GSIS专辑精选| “地球空间信息科学的挑战与趋势”
为庆祝李德仁院士80岁寿辰，总结李德仁院士40年来在地球空间信息科学领域所作的贡献，《地球空间信息科学学报》（Geo-Spatial Information Science，GSIS，2020年9月被SCI收录）推出了“地球空间信息科学的挑战与趋势”专辑，武汉大学龚健雅院士，邵振峰教授为专辑特邀客座编辑。
本期专辑作者包括ESRI总裁Jack Dangermond、美国科学院院士Michael F. Goodchild、ISPRS现任主席Christian Heipke、ISPRS名誉会员、曾任主席John Trinder、奥地利地图制图协会主席Wolfgang Kainz、德国科学院院士Meng Liqiu等教授。既报道了国际最先进的有关深度学习、地理信息系统、遥感应用、地图学、人机协作、移动地图系统等相关研究成果，也向世界报道了中国的地球空间智能研究进展、嫦娥三号、四号月球车等令人自豪的原创性成果，同时也对非洲大陆对地观测与地理信息科学的发展进行了关注。
扫描下方二维码可阅读、下载、分享本期专辑全部文章。
欢迎各位专家学者阅读、下载、交流、引用。
■本期专辑目录如下：
01
Building geospatial infrastructure
构建地理空间基础设施
Jack Dangermond & Michael F. Goodchild
文章简介
在过去的半个世纪里，人们对地球空间（科学）技术提出了许多设想。最初，研究人员认为学科研究中的主要问题是地球空间数据处理。地理信息系统的构想作为一个早期的国际共识，应运而生。此后，又陆续出现了空间数据基础设施、数字地球和地球神经网络（a nervous system for the planet）等构想。
随着信息技术的加速发展，需要勾画一个新的蓝图，来反映当今学界对开放、多模式访问、共享、共建、网络化、大数据、人工智能和数据科学等的关注。
本文详细阐述了地理空间基础设施的概念，并认为，如果地理空间技术有助于解决人类面临的问题，地理空间基础设施的建设是必不可少的。
Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today’s focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.
作者简介
Jack Dangermond ESRI公司主席和联合创始人，也是GIS技术、空间分析方法和测地设计领域公认的先驱。1969年，他和妻子在他的家乡加利福尼亚州雷德兰兹成立了ESRI，并坚定不移地支持地理信息科学，认为GIS是人类解决城市、区域、环境和全球问题的最有前途的决策工具之一。他在许多国际会议上发表了主旨演讲，发表了数百篇关于地理信息系统和计算机科学、摄影测量、规划、环境科学和制图等不同领域的论文，并在世界各地作了数千次关于地理信息系统的演讲。
Jack Dangermond is President and co-founder of Esri and a recognized pioneer in GIS technology, spatial analysis methods, and geodesign. In 1969, he and his wife founded Esri in his hometown of Redlands, California and ever since he has been an outspoken proponent of GIS as one of humanity’s most promising decision-making tools for urban, regional, environmental, and global problems. He has delivered keynote addresses at numerous international conferences, published hundreds of papers on GIS and in such diverse fields as computer science, photogrammetry, planning, environmental science, and cartography, and given thousands of presentations on GIS around the world.
