UASMaster在无人机低空航空摄影测量生产中的应用

介绍了UASMaster对低空无人机航摄影像的数据处理,并针对无人机应急保障的快拼影像制作和大比例尺测图数据生产的技术流程进行了探讨。     

SOFTWARE REVIEWS

software reviews are in this article MACATLAS . Number Cruncher Statistical System (NCSS) TRANSPRO FIRE-ROUTER     

城市地质灾害应急管理平台的设计与研究

我国地质灾害多发,严重威胁到山地城市安全.城市地质灾害应急管理的首要环节是应急部门对信息的及时沟通和决策部门对信息的高效管理.因此,设计具有完善的数据共享模式,并具备良好服务架构的信息平台是科学应急管理的必要手段.本文研究了城市地质灾害应急管理平台设计中的关键技术,提出了基于地理网络和元数据管理的数据共享模式;建立了基于SOA的平台架构,并描述了分布式环境下的平台配置结构.通过引入先进的软件技术和GIS技术,可以为城市地质灾害救援指挥提供必要的信息和技术支撑,最终实现减轻城市突发性地质灾害损失的目的.     

城市多灾种早期联合预警GIS系统的设计与应用

阐述了城市或区域范围内早期预警协作和预警联合发布的必要性,以及系统的具体设计思路,包括当前城市灾害预警应用现状分析,城市预警数据管理、系统应用设计,系统应用创新三个方面,最终通过城市预警信息融合和共享,来应对解决宽泛而又错综复杂的各类城市灾害问题,拓展应急协作工作的信息广度,提升公众防范的精细化服务水平。     

基于“一张图”的公共安全应急联动态势图的研究

公共安全应急联动态势图是应对公共安全突发事件的有效保障手段之一。文中提出基于"一张图"的观点,对基于"一张图"的公共安全应急联动态势图的体系架构进行阐述,说明基于"一张图"的公共安全应急联动态势图中,应急联动数据链节点构成和应急联动数据链的功能,介绍"一张图"的输出保障模式。     

广东2008年低温雨雪冰冻灾害及气象应急响应

2008年初我国南方遭受了百年一遇低温雨雪冰冻灾害,广东的受灾程度属80年一遇,造成了重大经济损失和严重社会影响.分析发现:灾害过程在近年来最严重的一次"拉尼娜"事件背景下发生的,与欧亚地区持续大气环流异常密切相关.在"北脊南槽"和西太平洋副高偏北偏强的形势下,冷暖气流在我国南方地区频繁交汇,使对流层中低层形成逆温层和局地经向环流产生异常,造成了此次持续低温雨雪冰冻过程.面对灾害引发的公共事件,广东省气象部门打破常规、准确预警,启动预案,通过媒体和"公共事件预警信息发布平台",及时传播权威的公共预警信息,为安定民心、稳定社会、减少灾害起到积极作用.灾后反思发现,山区冰灾的监测、灾害的评估、公共信息发布等的能力和规范均亟待加强.     

gPhone重力仪的面波频段响应实测研究

以中国大陆构造环境监测网络昆明台和恩施台gPhone相对重力仪连续重力潮汐观测数据为基础,研究了gPhone重力仪在1 mHz以上频段的高频响应。从瑞利面波角度获得gPhone重力仪的高频响应,并且通过与同址观测的STS-1地震仪LHZ分量数据进行对比,验证了gPhone重力仪高频观测结果的可靠性。对比从gPhone重力仪和STS-1地震仪观测数据中提取到的面波波形和群速度频散曲线,发现昆明台两类仪器观测到面波信号的振幅和相位都较为一致,而恩施台仅振幅较为一致,相位上存在较明显差异,gPhone重力仪记录的面波信号在各频段存在不同的时间延迟。用两类仪器观测数据获得了大地震激发的自由振荡,结果表明两类仪器观测到的基频球型模态自由振荡的频率和振幅都吻合较好,进一步验证了gPhone重力仪对高频频段信号振幅响应的可靠性。以上研究结果表明:利用gPhone重力仪能够准确地观测到大地震激发的面波和自由振荡等高频信号的振幅,但在记录信号的相位信息时,有些仪器会有相位偏移产生,如果研究中需要考虑信号的相位,则必须获得仪器相位偏移量,再进行仪器相位校正。     

地震应急信息速报视图自动发布系统的设计与实现

基于地震应急基础数据和网络震后灾害信息获取技术的相关研究,利用数据挖掘、大数据分析等理论方法,根据地震应急不同阶段的信息需求,挖掘信息时空属性,建立震情、灾情可视化信息图展现形式,开展对地震数据的整合汇聚、精准服务,创新表达方式,利用高维多元可视化处理技术,构建面向震后信息服务的自媒体可视化产品,并开发“速报视图自动发布系统”。该系统作为地震信息可视化交互服务平台,可实现桌面端和移动端H5页面的可视化发布任务,为今后进一步拓展和充实地震应急信息的可视化工作提供了基础平台和创新思路,在应用示范的基础上,完善系统运行功能,实现大震应急信息可视化服务。     

Mechanical behavior of porous solid considering mesoscopic elastic buckling

In this work, the elastic buckling of porous solids was investigated using a lattice spring model (LSM). The capability of the LSM to solve elastic buckling problems was comprehensively verified by comparing well-established numerical and analytical solutions. Following this, the buckling of a porous solid was studied, in which two porous structures were considered, ie, the random porous model and the Voronoi porous model. The results reveal that both the porosity and the shape of the pores influence the elastic buckling bearing capacity of the porous solid. Finally, the mechanical responses of a porous solid with an extra high porosity (0.85) were numerically investigated. Our numerical results demonstrated that the nonlinear elastic response of the porous solid might come from its mesoscale elastic buckling. This work shows the ability and promise of using the LSM as a fundamental numerical tool for the deep investigation of the buckling mechanical behavior of porous solids.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.