GIS技能竞赛辅助“空间分析与建模”教学的探索与实践

本文在简介“空间分析与建模”教学概况的基础上,分析了高校进行“空间分析与建模”教学的教学目标,通过指导学生参加高校GIS技能竞赛,结合竞赛依托平台进行技能与技巧的培训和指导,并将参赛实践引入到“空间分析与建模”的课程教学中,使得教学与竞赛相结合,促进了“空间分析与建模”教学的改革,使该课程教学始终与全国性学生竞赛实践紧...     

三维点云室内平面要素提取与优化

室内平面要素的准确提取与关系恢复是室内模型自动化语义重建的重要基础,本文提出了一种面向复杂三维点云的室内平面要素提取与优化方法。该方法首先利用区域增长和RANSAC平面混合分割方法分割室内点云数据;其次利用室内语义部件的空间位置信息及包围盒和法向量信息,对分割后的平面进行平面要素的精确提取;然后对提取的墙面进行优化,实现共享墙面的合并,解决室内墙面冗余的问题;最后利用门与墙的空间位置信息,恢复门墙关联关系。试验部分采用了两组试验数据：一组是深圳大学某层教学楼的激光点云数据,另一组是国际摄影测量与遥感学会（ISPRS）的标准数据,通过对试验结果进行评估,验证了本文方法的有效性和可靠性。     

Toward the optimization of PC-based training

Since 1992, the National Space Development Agency of Japan (NASDA) and the Economic and Social Commission for Asia and the Pacific (ESCAP) have been co-organising the Regional Remote Sensing Seminar on Tropical Ecosystem Management (Program Chairman: Prof. Shunji Murai) every year in some country in Asia. In these seminars, the members of the ISPRS Working Group VI/2 ‘Computer Assisted Teaching’ have been performing a PC-based hands-on-training on remote sensing and GIS for beginners. The main objective of the training was to transfer not only knowledge but also the technology of remote sensing and GIS to the beginners. The software and CD-ROM data set provided at the training were well designed not only for training but also for practical data analysis. This paper presents an outline of the training and discusses the optimisation of PC-based training for remote sensing and GIS.     

基于坡度自适应的机载LiDAR分割算法

本文提出了一种适用于离散LiDAR数据的区域生长算法:将离散点云数据重采样为规则格网,通过坡度自适应区域生长法分割规则格网,获得不同的面片;建立各个分割面片之间的拓扑关系,将分割面片划分为粗差、植被、建筑物和地面;检测原始激光脚点到DTM的距离,判断是否为地面点。文中采用ISPRS提供的测试数据验证了算法分割的有效性。     

开源软件辅助下“微波遥感”实践教学改革与探索

针对“微波遥感”教学中存在的学生动手能力差、实践能力培养欠缺等问题,探索利用开源软件进行实践教学辅助的教学改革。分析了开源软件在实验教学中的优缺点,介绍了微波遥感中常用的开源软件及主要功能。在此基础上,构建了一套开源软件辅助下的“微波遥感”实践教学项目,建立了标准实验数据集,编写了实验指导材料,并通过百度云盘等方式实现了网络共享。通过教学改革,拓展了学生的实践教学途径,提高了学生的实践动手能力及微波遥感数据处理能力。     

Progress in the Development of a High Performance Airborne Digital Sensor

Joint development work by LH Systems and Deutsches Zentrum für Luft- und Raumfahrt (German Aerospace Center) has produced encouraging results using forward, nadir and backward looking linear arrays on the focal plane to provide panchromatic imagery and geometric information, supplemented by further arrays to acquire multispectral imagery suitable for both high precision photogrammetric mapping and image processing for interpretative purposes. The geometric characteristics of line scanner imagery necessitate line-by-line rectification for aircraft tilts and shifts. Satisfactory execution of this process is enhanced by using supplementary data from high performance, on-board GPS and inertial measurement systems. Similarly, high demands are placed on other sub-systems, such as the camera mount, lens, electronics and storage technology. In addition to rectification for aircraft tilts and shifts, rectification for terrain characteristics is also required in order to generate colour and false colour composite images, since the various multispectral arrays are in different places on the focal plane. The special geometry affects triangulation. Thereafter, the imagery can be processed using existing software packages from both photogrammetry and remote sensing.
The concept has been demonstrated in several successful test flights and the production model is scheduled for market introduction at the ISPRS Congress in July 2000. The imagery from the new sensor will fulfil many market requirements between the highest resolution film imagery (<0.1 m) and high resolution space imagery (1m to 10 m). The sensor's unique blend of multispectral information with high quality geometric information will give rise to numerous new applications.     

