基于散射计风场数据的台风强度诊断方法——以海洋二号卫星数据为例

本文提出了一种基于散射计风场数据的台风定强方法。该方法定义了台风所在海区的一个圆形区域上的风速平均值来对台风进行定强,并使用海洋二号卫星散射计历史数据对该方法进行了验证。验证结果表明,该台风定强方法可以克服散射计反演台风风速过低的问题。与台风强度监测的历史记录比较的结果显示,在台风强度低于"强台风"这一强度等级时,该方法能够有效估算台风强度。     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.     

江河入海流量在线监测不确定度评估方法研究与应用

鉴于国内目前缺少流量在线监测不确定性评估方面的研究,针对江河入海流量在线监测过程中可能产生的各种不确定性,本文采用不确定度概念对不确定性进行评估,给出了不确定度的主要来源、各来源不确定度的评估方法,以及江河入海流量在线监测总不确定度评估模型,并应用该模型对辽河入海流量在线监测的不确定度进行了评估。     

海洋空间规划管控平台建设的总结思考

新时期国家着力构建陆海统筹、区域统筹、城乡统筹的国土空间规划体系,为更好的服务国土空间规划体系与海岸带专项规划的建立实施,满足新形势下海域海岛管理的新要求,深化落实主体功能区制度,本文对已经建立的海洋空间规划管控平台进行了总结。海洋空间规划管控平台主要目标是实现海洋空间“一张图”、海洋主体功能区监测评估、海洋空间综合决策,主要功能包括多规分析与一张图、海洋主体功能区监测评估、海洋空间分区辅助编制与审查、海洋空间符合性判断等.     

基于卫星测高数据的萨德湿地水位变化研究

以萨德湿地为例,使用ENVISAT和Jason2卫星测高数据利用改进的阈值法进行回波重定,反演萨德湿地水位。结果显示:萨德湿地的恒定水域水位变化规律。通过对比萨德湿地和维多利亚湖的水位变化可以发现,维多利亚湖对萨德湿地南部水域水位有巨大的影响,且影响与人类活动(尤其是欧文瀑布大坝的水能发电)有很大的关系,而位于大坝下游的阿尔伯特湖水位变化和萨德湿地南部水域水位变化有很强的相关性。     

地理国情监测成果在农业、旅游领域中的应用

开展地理国情监测工作的目的是为了获取自然与人类社会经济活动引起的地表变化信息,具体包括地表自然要素、人文地理要素和社会经济信息的空间分布特征及其相互关系,是基本国情的重要组成部分,为政府管理决策、企业生产运营、人民群众生活提供数据基础和决策依据。本文基于地理国情监测数据,结合多种测绘地理信息数据和技术手段,探讨如何利用地理国情监测成果促进农业与旅游业的发展,以期深入挖掘和提升监测成果价值,全面拓展监测成果应用服务的新思路、新方向。     

新型移动三维激光扫描技术在盾构管片椭圆度检测中的应用

铁运营阶段对隧道结构的变形监测保证了地铁运行的安全,而椭圆度检测是地铁隧道结构检测的重要工作。本文简单介绍了传统椭圆度检测的基本方法,分析了新型移动三维激光扫描检测系统基本原理及隧道椭圆度检测的方法和处理流程。通过工程案例实际应用以及对检测结果的综合分析,证明了移动三维激光扫描技术在盾构管片椭圆度检测中的优势。     

地灾监测的大数据信息平台研究及应用

重点对地灾监测方面的方案研究进行了阐述,在构建大数据信息平台的设计方案时,以实现高度自动化的全方位监测功能为导向,依托导航卫星数据接收机和多源传感器,集成构建大数据信息平台的系统解决方案,主要包括扼流圈卫星天线、GNSS数据接收机、MEMS传感器、环境测量单元、防雷区域单元等功能元件的组成、多传感器的系统集成,以及全方位监测的功能实现。按照地灾监测大数据信息平台建设、构建大数据平台关键技术突破及检测数据解算软件功能实现的顺序,完成了GNSS实时监测预警应用网络系统HCmonitor的研发。综合应用多种手段实现地灾监测的功能升级,为解决重大灾害预警提供了新的思路和解决方案,该项成果在甘肃舟曲的灾后重建工程得到应用与推广。     

差分层析SAR技术研究现状分析

差分层析SAR是在层析SAR基础上发展起来的一种四维信息反演技术。它不仅实现了对雷达目标的三维分辨能力,同时可以获取目标的形变速率信息,可实现对目标方位-距离-高度-时间四维成像,这对实现城市基础设施动态形变监测、古建筑风险评估、重要工程安全监测等应用具有重要实际意义和价值。本文基于差分层析SAR成像原理,分析了成像处理过程中存在的问题,总结了差分层析SAR成像算法研究现状和特点;最后列举了差分层析SAR技术的主要应用领域,并对其技术发展趋势进行了展望。     

River centerline extraction using the multiple direction integration algorithm for mixed and pure water pixels

The river centerline is a basic hydrological characteristic. Most prior studies have used remote sensing data to extract the river centerline from the open water region in a pure water pixel region. Extracting this type of river is relatively easy. However, extracting the centerline of a micro-river, which is mainly composed of mixed water pixels, is challenging. This paper presents a novel method, called the Multiple Direction Integration Algorithm (MDIA), to extract the river centerline using an image-enhancing method combined with river morphology. MDIA can be applied to regions mainly composed of pure water pixels, as well as to regions consisting of mixed water pixels in the index image. The method first calculates the normalized difference vegetation index (NDVI) and enhances the river linear structure using a Hessian matrix. Second, a small window is constructed as a circular structural element. In the window region, the local threshold is automatically obtained using water-oriented clustering segmentation and prior river knowledge to judge the pixel type. After completing the river centerline extraction in the current window, the next detecting window is generated to continue judgment. The structural element automatically executes river centerline judgment until the entire river centerline is extracted. The Landsat 8 images of six regions with different geomorphologies were chosen to analyze the method’s performance. The test sites include high mountain region, low mountain region, plains region with farmland and a residential region. The experimental results show that the optimal threshold of the processing results ranged from 0.2 to 0.3. In this range, the user’s accuracy is 0.813 to 0.997, and the producer’s accuracy is 0.981 to 1. The MDIA effectively and correctly extracts the river network in mixed-pixel regions. The presented method provides an effective algorithm for river centerline extraction that can be used to expand and update river datasets and provide reliable river centerline data for relevant hydrology studies.