Michael F.Goodchild 加州大学圣巴巴拉分校的地理名誉教授。他也是香港理工大学、亚利桑那州国家大学的特聘讲座教授，在世界各地的大学里都有许多名誉职位。他于1965年获得剑桥大学物理学士学位，1969年获得麦克马斯特大学地理博士学位。2002年当选为加拿大国家科学院院士、加拿大皇家学会外籍院士，2006年当选为美国文理学院院士，2010年当选为英国皇家学会外籍院士和相应院士；2007年，他获得了瓦特林·路德奖（Prix Vautrin Lud）----地理学的诺贝尔奖。他的研究兴趣集中在地理信息科学、空间分析和地理数据的不确定性上。
Michael F. Goodchild is Emeritus Professor of Geography at the University of California, Santa Barbara. He is also Distinguished Chair Professor at the Hong Kong Polytechnic University and Research Professor at Arizona State University, and holds many other affiliate, adjunct, and honorary positions at universities around the world. He received his BA degree from Cambridge University in Physics in 1965 and his PhD in geography from McMaster University in 1969. He was elected member of the National Academy of Sciences and Foreign Member of the Royal Society of Canada in 2002, member of the American Academy of Arts and Sciences in 2006, and Foreign Member of the Royal Society and Corresponding Fellow of the British Academy in 2010; and in 2007 he received the Prix Vautrin Lud. His research interests center on geographic information science, spatial analysis, and uncertainty in geographic data.
02
Deep learning for geometric and semantic tasks in photogrammetry and remote sensing
摄影测量与遥感中几何与语义任务的深度学习
Christian Heipke& Franz Rottensteiner
文章简介
在过去的几年里，基于深度学习的人工智能，尤其是基于卷积神经网络的人工智能，在几乎所有与摄影测量和遥感相关的任务中扮演了游戏规则的改变者的角色。结果表明，从图像定位到表面重建、场景分类以及图像序列中的变化检测、目标提取和目标跟踪与识别的整个摄影测量处理链中的许多项目都取得了部分显著的改进。
本文总结了摄影测量学和遥感学的深入学习基础，并举例说明了汉诺威莱布尼茨大学摄影测量和地理信息研究所在这一令人兴奋和快速发展的研究和发展领域正在开展的不同项目。
During the last few years, artificial intelligence based on deep learning, and particularly based on convolutional neural networks, has acted as a game changer in just about all tasks related to photogrammetry and remote sensing. Results have shown partly significant improvements in many projects all across the photogrammetric processing chain from image orientation to surface reconstruction, scene classification as well as change detection, object extraction and object tracking and recognition in image sequences. This paper summarizes the foundations of deep learning for photogrammetry and remote sensing before illustrating, by way of example, different projects being carried out at the Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, in this exciting and fast moving field of research and development.
作者简介
Christian Heipke 汉诺威莱布尼兹大学摄影测量和遥感学教授，目前他领导着一个大约25人的研究团队。他的专业兴趣包括摄影测量学、遥感、图像解译以及它们与计算机视觉和地理信息系统的联系。他撰写（合著）了300多篇科学论文，其中70多篇发表在同行评议的国际期刊上。他是1992年ISPRS Otto von Gruber奖、2012年ISPRS Fred Doyle奖和2013年ASPR摄影测量（Fairchild）奖的获得者。他加入了许多学术团体。2004—2009年，他担任EuroSDR副总裁。2011—2014年，他担任德国大地测量委员会（DGK）主席，2012—2016年担任ISPRS秘书长。目前是国际摄影测量与遥感学会（ISPRS）的主席。
Christian Heipke is a professor of photogrammetry and remote sensing at Leibniz University Hannover, where he currently leads a group of about 25 researchers. His professional interests comprise all aspects of photogrammetry, remote sensing, image understanding and their connection to computer vision and GIS. His has authored or coauthored more than 300 scientific papers, more than 70 of which appeared in peer-reviewed international journals. He is the recipient of the 1992 ISPRS Otto von Gruber Award, the 2012 ISPRS Fred Doyle Award, and the 2013 ASPRS Photogrammetric (Fairchild) Award. He is an ordinary member of various learnt societies. From 2004 to 2009, he served as vice president of EuroSDR. From 2011-2014 he was chair of the German Geodetic Commission (DGK), from 2012-2016 ISPRS Secretary General. Currently he serves as ISPRS President.
