基于Google Earth的无人机任务规划设计

针对无人机任务规划要求,提出了一种利用Google Earth二次开发能力实现的无人机任务规划方法。首先应用任务规划算法得到规划信息,然后将威胁数据、规划数据、飞机数据等信息通过Google Earth提供的接口引入到Google Earth中,得到无人机在Google Earth上的规划航迹。结果表明,该方法不仅省去了地形建模,而且能快速地生成一条逼真性相当高的满足无人机性能要求的规避威胁航路。     

A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America

Land use and land cover (LULC) maps from remote sensing are vital for monitoring, understanding and predicting the effects of complex human-nature interactions that span local, regional and global scales. We present a method to map annual LULC at a regional spatial scale with source data and processing techniques that permit scaling to broader spatial and temporal scales, while maintaining a consistent classification scheme and accuracy. Using the Dry Chaco ecoregion in Argentina, Bolivia and Paraguay as a test site, we derived a suite of predictor variables from 2001 to 2007 from the MODIS 250 m vegetation index product (MOD13Q1). These variables included: annual statistics of red, near infrared, and enhanced vegetation index (EVI), phenological metrics derived from EVI time series data, and slope and elevation. For reference data, we visually interpreted percent cover of eight classes at locations with high-resolution QuickBird imagery in Google Earth. An adjustable majority cover threshold was used to assign samples to a dominant class. When compared to field data, we found this imagery to have georeferencing error < 5% the length of a MODIS pixel, while most class interpretation error was related to confusion between agriculture and herbaceous vegetation. We used the Random Forests classifier to identify the best sets of predictor variables and percent cover thresholds for discriminating our LULC classes. The best variable set included all predictor variables and a cover threshold of 80%. This optimal Random Forests was used to map LULC for each year between 2001 and 2007, followed by a per-pixel, 3-year temporal filter to remove disallowed LULC transitions. Our sequence of maps had an overall accuracy of 79.3%, producer accuracy from 51.4% (plantation) to 95.8% (woody vegetation), and user accuracy from 58.9% (herbaceous vegetation) to 100.0% (water). We attributed map class confusion to limited spectral information, sub-pixel spectral mixing, georeferencing error and human error in interpreting reference samples. We used our maps to assess woody vegetation change in the Dry Chaco from 2002 to 2006, which was characterized by rapid deforestation related to soybean and planted pasture expansion. This method can be easily applied to other regions or continents to produce spatially and temporally consistent information on annual LULC.     

基于Google Earth的数字校园WebGIS系统的专题制图

数字校园建设是实现基于位置的查询和显示空间信息Web发布与服务的基础平台.生成校园数字地图是数字校园的重要基础,通过使用Google Earth提供的遥感影像图片,以哈尔滨师范大学的数字校园系统为例,对校园空间信息系统的生成进行了成功的设计与实现.     

A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation

China plans to launch four small optical satellites and four small SAR satellites to form a natural disaster monitoring constellation. Data can be obtained by the constellation in all weather conditions for disaster alert and environmental damage analysis. The scheduling problem for the constellation consists of selecting and timetabling the observation activities to acquire the requested images of the earth surface and scheduling the download activities to transmit the image files to a set of ground stations. The scheduling problem is required to be solved every day in a typical 1-day horizon and it must respect complex satellite operational constraints as well as request preferences, such as visibility time windows, transition time between consecutive observations or downloads, memory capacity, energy capacity, polygon target requests and priorities. The objective is to maximize the rewards of the images taken and transmitted. We present a nonlinear model of the scheduling problem, develop a priority-based heuristic with conflict-avoided, limited backtracking and download-as-needed features, which produces satisfactory feasible plans in a very short time. A decision support system based on the model and the heuristic is also provided. The system performance shows a significant improvement with respect to faster and better scheduling of an earth observing satellite constellation.     

无人运输机地面控制站显示界面的仿真系统

为实现地面控制站操作员对民用无人机的安全控制,提出了地面控制站集飞行仪表、地图综合界面显示设计方案. 采用GL Studio 和VC++ 6.0混合编程的方式,实现对飞行仪表显示界面的设计;使用VC++6.0 对Google Earth二次开发实现地面控制站地图显示功能. 将微软模拟飞行X作为飞行仪表和地图界面的数据驱动,通过UDP传输协议,实现仿真系统的综合测试. 测试结果表明,该系统设计可以为地面控制站操作员提供完整的态势信息,提高操作员的决策效率,为研究地面控制站显示界面工效问题提供新的方法.     

Google Earth在森林植被营养元素循环研究中的应用

森林植被营养元素循环是森林生态系统分析中的重要参数.将Google Earth应用在其研究过程中具有重要作用.阐述了Google Earth的主要原理和关键技术,重点分析了KML和Google EarthAPI;设计了Google Earth应用的数据处理流程和系统架构;最后实现了基于Google Earth的贵州龙里森林植被营养元素循环研究系统.     

基于Google Earth的数字城市快速建模——以扬州科技学院扬子津校区为例

以扬州科技学院扬子津校区为例, 以Google Earth为数据源, 以ArcGIS和天正软件为平台, 针对建筑施工图是否佚失, 分别从两条路径制定数字城市建模方案, 一是利用ArcGIS进行建筑物空间位置控制, 二是在空间控制的基础上或利用ArcGIS建模并在SketchUp软件中对模型进行细化处理, 或是直接将建筑施工图导入GIS平台中, 最终将两类数据在ArcGIS平台加以融合, 从而使三维数字城市建模变得快速, 高效, 极大降低了数字城市建设的成本, 同时还对该成果在城市规划、楼盘营销、数字导航领域中的应用进行了初步探讨.     

地球重力场模型在高程控制网中的应用

不同地球重力场模型的优选及不同拟合方法的合理选择是GPS高程转换所需考虑的关键问题。随着以卫星重力梯度为主要观测值的GOCE重力卫星的发射成功及其相关重力场模型的推出,地球重力场模型的精度及分辨率有了较大提高,有必要将其应用于GPS高程转换的研究。本文提出了用目前具有较高精度的SGG地球重力场模型来代替以往较低精度地球重力场模型的策略,计算分析了这种模型解算全球高程异常的精度,并将这种模型应用于”移去一拟合一恢复”法的GPS高程转换中,使GPS提供真正意义上的三维坐标。     

可编程控制器系统可靠性的设计

PLC广泛应用于社会生产各个行业，因此讨论其可靠性以及提出设计方案是非常必要的。文章分析了最为关注也是最为影响PLC可靠性的供电系统设计和接地设计，首先具体提出了供电系统保护措施的四种方法以及一般PLC系统供电电源设计，在I／O模板供电电源设计中则给出了24V直流和220V交流两种I／O模板的供电设计，最后分析了接地设计中应注意的问题并着重分析了接地电阻的选择。