准实时地震灾情综合评估系统的研发

震后如何快速获取灾区震情信息、准确评估地震灾情,是震后应急救援的关键问题。本研究从县市地震灾害应急救援需求出发,开发了准实时地震灾情综合评估系统,基于MEMS强震台网的强震观测数据、县域承灾体基础数据和手机终端获取的震后地震现场实时灾情信息,综合采用承灾体地震易损性分析方法和灾情动态修正算法,实现了县市地震灾区灾情准实时评估,为灾区地震应急指挥、救援和辅助决策提供科学依据。     

基于手机位置数据的四川九寨沟7.0级地震人流分析

2017年8月8日四川九寨沟7.0级震后,浙江省地震局利用大数据采集了1031.99万条手机位置记录和4.46万个空间格网位置。本文结合24hr连续定位的手机数据,使用手机位置数据分别对九寨沟灾区人口从时间和地理维度上进行了量化分析,估计了多维人口分布的偏差,同时,探讨了剔除微观误差数据用户来估算灾区通讯基站退服分布的方法。该项工作为震后快速获取灾区人口实时动态分布提供了有效途径,同时也为地震灾害评估提供了较准确的依据。     

基于手机定位服务的地震灾情速报和搜救技术探讨

介绍了无线移动定位技术,TOA、TDOA定位技术原理与数学模型,分析了手机定位服务在地震灾情速报和搜救被困人员的应用价值,提出了手机定位服务于灾情速报和地震灾区埋压被困人员搜救技术系统架构,为地震灾区的快速圈定提供重要支持,使得对大面积的地震灾区埋压被困人员准确、快速搜救成为可能。     

高精度静态人口空间分布研究——以银川市西夏区为例

地震发生后，人口空间分布密度是决定救援力量部署的重要依据。然而，高精度人口空间分布数据存在获取和更新困难的问题，缺少有效的解决途径。以银川市西夏区为例，基于高空间分辨率遥感影像，通过建筑物解译与实地调查相结合的方式获取住宅建筑物信息，建立人口与住宅建筑物之间的关系模型，得到更客观真实的人口空间分布情况。研究结果表明，以高空间分辨率遥感影像解译住宅建筑物作为人口空间分布指示因子建模，得到的总体预测人口误差率为3.56%，人口平均相对误差率为9.19%，研究结果具有较高的可靠性，为震前灾害风险评估和震后灾情快速评估提供可靠的人口空间分布数据。     

无人机技术在新疆塔县地震的应用及实现

目前,地震灾情信息的获取主要依靠地震现场调查,费时费力,为第一时间快速了解灾区灾情,以便尽快做出救灾决策,指挥调度救援力量,引进新的技术手段辅助获取灾情信息十分必要。进行了无人机技术在新疆塔什库尔干县地震的应用研究,利用无人机技术,获取了地震极灾区库孜滚村高分辨率影像数据,结合震前GF-1遥感影像数据及地震现场震害调查数据,获取极灾区灾情信息。结果表明:无人机遥感技术可快速采集极灾区遥感影像,有利于对灾情做出正确判断和评估。根据无人机遥感影像结合震前遥感影像和地震现场调查数据,进行区域建筑物结构类型和损毁程度遥感解译,可快速获取灾情,无人机技术在地震应急方面应用效果显著,为灾情评估、救援和灾后重建工作提供了科学决策依据。     

山西省人口空间公里格网分布模型研究

精准的人口分布信息是震后灾害快速评估、应急救援决策的重要依据。本文应用居民地这一与人口分布密切相关的基础数据,结合居民地建筑物给出不同区域人口权重,以人口统计数据为总量控制,完成人口空间公里格网数据模型建立,并与夜间灯光数据、道路数据、实际调研数据等进行对比分析。结果表明,该人口分布模型可靠性高,可为震后灾害快速评估、应急救援决策提供可参考的人口数据。     

基于遥感影像的建筑数据构建研究

在地震灾情快速评估中,基于空间分布的高精度房屋和人口数据是最重要的两组数据,其直接决定着灾情快速评估结果的准确性以及现场重点救援的目标指向。然而,高精度房屋数据的获取一直是一个难题,由于受到诸多因素的制约,至今缺少好的解决途径,这也是导致当前灾情快速评估准确性不高的主要原因之一。本文基于遥感影像和实地调查相结合,构建较高精度的房屋基础信息,更好地反映房屋和人口的实际分布情况,为提高地震灾害损失快速评估的精度和准确性奠定必要的基础。     

面向防震减灾的人口数据空间化研究——以2007年宁洱地震灾区为例

入口是地震灾害的重要受灾体,准确的入口空问分布信息是防震减灾工作的重要依据.本文借助地理信息系统,将人口统计数据与高分辨率遥感数据相结合,应用基于居民地的人口数据空间化方法,模拟人口空间分布.首先根据城市人口—面积异速生长模型的分形几何意义,推导出城乡人口一面积统一模型;进而以2007年宁洱地震灾区为例,在建立居民地分类体系和遥感解译标志的基础上,目视解译获得准确的居民地信息;最后应用城乡人口—面积统一模型获得网格人口密度矢量数据.经检验,本文的结果达到了较高的精度.同时在人口数据空间化完成的基础上,以地震受灾人口估算为例,探讨了人口数据空间化在防震减灾中的应用.研究结果表明,基于网格人口矢量数据的受灾人口估算结果更能客观反映地震灾情,可以为防震减灾和应急救援工作提供可靠的依据.     

