中分辨率成像光谱仪数据的滩涂环境遥感应用能力研究

以长江口海岸带地区为示范区，探讨了我国中分辨率成像光谱仪(CMODIS)的滩涂及水体图像特征。结合地面现场观测和图像处理结果，评价了其在滩涂环境遥感中的应用能力。     

变性绕极深层水入侵时南极普里兹湾湍流混合特征研究

基于中国第28、29和31次南极科学考察中的CTD数据,利用Thorpe尺度方法计算了普里兹湾及其附近海域湍动能耗散率,分析了其分布特征,并对当地的水团结构进行研究.结果表明,普里兹湾及其附近海域中,前两个航次观测中次表层湍动能耗散率强度在陆架坡折区域达到最大.在水团分布方面,在第28和29航次中均观测到了变性绕极深层...     

基于云存储技术的海岛信息管理和 展示平台设计与实现

随着海岛遥感影像数据的不断积累,传统数据存储管理方法越来越难以满足需求。针对上述问题,利用云存储技术对海岛影像数据进行分块组织,建立分布式海岛影像数据集,并在优化数据存储的同时,设计了一套海岛信息多形式展示平台。实现了信息检索、数据传输与审核、分析评价、成果展示和共享等功能。     

基于观测的南海西沙海域深层近惯性振荡特征分析

近惯性内波运动普遍存在于全球大洋中,影响大洋中的质量、动量和能量输送,是大气强迫与海洋混合之间的重要纽带。由于目前海洋深层观测资料的缺乏,对于深层近惯性内波生消演变特征研究甚少。利用2009-2012年的潜标观测资料,采用带通滤波和谱分析方法研究了南海西沙海域深层近惯性内波生成、传播和消亡等演变特征。通过研究发现,南海西沙海域深层存在较强的近惯性振荡,其生成源为台风过境能量输入,绝大部分时段内,近惯性振荡能量在海洋浅层耗散,不向海洋深层传播;仅在少部分时段内,近惯性振荡能量的80%～85%耗散在500 m以浅区域,有大概15%～20%继续向海洋深层传播。     

基于融合U-Net及ConvLSTM的海面高度异常预报方法研究

海面高度异常是反映海洋环境状况的主要变量之一。本文使用1993—2019年的融合月均海面高度异常数据,建立了基于深度学习的海面高度异常预测神经网络模型,提出了基于融合U型网络(U-Net)和卷积长短记忆网络(ConvLSTM)的中长期海面高度异常预报模型。在研究海域0.25°×0.25°的空间分辨率下,模型测试集预报结果的均方根误差和平均绝对误差分别为0.039 m和0.027 m,均优于全连接LSTM预报模型和ConvLSTM+CNN预报模型,为大中尺度的海面高度异常预报提供了新的方法。     

基于深度学习的赤潮发生预报方法研究

赤潮作为海洋灾害,对海洋渔业、生态、经济,以及人类生产、生活造成了严重影响。一直以来,赤潮受到研究者的广泛关注,但由于它的形成机制比较复杂,使得赤潮预报极具挑战性。针对赤潮预报的研究问题,本文收集了厦门海域赤潮发生前后的海洋监测数据,结合皮尔逊相关系数、散布矩阵、复相关系数方法,分析多环境因子与赤潮发生多要素的关联情况,重点采用基于深度学习的LSTM与CNN融合方法,挖掘环境因子的时序依赖,发现序列数据的局部特征,对赤潮发生进行预报。在厦门一号和厦门二号数据集中,本方法在预报未来12 h内的赤潮情况时,RMSE、MAE误差分别达到0.521 8、0.504 3。通过协同对比模型进一步确定赤潮发生的预报概率,在两个数据集上的最终预报准确率分别为67.58%和63.49%。本研究为赤潮的分析预报提供了探索经验,证明了将深度学习方法应用于赤潮预报的可行性。     

Macrobenthic infaunal communities associated with deep‐sea hydrocarbon seeps in the northern Gulf of Mexico

There are thousands of seeps in the deep ocean worldwide; however, many questions remain about their contributions to global biodiversity and the surrounding deep‐sea environment. In addition to being globally distributed, seeps provide several benefits to humans such as unique habitats, organisms with novel genes, and carbon regulation. The purpose of this study is to determine whether there are unique seep macrobenthic assemblages, by comparing seep and nonseep environments, different seep habitats, and seeps at different depths and locations. Infaunal community composition, diversity, and abundance were examined between seep and nonseep background environments and among three seep habitats (i.e., microbial mats, tubeworms, and soft‐bottom seeps). Abundances were higher at seep sites compared to background areas. Abundance and diversity also differed among microbial mat, tubeworm, and soft‐bottom seep habitats. Although seeps contained different macrobenthic assemblages than nonseep areas, infaunal communities were also generally unique for each seep. Variability was 75% greater within communities near seeps compared to communities in background areas. Thus, high variability in community structure characterized seep communities rather than specific taxa. The lack of similarity among seep sites supports the idea that there are no specific infauna that can be used as indicators of seepage throughout the northern Gulf of Mexico, at least at higher taxonomic levels.     

