of Biscay, northern Spain), where water conditions are moderately turbid. Three specific objectives were addressed: 1) to assess the data quality of the Hawk Eye LiDAR, both for terrestrial and subtidal zones, in terms of height measurement density, coverage, and vertical accuracy; 2) to compare bathymetric LiDAR with a ship-borne multibeam echosounder (MBES) for different bottom types and depth ranges; and 3) to test the discrimination potential of LiDAR height and reflectance information, together with multi-spectral imagery (three visible and near infrared bands), for the classification of 22 salt marsh and rocky shore habitats, covering supralittoral, intertidal and subtidal zones. The bathymetric LiDAR Hawk Eye data enabled the generation of a digital elevation model (DEM) of the Oka estuary, at 2 m of horizontal spatial resolution in the terrestrial zone (with a vertical accuracy of 0.15 m) and at 4 m within the subtidal, extending a water depth of 21 m. Data gaps occurred in 14.4% of the area surveyed with the LiDAR (13.69 km²). Comparison of the LiDAR system and the MBES showed no significant mean difference in depth. However, the Root Mean Square error of the former was high (0.84 m), especially concentrated upon rocky (0.55–1.77 m) rather than in sediment bottoms (0.38–0.62 m). The potential of LiDAR topographic variables and reflectance alone for discriminating 15 intertidal and submerged habitats was low (with overall classification accuracy between 52.4 and 65.4%). In particular, reflectance retrieved for this case study has been found to be not particularly useful for classification purposes. The combination of the LiDAR-based DEM and derived topographical features with the near infrared and visible bands has permitted the mapping of 22 supralittoral, intertidal and subtidal habitats of the Oka estuary, with high overall classification accuracies of between 84.5% and 92.1%, using the maximum likelihood algorithm. The airborne bathymetric Hawk Eye LiDAR, although somewhat limited by water turbidity and wave breaking, provides unique height information obscured from topographic LiDAR and acoustic systems, together with an improvement of the habitat mapping reliability in the complex and dynamic coastal fringe.     

山东海域海岛地质遗迹资源综合研究

地质遗迹是在地球演化的漫长历史时期,由内、外地质动力共同作用形成的不可再生的自然遗产,海域海岛地质遗迹因依托特有的海洋环境更显瑰丽和珍贵,对建设海洋强国也更具资源价值。为给海洋资源管理提供技术支撑,文章以《地质遗迹调查规范（DZ/T0303-2017）》“地质遗迹分类”为基础,结合地质条件、遗迹特点和地域分布,将山东省海域划分为滨洲—潍坊海域和烟台—日照海域两区,按海水与岛陆位置关系划分出岛陆、岸线潮间带和岸岛水下三带,在两区三带内按搬运-沉积类、构造-剥蚀类和地质体-地质构造类三大成因类型进行分区、分类综合研究,对遗迹成因进行分析,对重要遗迹资源作了重点介绍,并根据资源保护现状与存在问题,提出完善源法规体系和保护机制、建立信息与预警系统平台、加强宣传、进行监测、采取必要工程措施等严格保护建议,同时提出促进旅游业发展、开展地学科普、助推社会文明和生态文明建设、助力对外交流等利用方向。专门针对省域海域海岛地质遗迹进行综合研究在全国尚属首次,对科学管理和充分利用海域海岛优势生态资源具有重要意义。     

用于海底目标识别与底质分类的多波束水体波形预处理

多波束水体数据是多波束系统获取的最原始数据,记录了波束从发射到接收整个过程全部的反向散射强度信息,可以为目标识别、水下栖息环境探测等提供重要的数据支撑.目前,针对多波束水体强度时间序列所表现的波形信息的处理及研究仍处于起步阶段,另外水体波形数据易受噪声影响,且存在明显的入射角效应问题,对此,本文提出了一种基于分区异构的...     