Franz Rottensteiner 汉诺威莱布尼兹大学（LUH）副教授，“摄影测量图像分析”研究小组组长。他在奥地利维也纳技术大学（TUW）取得博士学位。他的研究方向包括图像定位、图像分类、基于图像和点云的自动目标检测和重建以及遥感数据的变化检测等方面。在2008年加入LUH之前，他分别在TUW和澳大利亚的新南威尔士大学和墨尔本大学工作。他撰写或合著了150多篇科学论文，其中36篇发表在同行评议的国际期刊上。他于2004年获得奥地利大地测量委员会的Karl Rinner奖，2017年获得Leica Geosystems公司赞助的Carl Pulfrich Award for Photogrammetry。自2011年起，他一直是Photogrammetrie Fernerkundung Geoinformation的副主编。作为ISPRS第II/4工作组主席，他发起并实施了ISPRS城市目标检测和三维建筑重建基准。
Franz Rottensteiner is an Associate Professor and leader of the research group “Photogrammetric Image Analysis” at Leibniz University Hannover. He received the Dipl.-Ing. degree in surveying and the Ph.D. degree and venia docendi in photogrammetry, all from Vienna University of Technology (TUW), Vienna, Austria. His research interests include all aspects of image orientation, image classification, automated object detection and reconstruction from images and point clouds, and change detection from remote sensing data. Before joining LUH in 2008, he worked at TUW and the Universities of New South Wales and Melbourne, respectively, both in Australia. He has authored or coauthored more than 150 scientific papers, 36 of which have appeared in peer-reviewed international journals. He received the Karl Rinner Award of the Austrian Geodetic Commission in 2004 and the Carl Pulfrich Award for Photogrammetry, sponsored by Leica Geosystems, in 2017. Since 2011, he has been the Associate Editor of the ISI-listed journal “Photogrammetrie Fernerkundung Geoinformation”. Being the Chairman of the ISPRS Working Group II/4, he initiated and conducted the ISPRS benchmark on urban object detection and 3D building reconstruction.
03
Assessing environmental impacts of urban growth using remote sensing
利用遥感技术评估城市增长的环境影响
John Trinder &Qingxiang Liu
文章简介
本文研究了中国武汉和澳大利亚悉尼西部两个城市的城市环境中土地利用的变化。由于混合像元是Landsat等中等分辨率图像的特征，当用于城市区域分类时，利用人工神经网络预测的小波方法，根据一个像素范围内城市地表覆盖的变化，利用MESMA和SRM相结合的方法提取分类分数，生成更高空间分辨率的分类图。
对这两个城市30年的Landsat图像进行了植被、建筑物、土壤和水的分类。然后使用Indifrag软件对分类进行处理，以评估30年来建筑物、植被、水和土壤面积变化所造成的分区。比较了两个城市的植被、建筑物、水和土壤的分区，并将植被百分比与建议的城市绿地比例进行了比较，以利于居民的健康和福祉。对武汉和悉尼城市化进程中生态系统服务价值的变化进行了评估。研究人员正在评估联合国城市可持续发展目标（SDG），以更好地实现城市的可持续性。
This paper provides a study of the changes in land use in urban environments in two cities, Wuhan, China and western Sydney in Australia. Since mixed pixels are a characteristic of medium resolution images such as Landsat, when used for the classification of urban areas, due to changes in urban ground cover within a pixel, Multiple Endmember Spectral Mixture Analysis (MESMA) together with Super-Resolution Mapping (SRM) are employed to derive class fractions to generate classification maps at a higher spatial resolution using an Artificial Neural Network (ANN) predicted Wavelet method. Landsat images over the two cities for a 30-year period, are classified in terms of vegetation, buildings, soil and water. The classifications are then processed using Indifrag software to assess the levels of fragmentation caused by changes in the areas of buildings, vegetation, water and soil over the 30 years. The extents of fragmentation of vegetation, buildings, water and soil for the two cities are compared, while the percentages of vegetation are compared with recommended percentages of green space for urban areas for the benefit of health and well-being of inhabitants. Changes in Ecosystem Service Values (ESVs) resulting from the urbanization have been assessed for Wuhan and Sydney. The UN Sustainable Development Goals (SDG) for urban areas are being assessed by researchers to better understand how to achieve the sustainability of cities.