A building extraction approach for Airborne Laser Scanner data utilizing the Object Based Image Analysis paradigm

In the past two decades Object-Based Image Analysis (OBIA) established itself as an efficient approach for the classification and extraction of information from remote sensing imagery and, increasingly, from non-image based sources such as Airborne Laser Scanner (ALS) point clouds. ALS data is represented in the form of a point cloud with recorded multiple returns and intensities. In our work, we combined OBIA with ALS point cloud data in order to identify and extract buildings as 2D polygons representing roof outlines in a top down mapping approach. We performed rasterization of the ALS data into a height raster for the purpose of the generation of a Digital Surface Model (DSM) and a derived Digital Elevation Model (DEM). Further objects were generated in conjunction with point statistics from the linked point cloud. With the use of class modelling methods, we generated the final target class of objects representing buildings. The approach was developed for a test area in Biberach an der Riß (Germany). In order to point out the possibilities of the adaptation-free transferability to another data set, the algorithm has been applied “as is” to the ISPRS Benchmarking data set of Toronto (Canada). The obtained results show high accuracies for the initial study area (thematic accuracies of around 98%, geometric accuracy of above 80%). The very high performance within the ISPRS Benchmark without any modification of the algorithm and without any adaptation of parameters is particularly noteworthy.     

多级移动曲面拟合的自适应阈值点云滤波方法

为了提高机载激光雷达点云滤波算法的精度、效率以及自适应性,提出了一种多级移动曲面拟合的自适应阈值点云滤波方法。首先,对点云数据进行预处理即剔除粗差,然后通过格网化分割建立格网索引,利用每个格网的邻域格网中的最低点建立曲面方程,计算真实高程与拟合高程的差值并设置自适应性阈值进行滤波,最后采用多级滤波策略,即逐级改变格网大小并自动设置邻域和阈值,直到滤波结果达到精度要求。使用国际摄影测量与遥感学会（ISPRS）提供的测试数据对算法进行验证,第1、2类误差和总误差平均值分别为7.33%、10.64%、6.34%。将该算法与ISPRS公布的8大经典滤波算法进行比较,结果表明该方法的适应性强,滤波结果具有较高的准确性。     

Results of the ISPRS benchmark on urban object detection and 3D building reconstruction

For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of airborne image and laserscanner data, has been made available to the scientific community by ISPRS WGIII/4. Researchers were encouraged to submit their results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current airborne sensor data, but also common problems of state-of-the-art methods.     

抗差趋势面的机载LiDAR点云滤波方法

传统曲面约束滤波算法中,利用最小二乘拟合地形曲面易受种子点粗差影响。针对这一问题,提出基于抗差趋势面的机载激光雷达点云数据滤波方法,首先构建格网索引组织数据,引入抗差趋势面拟合合理的区块地形,通过自适应阈值的设置实现不同区域的自动灵活处理,最终滤除孤立点完善滤波结果。使用ISPRS提供的测区数据进行实验,与传统曲面拟合方法进行对比,实验结果证明,该方法较传统移动曲面拟合法能够得到更加可靠的滤波结果,具备较高实用价值。     

微机遥感图像应用处理系统

本文详细介绍了我们研制的微机遥感图像应用处理系统。它的硬件部分以四台微机为主,采用分布式联接,组成四个子系统,可供1—4人同时操作,能方便地输入输出多种数据和图像。该系统的软件部分,由对应硬件子系统的四个软件包组成,即磁带机数据采集软件包,图像显示软件包,专题制图软件包及遥感应用处理软件包。作为重点的第四部分软件,是在遥感应用工作者的经验和工作方法的基础上设计的,它收集和综合了各种实用处理方法,比通用的图像处理软件包更具有遥感应用的特色。     

虚拟现实与计算机动画

虚拟现实与计算机动画方面的研究内容在较长的时期内是一个热点主题,ISPRS将其列为一个专题,对支持摄影测量与遥感的成果展示有积极的促进作用。本文通过归纳和总结2008年ISPRS大会的该专题论文,简要地给出这些论文的主旨,以企为读者提供举纲张目的帮助。这些论文的研究内容集中在3维可视化相关技术方面,包括3维数据获取建模与处理、3维模型数据精简、纹理数据提取、DEM可视化以及巷道可视化方法等。     

Computer-assisted teaching and learning in photogrammetry

The advanced personal computer models, new storage media such as CD-ROMs, new authoring tools and especially the Internet will influence the production of learning software for photogrammetry. Some examples of learning programs are presented, including experience from the development and use of these programs in the education of land surveyors. They demonstrate the progress made over the years as well as the potential and possibilities of computer-assisted teaching and learning in photogrammetry.     

