基于STPA法的空中加油软管甩鞭安全性分析

为定量评价空中加油软管甩鞭(HWP)现象的安全性,使用系统理论过程分析(STPA)法查找出相关系统级危险、不安全控制行为和致因因素共计46条,确定与之对应的44项安全对接约束条件;依据空中加油飞行试验数据,定义可量化的安全检查点,依据安全检查点将安全约束条件分为17类,确定各检查点的安全区间和权重;根据飞行数据确定HW...     

Texture Analysis for Mapping Tamarix parviflora Using Aerial Photographs along the Cache Creek, California

Natural color photographs were used to detect the coverage of saltcedar, Tamarix parviflora, along a 40 km portion of Cache Creek near Woodland, California. Historical aerial photographs from 2001 were retrospectively evaluated and compared with actual ground-based information to assess accuracy of the assessment process. The color aerial photos were sequentially digitized, georeferenced, classified using color and texture methods, and mosaiced into maps for field use. Eight types of ground cover (Tamarix, agricultural crops, roads, rocks, water bodies, evergreen trees, non-evergreen trees and shrubs (excluding Tamarix)) were selected from the digitized photos for separability analysis and supervised classification. Due to color similarities among the eight cover types, the average separability, based originally only on color, was very low. The separability was improved significantly through the inclusion of texture analysis. Six types of texture measures with various window sizes were evaluated. The best texture was used as an additional feature along with the color, for identifying Tamarix. A total of 29 color photographs were processed to detect Tamarix infestations using a combination of the original digital images and optimal texture features. It was found that the saltcedar covered a total of 3.96 km² (396 hectares) within the study area. For the accuracy assessment, 95 classified samples from the resulting map were checked in the field with a global position system (GPS) unit to verify Tamarix presence. The producer's accuracy was 77.89%. In addition, 157 independently located ground sites containing saltcedar were compared with the classified maps, producing a user's accuracy of 71.33%.     

Precision Measurements from Very-Large Scale Aerial Digital Imagery

Managers need measurements and resource managers need the length/width of a variety of items including that of animals, logs, streams, plant canopies, man-made objects, riparian habitat, vegetation patches and other things important in resource monitoring and land inspection. These types of measurements can now be easily and accurately obtained from very large scale aerial (VLSA) imagery having spatial resolutions as fine as 1 millimeter per pixel by using the three new software programs described here. VLSA images have small fields of view and are used for intermittent sampling across extensive landscapes. Pixel-coverage among images is influenced by small changes in airplane altitude above ground level (AGL) and orientation relative to the ground, as well as by changes in topography. These factors affect the object-to-camera distance used for image-resolution calculations. ‘ImageMeasurement’ offers a user-friendly interface for accounting for pixel-coverage variation among images by utilizing a database. ‘LaserLOG’ records and displays airplane altitude AGL measured from a high frequency laser rangefinder, and displays the vertical velocity. ‘Merge’ sorts through large amounts of data generated by LaserLOG and matches precise airplane altitudes with camera trigger times for input to the ImageMeasurement database. We discuss application of these tools, including error estimates. We found measurements from aerial images (collection resolution: 5–26 mm/pixel as projected on the ground) using ImageMeasurement, LaserLOG, and Merge, were accurate to centimeters with an error less than 10%. We recommend these software packages as a means for expanding the utility of aerial image data.     

基于HMM和DT的无人机异常检测方法

为了实时检测无人机异常状态,提出基于隐马尔可夫模型(Hidden Markov Model,HMM)和决策树(Decision Tree,DT)的无人机异常检测方法(HMMDT).首先根据异常致因将无人机异常分为干扰异常和硬件异常;然后结合HMM和DT建立无人机异常检测模型,定义无人机异常度衡量异常状态的严重程度,确定...     

无人机遥感系统在某河流域环境监测项目中的应用

剖析了无人机遥感系统的组成及工作流程,结合无人机遥感系统在某河流域环境监测项目中的应用案例进行深度分析。凸显了应用方案的诸多优势,并对该系统在环境保护领域中的应用前景进行了展望。     