作者简介
John Trinder 1965-1999年受雇于澳大利亚新南威尔士大学，1990-1999年升任教授和校长，2013年当选新南威尔士州名誉研究员。他目前担任新南威尔士大学土木与环境工程学院名誉客座教授。John Trinder 教授在新南威尔士州从事教学和研究大约55年，专长是摄影测量、遥感和空间信息。他的研究兴趣始终包括这些领域以及它们对研究环境影响的贡献。他曾任国际摄影测量和遥感学会（ISPRS）主席（2000-2004年），目前是ISPRS名誉会员。
John Trinder PhD (NSW) MSc (ITC) was employed at the University of NSW, Australia, from 1965-1999, progressing to Professor and Head of the School from 1990-1999 and was elected Honorary Fellow of UNSW in 2013. He currently holds the position of Visiting Emeritus Professor in the School of Civil and Environmental Engineering at the UNSW. John has undertaken teaching and research at UNSW for about 55 years, specializing in Photogrammetry and Remote Sensing and spatial information. He maintains an interest in these areas, and their contributions to studying environmental impacts. He was President (2000-2004) of the International Society for Photogrammetry and Remote Sensing (ISPRS) and is currently an Honorary Member.
Qingxiang Liu 2013年本科毕业于武汉大学，2018年获得新南威尔士大学地理信息工程博士学位。她曾从事大规模湿地测绘、海岸线变化监测、地形几何学和矿区植被恢复监测的遥感工作。她目前的研究方向是环境遥感研究和应用。
Qingxiang Liu received her PhD degree in Geomatics Engineering from the University of New South Wales in 2018. She finished undergraduate study at Wuhan University in 2013. She has worked on remote sensing for large-scale wetland mapping, shoreline change monitoring, landform geometry and vegetation rehabilitation monitoring for mining sites. Her current research interests include remote sensing applications to environmental studies and GIS.
04
Advances of geo-spatial intelligence at LIESMARS
地球空间智能研究进展
——以武汉大学测绘遥感信息工程国家重点实验室为例
Deren Li & Zhenfeng Shao & Ruiqian Zhang
文章简介
计算能力的增强、学习算法的成熟以及应用场景的丰富性，使得人工智能在解决地球空间信息科学（GSIS）问题时越来越具有吸引力。其中包括图像匹配、图像目标检测、变化检测、图像检索以及用于生成各种类型的数据模型。
本文讨论了人工智能与地理信息系统在区域调整、大数据库图像搜索与发现、自动变化检测、异常检测等方面的联系与综合，说明人工智能可以与地理信息系统集成。最后，介绍了对地观测大脑和智能地球空间服务（SGSS）的概念，以期推动地球观测系统向更广阔的应用领域发展。
The enhancement of computing power, the maturity of learning algorithms, and the richness of application scenarios make Artificial Intelligence (AI) solution increasingly attractive when solving Geo-spatial Information Science (GSIS) problems. These include image matching, image target detection, change detection, image retrieval, and for generating data models of various types. This paper discusses the connection and synthesis between AI and GSIS in block adjustment, image search and discovery in big databases, automatic change detection, and detection of abnormalities, demonstrating that AI can integrate GSIS. Moreover, the concept of Earth Observation Brain and Smart Geo-spatial Service (SGSS) is introduced in the end, and it is expected to promote the development of GSIS into broadening applications.