大学生GIS开发大赛对GIS专业实践教学的启示

针对大学生GIS开发大赛的特点、目的和意义,通过对当前GIS实践教学中存在的不足及成因分析,结合GIS学科特点及参赛实践,就GIS开发大赛在GIS专业实践教学的教学内容、教学模式、教学改革和教师队伍建设等方面的启示进行探讨。大学生GIS开发大赛的开展,促进GIS专业实践教学改革的深入,培养学生创新能力和工程实践能力,有利于提高GIS专业实践教学的质量。     

高分辨率遥感影像语义分割的半监督全卷积网络法

在遥感领域,利用大量的标签影像数据来监督训练全卷积网络,实现影像语义分割的方法会导致标签绘制成本昂贵,而少量标签数据的使用会导致网络性能下降。针对这一问题,本文提出了一种基于半监督全卷积网络的高分辨率遥感影像语义分割方法。通过采用一种集成预测技术,同时优化有标签样本上的标准监督分类损失及无标签数据上的非监督一致性损失,来训练端到端的语义分割网络。为验证方法的有效性,分别使用ISPRS提供的德国Vaihingen地区无人机影像数据集及国产高分一号卫星影像数据进行试验。试验结果表明,与传统方法相比,无标签数据的引入可有效提升语义分割网络的分类精度并可有效降低有标签数据过少对网络学习性能的影响。     

应急服务空间数据集成研究进展

第21届国际摄影测量与遥感大会（ISPRS）于2008年7月在北京召开。大会共举办了10个大类275场次的学术交流活动,共收集论文全文1881篇。其中应急服务空间数据集成主题共收录来自中国、加拿大、日本、德国、法国、意大利等9个国家的18篇会议论文,围绕应急服务信息快速获取、应急服务信息共享与互操作、应急服务决策支持系统、灾害情景分析、应急响应空间数据基础设施建设等方面展开了系统研究,这基本反映了该主题的研究现状和发展前沿。     

Report on the ISPRS Journal of Photogrammetry and Remote Sensing (PRS) for the period 1996–2000

This report was presented by the author, as Editor-in-Chief (EIC) of PRS, to the General Assembly of the Delegates of the ISPRS Members during the 19th ISPRS Congress, Amsterdam, 16–23 July 2000. Since it summarises in quite some detail many new developments since the last Congress that are of interest not only to ISPRS in general, but also to authors and readers, a slightly modified version of this report is published here.     

Assessment of various parameters on 3D semantic object-based point cloud labelling on urban LiDAR dataset

Semantic labelling of LiDAR point cloud is critical for effective utilization of 3D points in numerous applications. 3D segmentation, incorporation of ancillary data, feature extraction and classification are the key stages in object-based point cloud labelling. The choice of algorithms and tuning parameters adopted in these stages has substantial impact on the quality of results from object-based point cloud labelling. This paper critically evaluates the performance of object-based point cloud labelling as a function of different 3D segmentation approaches, incorporation of spectral data and computational complexity of the point cloud. The designed experiments are implemented on the datasets provided by the ISPRS and the results are independently validated by the ISPRS. Results indicate that aggregation of dense point cloud into higher-level object analogue (e.g. supervoxels) before 3D segmentation stage offers superior labelling results and best computational performance compared to the popular surface growing-based approaches.     

室内三维点云空间自动划分与规则化方法北大核心CSCD

精准空间划分是实现室内语义建模与拓扑结构重建的重要基础。三维点云作为常用的室内空间数据载体,如何基于三维点云进行室内空间语义信息提取与规则化具有重要意义。本文提出了一种基于形态学分割方法实现室内场景的分割,并结合矢量规则化方法完成分割场景的规则化。首先,基于区域增长算法与线性拟合方法提取空间分割要素,通过平面投影生成二进制影像,进而利用距离变换和分水岭算法完成空间分割;然后,对空间分割要素进行线性拟合,进行室内空间格网划分,采用矢栅叠加方法实现空间要素规则化;最后,通过4组实际场景(包含3组ISPRS数据集及1组实际场景采集数据)进行数据验证。试验结果显示,本文提出的室内空间分割与规则化方法可以准确快速地完成室内空间要素的提取。     

Gottfried Konecny:involvement of spatial information sciences in ISPRS disciplines

Preface I am pleased to contribute an article to GSIS to com-memorate the great achievements of Prof.Dr.Gottfried Konecny on the occasion of the celebration of his 90th birthday. I was lucky to work closely with Gottfried as an ISPRS Council member for the first time in 1984 in Rio de Janeiro,Brazil,when I was elected as Congress Director of the Kyoto ISPRS Congress to be held in 1988.Gottfried was elected as ISPRS President for 1984～1988.At the first Council meeting under the President Gottfried,he said to all Council members"as we are like a family,I request that we address each other by our first names".If he had not said this,I might have called him Professor Konecny,according to Japanese custom.