基于地学信息图谱的河道、海岸线演变对黄河三角洲景观格局影响研究

本文利用1988、1998、2009和2016年四期遥感影像,运用GIS技术,将地学信息图谱的图形思维与景观生态学的定量思维相结合,以距今不同时期的亚三角洲和滨海湿地为研究区,从景观结构和景观演替两个方面探究黄河三角洲河道、海岸线演变对景观格局的影响。结果表明:(1)距今不同时间的河道对黄河三角洲景观结构的影响程度不同,距今时间越长的亚三角洲研究区内耕地占总面积的比例越大且耕地是亚三角洲研究区中的第一优势景观类型。在1855—1889亚三角洲研究区内,除耕地和建筑用地外,其他各类景观占总面积的比例都较小且随时间变化不明显;在1929—1934亚三角洲研究区内,盐田、养殖池占总面积的比例从2009年到2016年增加了近40%,涨幅明显;在1964—1976亚三角洲研究区内,各类景观占总面积的比例趋于平均;在2017至今的亚三角洲研究区内,耕地和光滩占总面积的比例较高,达到24%左右。(2)距今不同时间的海岸线对黄河三角洲景观结构的影响程度也不同,在1855滨海湿地研究区内,耕地占总面积比例为60%左右,而海域占总面积比例接近于0,极差较大;在1934和1974滨海湿地研究区内,光滩、柽柳、碱蓬群落、芦苇、白茅群落占总面积比例随时间变化几乎呈逐渐下降趋势,而建筑用地和盐田、养殖池则呈逐渐上升趋势;2009滨海湿地研究区,河流、人工水域占总面积比例在2009年和2016年均达到32%以上。(3)根据景观类型重心变化特征,分析河道、海岸线演变对景观演替的影响程度,将不同时期亚三角洲和滨海湿地研究区景观演替分为如下几类:亚三角洲人类活动主导型、废弃河道主导型、行水河道主导型、滨海湿地人类活动主导型、废弃海岸主导型、新海岸主导型。     

基于ArcGIS Engine与ArcGIS Server的海域定级信息管理系统设计与开发

以Visual Studio 2012为平台,利用ArcGIS Engine强大的空间分析功能,以C#为开发语言结合第三方插件设计开发海域定级决策子系统,实现了不同用海方式海域的自动化定级,对海域定级基础数据、过程数据和结果数据进行综合管理,构建了一个具有一定实用价值的海域定级信息管理系统原型;此外,利用WebGIS将海域定级决策子系统分析生成的结果数据发布成服务,实现海域定级信息共享子系统。本研究为海域定级提供智能化平台,提高对海域定级及评估效率,有利于海洋可持续发展。     

西太平洋深海海水中乙醛降解菌多样性及群落结构研究

As a major aldehyde pollutant widely existing in industry and our daily life, acetaldehyde is more and more harmful to human health. As characteristic habitat niche, bacteria from deep sea environments are abundant and distinctive in heredity, physiology and ecological functions. Thus, the development of acetaldehyde-degrading bacteria from deep sea provides a new method to harness acetaldehyde pollutant. Firstly, in this study,acetaldehyde-degrading bacteria in the deep sea water of the West Pacific Ocean were enriched in situ and in the laboratory respectively, and then the diversity of uncultured bacteria was studied by using 16 S r RNA genes. Then acetaldehyde-degrading strains were isolated from two samples, including enrichment in situ and enrichment in laboratory samples of deep sea water from the West Pacific Ocean using acetaldehyde as the sole carbon source,and then the ability of acetaldehyde degradation was detected. Our results showed that the main uncultured bacteria of two samples with different enrichment approaches were similar, including Proteobacteria,Actinobacteria, Firmicutes, Cyanobacteria, but the structure of bacterial community were significant different.Four subgroups, α, γ, δ and ε, were found in Proteobacteria group. The γ-Proteobacteria was dominant(63.5%clones in laboratory enriched sample, 75% clones in situ enriched sample). The species belonged to γ-Proteobacteria and their proportion was nearly identical between the two enrichment samples, and Vibrio was the predominant genus(45% in laboratory enriched sample, 48.5% in situ enriched sample), followed by Halomonas(9% in situ enriched sample) and Streptococcus(6% in laboratory enriched sample). A total of 12 acetaldehyde-degrading strains were isolated from the two samples, which belonged to Vibrio, Halomonas,Pseudoalteromonas, Pseudomonas and Bacillus of γ-Proteobacteria. Strains ACH-L-5, ACH-L-8 and ACH-S-12,belonging to Vibrio and Halomonas, have strong ability of acetaldehyde degradation, which could tolerate 1.5 g/L acetaldehyde and degrade 350 mg/L acetaldehyde within 24 hours. Our results indicated that bacteria of γ-Proteobacteria may play an important role in carbon cycle of deep sea environments, especial the bacteria belonging to Vibrio and Halomonas and these strains was suggested for their potentials in government of aldehyde pollutants.