作者简介
李德仁 武汉大学测绘遥感信息工程国家重点实验室教授。1991年当选为中国科学院院士，1994年当选为中国工程院院士。1963年和1981年分别在武汉测绘技术大学获得学士学位和硕士学位。1985年，他在德国斯图加特大学获得博士学位。2008年，他被授予瑞士苏黎世大学荣誉博士称号。
Deren Li is a professor in State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University. He was selected as a member of Chinese Academy of Sciences in 1991 and a member of Chinese Academy of Engineering in 1994. He got his bachelor and master degrees from Wuhan Technical University of Surveying and Mapping respectively in 1963 and 1981. In 1985, he got his doctor degree from University of Stuttgart, Germany. He was awarded the title of honorary doctor from ETH Zürich, Switzerland in 2008.
邵振峰 武汉大学测绘遥感信息工程国家重点实验室教授。1998年和2001年分别在武汉测绘技术大学获得学士学位和硕士学位，2004年获得武汉大学博士学位。他的研究兴趣主要集中在城市遥感应用上。具体研究方向包括高分辨率遥感图像处理与分析、从数字城市到智能城市、海绵城市的关键技术与应用。
Zhenfeng Shao is a professor in State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University. He got his bachelor and master degrees from Wuhan Technical University of Surveying and Mapping respectively in 1998 and 2001, and received the PhD degree from Wuhan University in 2004. His research interest mainly focuses on urban remote sensing applications. The specific research directions include high-resolution remote sensing image processing and analysis, key technologies and applications from digital cities to smart cities and sponge cities.
Ruiqian Zhang 武汉大学遥感与信息工程学院的博士生。2015年获得武汉大学遥感科学与技术学士学位。目前，她正在武汉大学遥感与信息工程学院攻读摄影测量与遥感博士学位。她的研究兴趣包括图像/视频处理和目标检测。
Ruiqian Zhang is a PhD student in School of Remote Sensing and Information Engineering in Wuhan University. She received the bachelor degree in remote sensing science and technology from Wuhan University, Wuhan, China in 2015. She is currently working toward the Ph.D. degree in photogrammetry and remote sensing from School of Remote Sensing and Information Engineering from Wuhan University. Her research interests include image/video processing and object detection.
05
Cartography and the others – aspects of a complicated relationship
地图学及其他——复杂关系的方方面面
Wolfgang Kainz
文章简介
地图可视化已经有几千年的历史了，并产生了大量不同的地图投影和地图产品。然而，地图学作为一门独立的科学，在大约100年前才建立起来，它在空间学科中的地位有时会受到科学界的挑战。它是一门建立在地图制作、地球仪制作和地图投影开发的悠久传统基础上的年轻的学科。地图和与地图相关的可视化在许多其他空间学科，如地理学和大地测量学中发挥着重要和不可或缺的作用。地图学与这些传统学科以及较新的摄影测量学和遥感学科有许多重叠。
本文回顾了人类历史上空间和时间概念的基本方面，地图学从地图制作技术到空间科学的历史发展，突出了该学科发展史上的主要里程碑。地图学作为一门年轻的科学，在20世纪末面临着重大的技术发展，在地图学究竟是什么，以及它如何与其他空间科学，特别是地理信息系统的关系方面，经历了几次危机。
本文讨论了地图学面临的主要危机和错误认识，并定义了地图学的三大科学支柱。讨论了地图学与相邻学科的关系，指出了地图学相对于其他学科的地位。最后，讨论了科学地图学未来的发展方向。
Cartographic visualizations have been known for thousands of years and have brought forth a wealth of different map projections and cartographic products. Yet, cartography as an independent science has been established only about 100 years ago and sometimes its position among the spatial disciplines is challenged by the scientific community. In this respect it is a young science based on a very long tradition of map making, globe production, and the development of map projections. Maps and map related visualizations play an important and indispensable role in many other spatial disciplines such as geography and geodesy. Cartography has many overlaps with these traditional disciplines as well as with the more recent ones of photogrammetry and remote sensing. This paper reviews fundamental aspects of the conception of space and time throughout human history, the historic development of cartography from a technique of map making to a spatial science, highlighting major milestones in the history of the discipline. As a young science and confronted with major technological developments in the late 20th century cartography underwent several crises as to what exactly is cartography and how it relates to other spatial sciences, in particular to geographic information systems. Major pitfalls and misconceptions are discussed and the three major scientific pillars of cartography are identified. The relationships of cartography with neighboring disciplines are discussed and the position of cartography vis a vis the others is delineated. Finally, desirable future developments of scientific cartography are discussed.
