ASTER GDEM V2的南极冰川高程误差校正及精度分析

ASTER GDEM V2是研究南极冰盖表面的一种重要DEM数据源。由于南极冰雪区反射率高且缺乏地形特征,导致ASTER GDEM V2存在大量的坑、隆起等噪声,难以直接用于南极地形分析。本文以ICESat/GLAS激光点高程数据作为参考,采用修正等高线法对南极伯德（Byrd）冰川ASTER GDEM V2进行了误差校正,并将其与ICESat-1 DEM的垂直精度进行了对比分析。结果表明：ASTER GDEM V2的RMSE由校正前的26.56 m下降到校正后的18.77 m,远低于ICESat-1 DEM的RMSE（121.24 m）;校正后的ASTER GDEM V2高程精度受坡度影响较小,不存在明显的系统误差,而ICESat-1 DEM的高程精度受坡度的影响较大。本研究进一步通过地形剖面分析得到：校正前的ASTER GDEM V2噪声主要分布于高程较低、地形平坦的区域,通过修正等高线的方法可以有效去除这些噪声,去除噪声后的ASTER GDEM V2可作为研究伯德冰川理想的DEM数据源。     

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

守初心耕海探洋七十载担使命披风踏浪砥砺行——中国科学院海洋研究所70年发展纪实

中国科学院海洋研究所是新中国第一个专门从事海洋科学研究的国立科研机构,她的70年光辉历程是我国海洋科技事业从无到有、从弱到强的发展缩影,是新中国海洋科学调查研究自主创新发展历程的真实写照。本文简要介绍中国科学院海洋研究所的主要发展历程,回顾70年来取得的主要科技成就,并围绕新形势下建设海洋大科学研究中心等改革发展举措,讨论和展望研究所的未来发展。     

长江口咸潮入侵变化特征及成因分析

本文基于海洋站潮位观测数据、海平面变化影响调查信息以及长江口水文站径流量数据等,重点分析了2009?2018年长江口咸潮入侵的变化特征及其影响因素,分析结果表明:(1)长江口咸潮入侵季节变化特征明显。咸潮一般从每年的9?10月开始入侵,翌年4?5月结束。3月咸潮入侵次数最多,达12次。2009?2018年,长江口咸潮入侵次数和咸潮持续时间均呈下降趋势,2009年长江口咸潮入侵次数最多,达13次,时间均发生在10月至翌年的4月;咸潮持续时间年际变化较大,2011年咸潮入侵持续时间最长,累计为55 d。2015?2018年,咸潮入侵次数和入侵持续时间均明显减少,2018年没有监测到咸潮入侵过程。(2) 1?4月,长江口处于季节性低海平面期,且同期径流量少,但是受东亚季风影响,持续的增水过程使得增减水?径流量综合影响指数明显偏高,其中1月、2月、3月的影响指数分别为1.5、1.9和1.6,该时段长江口的咸潮入侵过程主要受增减水的影响。5?7月,长江口径流量明显增加,海平面?径流量综合影响指数均小于0,径流的作用强于海水上溯。8月,长江口径流量开始下降,虽然季节海平面较高,但是长江口呈现明显的减水过程,海平面?径流量和增减水?径流量的综合影响指数分别为0.1和?1.6,基本不会发生咸潮入侵。9月,长江口处于季节高海平面期,并且以增水为主,海平面?径流量和增减水?径流量的综合影响指数较大,分别为1.2和1.0,易发生咸潮入侵。10月、11月长江口海平面?径流量的综合影响指数分别为1.5和0.8,径流影响弱于海水上溯,易发生咸潮入侵。(3) 2009?2018年发生的48次咸潮入侵过程有2/3恰逢天文大潮。在某些年份长江口沿海基础海平面偏高,若持续增水恰逢天文大潮,则加剧咸潮入侵的影响程度。     

基于广义回归神经网络的全球表层海水1°×1°二氧化碳分压数据推演

表层海水二氧化碳分压是评估海洋碳源汇强度的关键参数,但其实测数据较少、时空分布极不均匀,导致二氧化碳交换通量的估算有很大的不确定性,海洋源汇特征就不能确切获取。为了解决这个难题,在收集的表层大洋二氧化碳地图(Surface Ocean CO₂ Atlas,SOCAT)实测数据集基础上,运用广义回归神经网络建立二氧化碳分压与经纬度、时间、温度、盐度和叶绿素浓度间的非线性关系,构建了1998?2018年间全球1°×1°经纬度的表层海水二氧化碳分压格点数据,其标准误差为16.93 μatm,平均相对误差为2.97%,优于现有研究中的前反馈神经网络、自组织映射神经网络和机器学习算法等方法。根据构建的数据所绘制的全球表层海水二氧化碳分压的分布与现有研究有较好的一致性。     

