利用Jx4加密成果在像素工厂进行快速DOM生产

通过利用已有JX4加密成果在像素工厂进行快速DOM生产的试验,研究使用像素工厂快速生产DOM的生产流程和技术方案,测试其精度及效率。     

像素工厂中真正射影像的生产及其精度分析

像素工厂是当今世界一流的遥感影像自动化处理系统,集自动化、并行处理、多种影像兼容、远程管理等特点于一身,代表了当前遥感影像数据处理技术的发展方向,主要用于地形图测绘、城市规划等。这里主要分析像素工厂生产数字表面模型(DSM)和真正射影像的工作流程,并结合实际生产进行精度分析。     

浅谈像素工厂在辽宁省1∶2000 DOM制作中的应用

根据辽宁省1∶2 000 DOM制作项目的实际需求,研究了利用像素工厂高效地生产DOM的关键技术。本文通过案例分析了像素工厂制作DOM的基本流程和方法,验证了无控空三平差获得的数据成果可满足1∶2 000正射影像的精度要求,总结了像素工厂提高生产DOM效率的几点经验方法,并提出实际生产中存在的问题,对像素工厂的优化具有参考价值。     

像素工厂中真正射影像的生产及其精度分析

像素工厂是当今世界一流的遥感影像自动化处理系统,集自动化、并行处理、多种影像兼容、远程管理等特点于一身,代表了当前遥感影像数据处理技术的发展方向,主要用于地形图测绘、城市规划等.这里主要分析像素工厂生产数字表面模型(DSM)和真正射影像的工作流程,并结合实际生产进行精度分析.     

基于像素工厂的海量遥感卫星影像处理方法

像素工厂是当今世界一流的遥感影像自动化处理系统,具有超强的影像处理能力,可以自动处理多种传感器的海量数据,生产各种基础地理信息成果。高分一号卫星是中国高分辨率对地观测系统的第一颗卫星,为经济社会发展建设提供丰富的影像资源。本文以国产高分一号卫星影像数据为基础数据源,结合实际生产,探索了一套基于像素工厂系统的高效处理高分一号卫星影像的关键技术及工艺流程。     

不同影像处理系统的空三数据处理比较研究

系统介绍了像素工厂和海拉瓦数字摄影测量系统的空中三角测量特点,并通过实验比较了二者的性能。实验比较发现,基于两个系统的空中三角测量精度基本相同;执行效率方面,当测区数据量较大时,像素工厂更具有整体优势;而在小区域数据处理上,SOCET GXP更具灵活性。当测区影像超过150景时,建议在像素工厂中进行空中三角测量。     

基于像素工厂的无人机影像空三优化技术

研究了利用像素工厂对无人机遥感影像进行空三优化技术。分析了像素工厂快速处理无人机遥感影像的理论依据和方法;探讨了空三优化分组参数的绑定策略;提出了空三优化结果的精度评价要求。最后利用GPS辅助无人机遥感影像数据进行试验验证,结果表明:在像素工厂平台上对无人机遥感影像进行空三优化处理,能够快速地为后续DSM,DOM和真正射影像生产提供符合精度要求的基础数据。像素工厂与无人机影像数据的结合是无人机测绘工程自动化处理和应急保障的一个有效途径。     

像素工厂DOM制作的精度研究

像素工厂是新一代的自动化影像处理系统,它与传统的生产工艺相比,具有快速、高效的优势。本文针对生产中发现的精度损失问题,通过实验说明产生问题的主要原因,最后简述了该问题在实际生产中的解决方法。     

基于像素工厂的京津冀地区GF-1正射影像制作

本文选择京津冀地区高分一号卫星影像作为研究对象,制定像素工厂平台下大区域高分一号正射影像制作方案。研究了利用像素工厂对大区域高分辨率遥感影像进行空三优化、正射校正、影像融合、影像镶嵌等关键技术,完成了京津冀地区高分一号正射影像的制作。精度评价结果表明,利用像素工厂能够生产在定位精度上满足要求的大区域高分一号卫星遥感影像正射影像,像素工厂在处理高分一号卫星遥感影像上具有大批量、精度高的优势。     

像素工厂在宿迁市第二次土地调查中的应用

近年来,出于处理海量数字影像的需要,法国Infoterra公司的“像素工厂”(Pixel Factory,简称PF)系统已被引入到国内.像素工厂是一种能够处理海量数据、进行并行计算和高度自动化的新一代数字影像处理系统.利用像素工厂能够进行高精度的DSM、DEM、DOM和True DOM产品的生产与制作.     