作者简介
Wolfgang Kainz 奥地利维也纳大学地理和区域研究系的制图和地理信息科学的教授，他主要从事地理信息系统的数学原理、地理信息系统中的不确定性和拓扑结构方面的研究和教学。
Wolfgang Kainz is a full professor of cartography and geo-information science at the Department of Geography and Regional Research of the University of Vienna, Austria, where he conducts research and teaching on the mathematical principles of GIS, uncertainty and topology in GIS.
06
An IEEE value loop of human-technology collaboration in geospatial information science
地球空间信息科学中人机协作的Informing—Enabling—Engaging—Empowering价值环
Liqiu Meng
文章简介
作为大数据时代的两大数字化主流，地球感知和社会感知正向着创造一个语义丰富的数字地球的集成系统而不断靠拢。随着人工智能技术的飞速发展，这种融合不可避免地带来了一些变革。
一方面，从原始数据到产品和服务的增值链正在成为由四个连续阶段组成的增值环——通知、启用、参与和授权（Informing—Enabling—Engaging—Empowering，IEEE）。每个阶段本身都是一个动态循环。另一方面，“人与技术”的关系升级为改变游戏规则的“人与技术”合作。
信息循环本质上是由人类和技术之间无所不在的相互作用所形成的，它们是平等的伙伴、共同学习者和新价值观的共同创造者。
本文对IEEE循环各个阶段中人与技术的相互作用和责任进行了分析性的回顾，旨在促进对地球空间信息科学技术现状的全面理解。同时，作者还提出了人与技术相互交织协作所面临的一些挑战。转变为增长心态可能需要时间来实现和巩固。大规模语义数据集成的研究工作刚刚起步。地理视觉分析方法的用户经验远未被系统地研究。最后，在处理语义丰富的数字地球时，伦理问题不仅包括与侵犯隐私、侵犯版权、滥用版权有关的敏感问题，还有如何使技术尽可能地为人类所控制和理解，以及如何将技术精神保持在其建设性的社会影响范围内的问题。
Geosensing and social sensing as two digitalization mainstreams in big data era are increasingly converging toward an integrated system for the creation of semantically enriched digital Earth. Along with the rapid developments of AI technologies, this convergence has inevitably brought about a number of transformations. On the one hand, value-adding chains from raw data to products and services are becoming value-adding loops composed of four successive stages – Informing, Enabling, Engaging and Empowering (IEEE). Each stage is a dynamic loop for itself. On the other hand, the “human versus technology” relationship is upgraded toward a game-changing “human and technology” collaboration. The information loop is essentially shaped by the omnipresent reciprocity between humans and technologies as equal partners, co-learners and co-creators of new values.
The paper gives an analytical review on the mutually changing roles and responsibilities of humans and technologies in the individual stages of the IEEE loop, with the aim to promote a holistic understanding of the state of the art of geospatial information science. Meanwhile, the author elicits a number of challenges facing the interwoven human-technology collaboration. The transformation to a growth mind-set may take time to realize and consolidate. Research works on large-scale semantic data integration are just in the beginning. User experiences of geovisual analytic approaches are far from being systematically studied. Finally, the ethical concerns for the handling of semantically enriched digital Earth cover not only the sensitive issues related to privacy violation, copyright infringement, abuse, etc. but also the questions of how to make technologies as controllable and understandable as possible for humans and how to keep the technological ethos within its constructive sphere of societal influence.
