Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data

Combined optical and laser altimeter data offer the potential to map and monitor plant communities based on their spectral and structural characteristics. A problem unresolved is, however, that narrowly defined plant communities, i.e. plant communities at a low hierarchical level of classification in the Braun-Blanquet system, often cannot be linked directly to remote sensing data for vegetation mapping. We studied whether and how a floristic dataset can be aggregated into a few major discrete, mappable classes without substantial loss of ecological meaning. Multi-source airborne data (CASI and LiDAR) and floristic field data were collected for a floodplain along the river Waal in the Netherlands. Mapping results based on floristic similarity alone did not achieve highest levels of accuracy. Ordination of floristic data showed that terrain elevation and soil moisture were the main underlying environmental drivers shaping the floodplain vegetation, but grouping of plant communities based on their position in the ordination space is not always obvious. Combined ordination-based grouping with floristic similarity clustering led to syntaxonomically relevant aggregated plant assemblages and yielded highest mapping accuracies.     

基于B/S架构的城市车辆指挥调度系统

提出了基于B/S架构的WebGIS城市车辆指挥调度系统框架,综合利用了GPS、GPRS等技术,实现了对城市车辆的指挥调度功能。     

动态空间正图像透视投影正反解

卫星图像都是在动态情形下获取的。瞬间曝光获取的图像投影性质符合透视投影。本文针对卫星动态获取的正图像,建立其平面透视投影,利用矢量解法研究其正反解变换和星下点坐标计算方法,最后给出了算例。     

GPS车载导航的交互式多模型算法

GPS动态定位数据的处理广泛采用卡尔曼滤波技术,而应用卡尔曼滤波要求运动模型准确可靠,但由于载体真实运动的复杂多变,任何单一模型都难以全面描述,致使单一模型的滤波都容易出现模型误差。针对这一问题,将机动目标跟踪领域广泛应用的交互式多模型算法引入到车载导航中。通过分析车辆的运动特点,选取匀速直线模型和当前统计模型进行交互;同时考虑到车载终端计算能力有限,将状态变量在各方向解耦。仿真显示,在机动时改进的算法和单一模型的自适应算法基本相当,但在非机动时改进的算法明显占优。     

Vision-based tracking with projective mapping for parameter identification of remotely operated vehicles

Parameter identification of a remotely operated vehicle (ROV) is often based on the dynamic responses collected by its onboard sensors. However, for commercial ROVs, the required data for identification may not be available due to the absence of suitable sensors or limitations in accessing onboard sensor data. Therefore, this study proposes a vision-based tracking system to measure the dynamic response of an ROV. The tracking system is independent of the ROV, and is able to localize an ROV to a high degree of precision by means of projective mapping. The validity of the proposed tracking system is demonstrated through identification of a commercial ROV. A simplified nonlinear ROV dynamic model with six degrees of freedom (DOF) is used for identification. Uncoupled motions, including surge, sway, and yaw, are obtained from the ROV dynamic model, and the corresponding experiments are carried out for each DOF. Hydrodynamic parameters are then estimated with numerical optimizations by comparing the measured ROV responses with the output of the mathematical model. The experimental results show that the vision-based tracking system can accurately measure the transient and steady-state responses of an ROV. Additionally, the simulations of the ROV dynamic model, with the optimal parameter estimates, give results in agreement with the measured data.     

In-situ survey of nanomolar manganese in seawater using an autonomous underwater vehicle around a volcanic crater at Teishi Knoll,Sagami Bay,Japan

We present the results of a chemical survey at a submarine volcano, Teishi Knoll, obtained using a submersible in-situ Mn analyzer (GAMOS) mounted on an autonomous underwater vehicle (AUV) platform. During this survey, high-resolution data of dissolved Mn were obtained in three dimensions in nearly real time. The AUV enabled continuous detailed observations along a preprogrammed pathway, which could not have been performed with conventional CTD hydrocasts. During this observation, anomalously high dissolved Mn concentrations were obtained within the crater, corresponding to high water temperatures. The anomalies might be a hydrothermal signature due to volcanic activity from the crater.     

基于LiDAR数据的DEM和矢量自动提取探讨

近年来LiDAR技术发展迅速,应用潜力巨大.基于TerraSolid软件环境,简要介绍了LiDAR数据的分类,在此基础上,重点讨论了LiDAR数据的DEM和矢量自动提取的相关问题.由LiDAR数据生成的DEM精度较高.但矢量自动提取还未到实用阶段.     

基于模糊控制的快速循迹智能车的设计与实现

提出基于模糊控制的快速循迹智能车的实现方法.利用转速传感器、线阵CCD、舵机等构成一个闭环控制系统,并采用PI算法控制智能车后轮速度.采用模糊控制算法将线阵CCD返回的误差模糊化,然后按照MAX-MIN规则进行逻辑推理,最后将推理结果反模糊化后以控制舵机转向.实验结果证明了该方法的有效性.     

无舵翼水下机器人路径跟踪控制研究

针对无舵翼水下机器人的各种不同任务要求下的路径跟踪控制进行研究。通过模拟人的运动行为,建立了虚拟避碰声纳模型。根据地形跟踪的方法提出基于虚拟声纳的路径跟踪控制方法,并通过考虑纵向速度对于其他各个自由度运动的影响设计了运动控制器。通过海上试验验证了所提出的路径跟踪控制方法对于无舵翼水下机器人是可以满足实际需要的。     

Hydrodynamic and dynamic analysis to determine the directional stability of an underwater vehicle near a free surface

A theoretical methodology to determine the open-loop directional stability of a near-surface underwater vehicle is presented. It involves a solution of coupled sway and yaw equations of motion in a manner similar to that carried out for surface ships. The stability derivatives are obtained numerically through simulation of motions corresponding to planar motion mechanism (PMM) model tests. For the numerical simulation, a boundary-integral method based on the mixed Lagrangian-Eulerian formulation is developed. The free-surface effect on the vehicle stability is determined by comparing the results with that obtained for vehicle motion in infinite fluid. The methodology was used to determine the stability of the Florida Atlantic University’s Ocean EXplorer (OEX) AUV. The presence of the free surface, through radiation damping, is found to suppress unsteady oscillations and thereby enhance the directional stability of the vehicle. With effects of free surface, forward speed, location and geometry of rudders, location of the center of gravity etc. all being significant factors affecting stability, a general conclusion cannot be drawn on their combined effect on the vehicle stability. The present computational methodology is therefore a useful tool to determine an underwater vehicle’s stability for a given configuration and thus the viability of an intended mission a priori.