Three new species of Anthomedusae (Hydrozoa: Hydroidomedusa) from the Guangdong coastal water, China

The samples of Anthomedusae were collected from the Guangdong coastal water,China.Three new species of Anthomedusae,i.e.Zhangiella condensum Huang,Zhang et Sun,sp.nov.,Hydractinia leizhouensis Huang,Zhang et Yang,sp.nov.,and Cladosarsia simplex Huang,Zhang et Ke,sp.nov.are described.All type specimens are deposited in College of Ocean and Earth Sciences,Xiamen University.     

2012-2016年调水调沙对黄河口海域大型底栖动物群落结构的影响

为了明确黄河调水调沙对河口海域大型底栖动物群落结构的影响,本研究于2012至2016年调水调沙后进行了大型底栖动物样品的采集工作。整个研究时期共鉴定出大型底栖动物7门138种,生物量和丰度2012年显著高于2016年,生物量年间无显著差异;研究时期内优势种以小型多毛类为主,鲜见软体动物、节肢动物和棘皮动物,其中2016年优势种全部为小个体多毛类;MDS显示,随时间的推移距河口不同距离梯度的大型底栖动物逐渐演变为相同的群落结构,且Shannon-Wiener多样性指数和Margalef丰富度指数呈下降趋势;CCA显示研究海域主要底栖动物种类的生态需求为高中值粒径、低溶解氧、pH、黏土和硫化物含量。本研究推测调水调沙工程一定程度上影响了底层生物群落结构,特别是研究海域的A断面。     

Nitrogen fixation driven by mesoscale eddies and the Kuroshio Current in the northern South China Sea and the East China Sea

N₂ fixation rates (NFR, in terms of N) in the northern South China Sea (nSCS) and the East China Sea (ECS) were measured using the acetylene reduction assay in summer and winter, 2009. NFR of the surface water ranged from 1.14 nmol/(L·d) to 10.40 nmol/(L·d) (average at (4.89±3.46) nmol/(L·d), n=11) in summer and 0.74 nmol/(L·d) to 29.45 nmol/(L·d) (average at (7.81±8.50) nmol/(L·d), n=15) in winter. Significant spatio-temporal heterogeneity emerged in our study: the anticyclonic eddies (AE) (P<0.01) and the Kuroshio Current (KC) (P<0.05) performed significantly higher NFR than that in the cyclonic eddies or no-eddy area (CEONE), indicating NFR was profoundly influenced by the physical process of the Kuroshio and mesoscale eddies. The depth-integrated N₂ fixation rates (INF, in terms of N) ranged from 52.4 μmol/(m2·d) to 905.2 μmol/(m2·d) (average at (428.9±305.5) μmol/(m2·d), n=15) in the winter. The contribution of surface NFR to primary production (PP) ranged from 1.7% to 18.5% in the summer, and the mean contribution of INF to new primary production (NPP) in the nSCS and ECS were estimated to be 11.0% and 36.7% in the winter. The contribution of INF to NPP (3.0%–93.9%) also decreased from oligotrophic sea toward the eutrophic waters affected by runoffs or the CEONE. Furthermore, we observed higher contributions compared to previous studies, revealing the vital roles of nitrogen fixation in sustaining the carbon pump of the nSCS and ECS.     

海洋脊椎动物甲状腺系统的研究与应用

甲状腺（Glandula thyreoidea）是海洋脊椎动物体内重要的内分泌腺,从海洋脊椎动物开始,才有了独立的甲状腺结构。海洋脊椎动物的甲状腺一般为实质性的组织。实质由甲状腺滤泡组成,构成滤泡的上皮细胞合成、贮存和分泌的甲状腺激素是调节机体生长发育的关键激素。从海洋脊椎动物开始才有了独立的甲状腺结构。对于动物甲状腺的研究多集中在甲状腺形态及甲状腺与生长发育关系方面,而对海洋脊椎动物的甲状腺的研究则越来越多的集中于环境因素所引起的甲状腺病变方面,环境因素对甲状腺功能的影响也逐渐成为科学研究的重点。海洋水体污染导致的甲状腺机能受损,使海洋脊椎动物不能正常生长发育,数目与种类骤减之时,我们不得不重视对海洋脊椎动物甲状腺的研究。