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.     

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。     

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。     

4种再分析月降水数据在内蒙古地区的适用性分析

利用1981—2020年气象台站的实测降水数据,对CRA40、ERA5、JRA55和MERRA2这4种再分析月降水数据在内蒙古地区的降水分布特征,与实测降水的相关性和误差进行分析。结果表明：(1)内蒙古地区4种再分析降水数据的空间分布与台站降水基本一致,误差分析表明CRA40与MERRA2的数据质量较高,ERA5次之,而JRA55数据质量相对较差。(2)CRA40和MERRA2在1983—1986年存在明显的降水低估,ERA5在2005年之后的内蒙古中东部出现明显的降水低估,JRA55在115°E以东存在明显降水高估,在115°E以西则以降水低估为主。(3)4种再分析月降水数据的年内最大均方根误差和绝对误差均集中在6—8月,与台站降水相关系数的年内最小值均出现在7月,内蒙古夏季汛期是再分析降水误差产生的主要时段。     

东莞南城区能源厂组合式挡土墙失稳分析及处理措施

挡土墙病害和破坏形式主要有:滑移、倾覆、墙身开裂等,并且主要考虑一级或单级挡墙的破坏。本文通过对东莞南城区能源厂重叠式组合挡土墙失稳观察,提出其破坏形式除了一般挡土墙具有的常见病害倾覆之外,还伴随有该类挡土墙特有的灾害流土的发生,本文从定量、定性两方面对该失稳挡墙进行了具体分析,最后,根据分析结果对该挡墙提出了具有针对性的处理措施。通过对该挡土墙的分析总结,为今后该类挡土墙的设计、施工提出了极具借鉴价值的建议。     

简介加利福尼亚理工学院建筑结构健康状态的实时监测和性能评估系统

介绍了加利福尼亚理工学院建筑结构健康状态的实时监测和性能评估系统近年来的发展。该系统安装在帕斯迪纳市的加利福尼亚理工学院校园里的米利肯图书馆内。它通过互联网向全世界提供真实的实时数据。