像素工厂空三转换及其精度控制研究

空中三角测量是摄影测量生产中的关键步骤,是创建DEM、DOM和进行立体测图的基础.像素工厂是新一代数字摄影测量系统,其空三数据格式与传统的VirtuoZo空三格式存在区别,本文对比分析VinuoZo与PF的空三加密成果,研究VirtuoZo与PF空三数据的转换关系,并控制PF的空三精度.     

Improved Priority‐Flood method for depression filling by redundant calculation optimization in local micro‐relief areas

Depression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data.     

利用双变量同化与PCA-Copula法的冬小麦单产估测

为了进一步提高冬小麦产量估测的精度,基于集合卡尔曼滤波算法和粒子滤波（particle filter, PF）算法,对CERES–Wheat模型模拟的冬小麦主要生育期条件植被温度指数（vegetation temperature condition index,VTCI）、叶面积指数（leaf area index, LAI）和中分辨率成像光谱仪（moderate-resolution imaging spectroradiometer, MODIS）数据反演的VTCI、LAI进行同化,利用主成分分析与Copula函数结合的方法构建单变量和双变量的综合长势监测指标,建立冬小麦单产估测模型,并通过对比分析选择最优模型,对2017—2020年关中平原的冬小麦单产进行估测。结果表明,单点尺度的同化VTCI、同化LAI均能综合反映MODIS观测值和模型模拟值的变化特征,且PF算法具有更好的同化效果;区域尺度下利用PF算法得到的同化VTCI和LAI所构建的双变量估产模型精度最高,与未同化VTCI和LAI构建的估产模型精度相比,研究区各县（区）的冬小麦估测单产与实际单产的均方根误差降低了56.25 kg/hm2,平均相对误差降低了1.51%,表明该模型能有效提高产量估测的精度,应用该模型进行大范围的冬小麦产量估测具有较好的适用性。     

Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter

Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes, which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance. Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes, which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories, and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages.     

基于ADS80推扫式相机数据在PF中的预处理方法及要点

像素工厂(简称PF)具有自动化程度高、处理速度快等特点,被越来越多的行业内同仁所青睐。但由于PF在国内还属于新兴技术,针对于一些具体工作还没有相关的作业指导文件。本文通过实际生产,总结出了一套对推扫式相机数据(ADS80)进行预处理,使其能够满足PF格式的作业方法,并对相关的技术要点进行了说明。文中介绍的方法及步骤,对类似的工作,具有很高的参考价值。     

Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery

This research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes – primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water – were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed “from-to” conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation – the conversion from PF to SF and AP – accounted for a large proportion of land-cover changes, the changes between SF and AP became more important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization.     

从PF和DPGrid的发展谈数字摄影测量发展的新特征

结合目前国内外新一代摄影测量处理系统的发展现状,从主要特点、功能组成、工艺流程、产品体系、关键技术等共性方面,深入分析和总结了新一代摄影测量处理系统的基本特征;同时指出了今后数字摄影测量处理系统的发展重点和方向.     

应用高斯粒子群优化的无迹粒子滤波

针对粒子滤波算法中存在的粒子退化与粒子匮乏的缺陷,提出了利用高斯粒子群优化无迹粒子滤波的新算法。算法使用无迹粒子滤波进行重要性采样,并将高斯粒子群优化算法融入重采样过程中。该算法选取的概率密度更加接近系统真实状态,有效增加了粒子的多样性,提高了抽样效率,降低了粒子退化程度,缓解了粒子匮乏现象。试验结果表明,该算法的滤波精度明显优于粒子滤波与无迹粒子滤波算法所得到的滤波精度。     

基于局域均值分解和BP神经网络的大坝变形预测

从时频联合域分析角度出发,探讨基于局域均值分解(LMD)和BP神经网络模型的大坝变形预测方法;利用局域均值分解把时间序列分解为多个具有不同尺度的PF分量,然后再用BP神经网络对其进行预测并将结果进行叠加重构合成。实例结果表明,基于LMD-BP的大坝变形预测方法的预测精度高于多项式曲线拟合预测模型,其预测结果与实际监测值相比具有较高的一致性。