一种基于分割图斑的海岸带遥感图像分类方法

传统的基于象元的分类方法在处理海岸带这类动态多变、混杂度大的地物时常出现“椒盐现象”,难以矢量化形成专题图。提出了一种新的遥感图像分类方法——基于分割图斑的分类法,即选择一个合适的尺度,利用光谱信息按照一定的策略将图像分割为一系列的图斑,并确保图斑内大多数象元的光谱特征相近,分别对图斑内诸象元进行统计,求出各个波段的均值,用该均值替换图斑内所有象元的原始亮度值,这样分类时可以确保同一图斑内的所有象元被分到同一个类别中,从而有效地避免了“椒盐现象”,使分类结果便于矢量化成图,也便于对特定地物的提取。实验结果表明,该方法还能在一定程度上提高分类精度。     

Physical characterisation and a biologically focused classification of “seamounts” in the New Zealand region

The physical, biological, and oceano‐graphic characteristics of seamounts of the New Zealand region of the South Pacific Ocean are poorly known. The aim of this study was to present a synopsis of the physical characteristics of seamounts within the region, and to present a preliminary classification using biologically meaningful variables. Data for up to 16 environmental variables were collated and used to describe the distribution and characteristics of the c. 800 known seamounts in the New Zealand region. Seamounts span a wide range of sizes, depths, elevation, geological associations and origins, and occur over the latitudinal range of the region, lying in different water masses of varying productivity, and both near shore and off shore. As such, it was difficult to generally describe New Zealand seamounts, as there is no “typical” feature. Thirteen environmental variables were included in a multivariate cluster analysis to identify 12 seamount similarity groupings, for a subset of over half the known seamounts. The groupings generally displayed an appreciable geographic distribution throughout the region, and were largely characterised by a combination of four variables (depth at peak, depth at base, elevation, and distance from continental shelf). In the future, the findings of the present study can be tested to determine the validity and usefulness of the approach for directing future biodiversity research and informing management of seamount habitat.     

Retracking of Jason-1 Data

We present the results of retracking 18 cycles (15 from the Jason-TOPEX collinear period) of Jason-1 data. We used the retracking method of Rodriguez which simultaneously solves for all relevant waveform parameters using a 26 Gaussian model of the altimeter point target response. We find significant differences from the Jason-1 Project retracking in the key parameters of range and significant wave height (SWH) in the second version of the Project SGDRs. The differences from the Jason-1 data have a strong dependence on off-nadir angle and some dependence on SWH. The dependence of range on SWH is what is called sea state bias. The retracking technique also estimates surface skewness. For Jason-1 with its very clean waveforms we make the first direct estimates of the skewness effect on altimeter data. We believe that the differences found here and thus in overall sea surface height are the result of the standard project processing using a single Gaussian approximation to the Point Target Response (PTR) and not solving simultaneously for off nadir angle. We believe that the relatively large sea state bias errors estimated empirically for Jason-1 during the cal/val phase result from sensitivity of quantities, particularly SWH, in project GDRs to off nadir angle. The TOPEX-Jason-1 bias can be determined only when a full retracking of Jason-1 is done for the collinear period.     

Seafloor Classification of Multibeam Sonar Data Using Neural Network Approach

In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method.     

Optimizing Remote Sensing and GIS Tools for Mapping and Managing the Distribution of an Invasive Mangrove (Rhizophora mangle) on South Molokai,Hawaii

In 1902, the Florida red mangrove, Rhizophora mangle L., was introduced to the island of Molokai, Hawaii, and has since colonized nearly 25% of the south coast shoreline. By classifying three kinds of remote sensing imagery, we compared abilities to detect invasive mangrove distributions and to discriminate mangroves from surrounding terrestrial vegetation. Using three analytical techniques, we compared mangrove mapping accuracy for various sensor-technique combinations. ANOVA of accuracy assessments demonstrated significant differences among techniques, but no significant differences among the three sensors. We summarize advantages and disadvantages of each sensor and technique for mapping mangrove distributions in tropical coastal environments.     

中国热带6种海参骨片的种类和形态研究

利用扫描电子显微镜对我国6种热带海参(蛇目白尼参、玉足海参、花刺参、梅花参、子安辐肛参和巨梅花参)背脊部骨片的组成和结构进行了观察。结果表明,蛇目白尼参骨片有3种类型的花纹样体和1种杆状体;玉足海参骨片有2种类型的桌形体和1种扣形体;花刺参骨片有2种类型的桌形体、1种C形体和1种花纹样体;梅花参骨片有4种类型的杆状体;子安辐肛参骨片有1种花纹样体;巨梅花参骨片有1种杆状体、1种拟桌形体和1种颗粒体。结果显示,与之前学者光镜下观察的结果存在差异,玉足海参桌形体底盘中央是单孔而非4孔;花刺参桌形体立柱之间没有横梁连接。并发现了新的骨片类型:蛇目白尼参Ⅲ型花纹样体和杆状体;玉足海参顶部周缘小孔桌形体;花刺参顶部5簇小齿桌形体;梅花参Ⅱ型、Ⅲ型、Ⅳ型杆状体。