震害快速评估中基于GM(1;1)模型的人口预测

地震灾区人口数据是破坏性地震发生时震害快速评估中一项重要的关键基础数据.本文利用GM(1,1)模型建立了甘肃省县一级人口数量的增长模型,实现了静态人口基础数据在地震发生时的动态计算,使其更接近于人口发展的实际情况,为震害评估提供更准确的人口基础数据.     

面向地震应急的人口空间化方法研究——以云南省大理白族自治州为例

为提高震后受灾人口估算精度和灾区人口空间分布可视化表达效果,以云南省大理州为研究区,结合FROM-GLC10地表覆盖数据和NPP/VIIRS夜间灯光数据,基于乡镇人口统计数据,展开人口空间化方法研究,制作了大理州50 m×50 m人口格网数据。使用相关系数、相对误差和平均相对误差对人口模拟结果进行了检验,以漾濞5.1级地震和云龙5.0级地震为例对模拟结果进行了应用分析。结果表明:①结合FROM-GLC10地表覆盖数据和NPP/VIIRS夜间灯光数据的人口空间化可以有效提取人口空间分布范围,并区分人口空间分布的差异性;②乡镇模拟人口与实际统计人口的相关系数R~2为0.955,平均相对误差为14.306%,82%的乡镇相对误差在±20%以内,人口模拟数据精度较高;③2次地震的灾区人口模拟数据与实际统计数据的相对误差分别为-1.67%和-2.27%,人口空间分布模拟结果可以直观反映灾区人口分布情况,研究成果可为震后辅助决策提供数据支持。     

A Monte Carlo study of rainfall forecasting with a stochastic model

A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities.     

Earthquake Engineering and Engineering Vibration Aims And Scope

正This journal is established by the Institute of Engineering Mechanics(IEM),China Earthquake Administration,to promote scientific exchange between Chinese and foreign scientists and engineers so as to improve the theory and practice of earthquake hazards mitigation,preparedness,and recovery.To accomplish this purpose,the journal aims to attract a balanced number of papers between Chinese and     

Foreword

Destructive earthquakes have caused great damage in China and the United States and collapsing buildings havecaused many deaths and injuries. The field of earthquake engineering studies earthquake hazards, the occurrence ofearthquakes of various magnitudes, the nature of the ground shaking during an earthquake, the vibration of structuresduring earthquakes, the strengthening of existing structures and the design of new structures to be earthquake resistant,and finally, how to cope with earthquake damage and restore a city to normal functioning. Such efforts are in progressin both countries, but unfortunately, the language barrier interferes with the free flow of information between China andthe Untied States. It would be mutually beneficial if some means could be developed to promote the exchangeof information across the Pacific Ocean. This new journal has been established for this purpose and its success willbe an important step in promoting earthquake engineering in China and the United States.     

WORLD ASSOCIATION FOR SEDIMENTATION AND EROSION RESEARCH(WASER)

正President:Giampaolo Di Silvio,Italy Vice Presidents:Ulrich C.E.Zanke,Germany Zhao-yin Wang,China The World Association for Sedimentation and Erosion Research(WASER),inaugurated on Oct.19,2004,is an independent non-governmental,non-profit organization.The mission of WASER is to promote international co-operation on the study     

Enhancing remote sensing research on global change to improve our understanding on Earth system processes

正Global Change includes climate change and other environmental changes caused by the joint interaction among various layers of Earth. From the positive side, global change provides new opportunities to human and other living forms on Earth. In the meantime, it creates tremendous challenges and negative impact. At present, the negative impacts have reached all primary processes of the global ecosystem and every aspect of human society, especially causing degradation of the ecosystem. For instance, intensive deforestation causes decline of biodiversity; global warming causes sea level rise and increases     

Dissolved Carbohydrate Concentration,Composition, and Bioavailability to Microbial Heterotrophs in Stream Water

Dissolved total carbohydrates (DTCH), dissolved free monosaccharides (DFMS), dissolved organic carbon (DOC), biodegradable DOC (BDOC), and humic substances (HS) were measured in White Clay Creek (WCC), a stream in southeastern Pennsylvania Piedmont, USA. Samples were collected over different seasons and under baseflow and stormflow conditions. DOC concentrations ranged from 1.0 to 12.8 mg/L C with the highest concentrations associated with stormflows. Carbohydrates ranged from 0.42 to 12.4 μM and accounted for 2.9 to 12.7% of the DOC. Humic substances represented the major DOC fraction, accounting for 55 to 72% of the DOC pool under all flow conditions. The humic fraction had a lower carbohydrate content (4.4%) than the non-humic fraction of DOC (7.2%). Stormflow DOC was enriched in carbohydrates relative to baseflow DOC, but the percentage of humic-C changed little. Carbohydrates were primarily present as dissolved polysaccharides (55%), but a significant fraction was bound to humic substances (40%), while a small proportion was present as monosaccharides (5%). The major monosaccharides in stream water, listed in order of decreasing concentration, included glucose, galactose, rhamnose, xylose, arabinose, mannose, and fucose. On average (30.6 ± 7.4)% (n = 44) of the stream water DOC was biodegradable, and carbohydrates accounted for 9.9 to 17.7% of the BDOC.