基于GIS的无人机地面监控系统的设计与实现

在分析无人机领域飞行数据特征的基础上,设计实现了一套功能较为完善的无人机地面监控系统。该系统主要完成了无人机飞行状态实时显示、航线规划和航线回放等功能模块。系统借助于G IS技术,导入矢量形式的电子地图,利用丰富的地理信息来辅助实现无人机的地面监控,在V isual C 6.0开发环境下利用基于异步方式和事件驱动方式的串口通信实现了系统与地面控制站的通信,利用地图控制文件实现了地图数据的调度,利用显示缓存实现了视图实时刷新。经过实际联调,系统运行良好,实用性较好。     

RS和GIS结合的初步尝试

通过对航空遥感图像物体特征（色调、形状、大小、阴影、纹理及其相互关系）的提取，采用人机交互和自动识别的方法进行遥感航片的综合分析和利用，是合肥市规划与建设管理信息系统的一个重要内容。ＡＲＣ／ＧＲＩＤ模块的优势在于一对于栅格数据进行显示和查询；对于栅格数据进行算术、逻辑、关系、赋值等操作；对数据进行管理；其分析功能很强，可进行环境分析、社会分析、水文分析、经济分析；建立模型。通过图象分类处理，可将城市绿化、江河、城市主干道、建筑物分类，并对城市绿化进行区域统计，对江河、日照进行分析和对所分割的地块进行检索分析     

Water level observations from unmanned aerial vehicles for improving estimates of surface water–groundwater interaction

Integrated hydrological models are usually calibrated against observations of river discharge and piezometric head in groundwater aquifers. Calibration of such models against spatially distributed observations of river water level can potentially improve their reliability and predictive skill. However, traditional river gauging stations are normally spaced too far apart to capture spatial patterns in the water surface, whereas spaceborne observations have limited spatial and temporal resolution. Unmanned aerial vehicles can retrieve river water level measurements, providing (a) high spatial resolution; (b) spatially continuous profiles along or across the water body, and (c) flexible timing of sampling. A semisynthetic study was conducted to analyse the value of the new unmanned aerial vehicle‐borne datatype for improving hydrological models, in particular estimates of groundwater–surface water (GW–SW) interaction. Mølleåen River (Denmark) and its catchment were simulated using an integrated hydrological model (MIKE 11–MIKE SHE). Calibration against distributed surface water levels using the Differential Evolution Adaptive Metropolis algorithm demonstrated a significant improvement in estimating spatial patterns and time series of GW–SW interaction. After water level calibration, the sharpness of the estimates of GW–SW time series improves by ~50% and root mean square error decreases by ~75% compared with those of a model calibrated against discharge only.     

无人机信号传输中断解决方案研究

在福建地区从事无人机低空数码航空摄影测量项目时,我们发现数传电台信号中断是无人机飞行的一个重大安全隐患。如不能实时掌握无人机飞行动态,出现异常状况时不能第一时间处理,极有可能出现安全事故,造成重大损失。本文通过具体案例说明,提出无人机信号传输中断的解决方案。     

关于地籍工作底图获取方法的探讨

随着社会的发展,现代地籍因其保护土地产权与课税服务的特性越来越被人们重视,成为国土资源管理、城市建设管理的有力依据。本文初步探讨了几种地籍工作底图制作的作业流程、适用工作范围及其优缺点,并简要介绍了新技术在地籍工作底图中的应用。     

倾斜摄影无人机极地应用保障方法研究

介绍了倾斜摄影无人机设备为适应南极长城站地区特殊环境,在设备准备、寒潮防护、运输保护等方面所采用的保障方法,和应对飞行异常情况的技术预案,以及在长城站倾斜摄影任务中的应用情况,为以无人机为飞行载体的科考设备在南极地区的使用提供一种可行的参考方案。     

迁移学习支持下的高分影像山地滑坡灾害解译模型

无人机低空遥感是近年来新兴的一种快速获取灾情信息的手段,如何利用无人机高分影像构建滑坡灾害解译模型是实现快速自动解译滑坡的关键。针对该问题,对比了多种影像特征提取方法,将迁移学习(TL)特征和支持向量机(SVM)引入到构建滑坡灾害自动解译模型中,提出了一种TL支持下的高分影像滑坡灾害解译模型。选取5·12汶川地震及4·20芦山地震系列无人机影像构建了滑坡灾害样本库并进行了实验,TL特征方法整体分类准确度ACC为95%,ROC达到0.98,识别准确率达到97%。结果表明,所提方法可用于高分影像滑坡自动解译,同时可用于大面积高分影像中快速山地滑坡灾害定位及检测。     

无人机影像匹配中尺度不变特征应用改进

针对尺度不变特征变换算法用于无人机影像匹配中存在匹配效率低下,误匹配较多等问题,该文提出一种特征点提取优化算法,并改进了特征点匹配策略。通过将原始影像划分格网,依据每个格网影像信息熵的大小来合理分配各格网中特征点数量,实现了基于纹理信息丰富程度的特征点均匀分布;基于Harris兴趣值进行筛选,保留了适合于摄影测量的特征点;采用一种多层次自适应的匹配策略,在尽可能保留正确匹配的同时提高了匹配正确率。基于一对由小型无人机拍摄影像的实验结果表明,所提方法在大量减少SIFT特征点的同时,保证较高的正确率,增加了匹配点的精度,且提高了算法效率。     

2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

One of the challenges of remote sensing and computer vision lies in the three-dimensional (3-D) reconstruction of individual trees by using automated methods through very high-resolution (VHR) data sets. However, a successful and complete 3-D reconstruction relies on precise delineation of the trees in two dimensions. In this paper, we present an original approach to detect and delineate citrus trees using unmanned aerial vehicles based on photogrammetric digital surface models (DSMs). The symmetry of the citrus trees in a DSM is handled by an orientation-based radial symmetry transform which is computed in a unique way. Next, we propose an efficient strategy to accurately build influence regions of each tree, and then we delineate individual citrus trees through active contours by taking into account the influence region of each canopy. We also present two efficient strategies to filter out erroneously detected canopy regions without having any height thresholds. Experiments are carried out on eight test DSMs composed of different types of citrus orchards with varying densities and canopy sizes. Extensive comparisons to the state-of-the-art approaches reveal that our proposed approach provides superior detection and delineation performances through supporting a nice balance between precision and recall measures.     

Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.