基于多旋翼无人机平台的大气PM2.5垂直结构观测技术

目的设计可用于大气边界层范围的大气污染观测平台。方法使用多旋翼无人机作为载体,集成多种大气污染物和气象要素的便携式检测设备,组建无人机观测平台。通过地面比对实验,保障所搭载的设备数据可靠,通过与大载荷系留气艇平台的垂直比对实验验证平台集成后的数据可靠性。结果对于重点观测指标PM_(2.5)而言,无人机和系留气艇所获取的垂直廓线表现出良好的一致性,各个航次的R2最低值为0.762,多数航次的组内相关系数为0.94以上。在2017年12月18日的案例中,无人机的观测数据表明,早上的大气垂直结构呈现了明显分层,0～200 m高度较为稳定的大气层结阻碍了污染物向上扩散,导致了近地面PM_(2.5)80μg/m~3的较高浓度,而下午的观测数据有助于解释污染消散。结论文中搭建的多旋翼无人机平台可以用于0～1000 m范围内的边界层观测,尽管个别航次数据和系留气艇平台仍存在差异,但现有观测结果已表明,该平台有助于研究人员了解污染事件的发生和消散,可以进一步推广应用。     

High-Resolution Vegetation Data for Mangrove Research as Obtained From Aerial Photography

In this methodological study, the applicability of aerial photographs for monitoring mangrove vegetation dynamics at high resolution was investigated. Vegetation maps of three mangrove forests in Sri Lanka (Galle, Rekawa and Pambala) were produced based on visual analysis of aerial photographs. The visual analysis was aided by applying an interpretation key constructed during a first fieldwork mission. Image attributes used for the identification of individual trees included: gray values, texture, form and size of the crowns and the presence or absence of a shaded side. For the identification of species assemblages, the vegetation structure (i.e. the distribution of individual trees) appeared to be an important attribute. The accuracy and reliability of the vegetation maps were investigated during a second fieldwork mission. The aerial photographs proved to be very useful for the production of genus-based vegetation maps. The error analysis showed that density estimations (quantitative identification) based on aerial photography was not sufficiently accurate for the objectives of the study, but that the overall identification of vegetation assemblages (qualitative identification) coincided most satisfactory with the ground-truth data. In addition to the applicability of aerial photography in monitoring mangroves, the importance of aerial photography in the management of the mangrove ecosystem is clearly highlighted.     

一种高分辨率遥感影像建筑物边缘提取方法

提出一种利用高分辨率遥感影像半自动提取建筑物边缘的方法。先对遥感影像进行预处理,对所有边缘进行边缘检测。然后进行边缘跟踪,提取建筑物的主方向线,利用模型进行线段关系判断,再进行线段关系处理、区域分割和区域生长,最后进行区域合并提取出建筑物的轮廓。用上述方法对Quick Bird卫星的高分辨率影像进行了实验,实验结果证明该方法有较高的识别率、较好的准确性,具有一定的实用价值。     

无人机在重大自然灾害中的应用与探讨

重大自然灾害往往会造成重灾区信息通讯中断和道路交通破坏,灾情传递受阻将导致抢险救灾盲目部署,继而造成更大的损失和次生灾害。因此,获取灾情成为重大自然灾害抢险救灾的首要问题。无人驾驶飞机(简称无人机)是一种新工具,能够越过山川河流阻隔,通过摄影、摄像或其他遥感手段获取灾情。通过在北川县曲山镇等地震灾区进行无人机获取灾害信息实验,在2010年玉树地震抢险救灾工作中实现了高原灾区无人机首次航拍,获取的高清图片为划分灾区范围提供了重要依据。鉴于上述实践和探索,介绍了无人机性能和影响无人机摄影的诸多因素,如天气条件、无人机航带航迹和高度、航片重叠率、图片拼接及校正等,对相机与地面影像分辨率的关系进行了介绍,还通过航拍图片和地面图片比对,总结出建筑物倒塌破坏识别的基本要则。     

Antibacterial,antiviral and antioxidant activities of aerial part extracts of Peganum harmala L. grown in Tunisia

Ethyl acetate, chloroform, butanol, and methanol extracts from the aerial part of Peganum harmala were tested for antibacterial, antioxidant, and antiviral activities. The antibacterial activity was evaluated by the determination of minimum inhibitory concentration (MIC) using the solid medium technique. Oxacillin, amoxicillin, ticarcillin, cefotaxim, and amphotericin were used as control agents. The antiviral activity was evaluated against human cytomegalovirus (HCMV) strain AD-169 (ATCC Ref. VR 538) and Coxsackie B virus type 3 (CoxB-3) using a cytopathic effect (CPE) reduction assay. The antioxidant activity was evaluated using two tests: 1,1-diphenyl-2-picrylhydrazyl (DPPH) free-radical scavenging and ammonium thiocyanate methods. Among tested extracts; the chloroform extract displayed a higher antibacterial activity against Gram-positive than Gram-negative bacteria. The butanol extract demonstrated the highest antioxidant activity. The methanol extract showed significant antiviral activity against CoxB-3 virus. The chloroform extract may be an important source of bactericidal compounds against Gram-positive bacteria.