作者简介
孟立秋 慕尼黑工业大学地图学教授，德国国家科学院院士。她是国际制图协会的副主席。她的研究兴趣包括地理数据集成、移动地图服务、多模式导航算法、地理视觉分析以及社会感知中的伦理问题。
Liqiu Meng is a professor of Cartography at the Technical University of Munich, and a member of German National Academy of Sciences. She is serving as Vice President of the International Cartographic Association. Her research interests include geodata integration, mobile map services, multimodal navigation algorithms, geovisual analytics, and ethical concerns in social sensing..
07
Analysis of mobility data – A focus on Mobile Mapping Systems
移动性数据分析——以移动地图系统为中心
Monika Sester
文章简介
越来越多的设备可以捕捉到移动物体的位置（以及其他环境信息），从而产生了大量多样的移动数据。为了获得有关对象、对象行为或对象环境的重要信息，需要进行自动分析。
本文以德国汉诺威莱布尼兹大学制图和地理信息学研究所为基础，着重介绍了当前在流动性数据分析方面的研究问题。同时着重介绍了移动地图车信息的分析与开发。
The increasing availability of devices to capture the position of moving objects (and other environmental information) leads to a very large amount and variety of mobility data. In order to obtain important information about the objects, their behavior or the environment of the objects, an automatic analysis is required. This article highlights current research questions in the context of the analysis of mobility data and presents them on the basis of work carried out at the Institute of Cartography and Geoinformatics (ikg) at Leibniz University of Hannover, Germany. A focus is put on the analysis and exploitation of information from Mobile Mapping vehicles.
作者简介
Monika Sester 汉诺威莱布尼兹大学全职教授。于斯图加特大学获得博士学位。她的研究方向是空间数据分析的自动化，在支持数据解析、综合和融合等许多领域内得到应用。
Monika Sester is a full professor at Leibniz University Hanover. She received her PhD and her habilitation from the University of Stuttgart. Her research interests are the automation of spatial data analysis, applied to many fields, e.g. data interpretation, generalization and fusion.
08
Toward a unified theoretical framework for photogrammetry
走向统一的摄影测量学理论框架
Jie Shan，Zhihua Hu，Pengjie Tao，Lei Wang，Shenman Zhang ，Shunping Ji
文章简介
摄影测量的目的是从影像中获取信息。随着传感技术和计算技术的日益密切的相互作用，摄影测量学的理论框架在过去几十年中经历了一场演变性的变化。从传统上不同但又相关的多个学科，包括计算机视觉、摄影测量、计算机图形学、模式识别、遥感和机器学习等，都取得了许多理论进展和实际应用。这在理论和实践上都逐步拓展了传统摄影测量的边界。
本文介绍了一个新的整体的理论框架来描述各种摄影测量任务和解决方案。在这个框架下，摄影测量通常被视为一个统一优化问题的逆向成像过程。根据需要优化确定的变量，摄影测量任务主要分为图像空间任务、图像对象空间任务和对象空间任务，每一个任务都是一般公式的特例。本文针对每个任务提出了具有代表性的解决方法。根据本文工作，倡导摄影测量学研究和学习的范式转变已经十分必要，迫在眉睫。
The objective of photogrammetry is to extract information from imagery. With the increasing interaction of sensing and computing technologies, the fundamentals of photogrammetry have undergone an evolutionary change in the past several decades. Numerous theoretical progresses and practical applications have been reported from traditionally different but related multiple disciplines, including computer vision, photogrammetry, computer graphics, pattern recognition, remote sensing and machine learning. This has gradually extended the boundary of traditional photogrammetry in both theory and practice. This paper introduces a new, holistic theoretical framework to describe various photogrammetric tasks and solutions. Under this framework, photogrammetry is generally regarded as a reversed imaging process formulated as a unified optimization problem. Depending on the variables to be determined through optimization, photogrammetric tasks are mostly divided into image space tasks, image-object space tasks and object space tasks, each being a special case of the general formulation. This paper presents representative solution approaches for each task. With this effort, we intend to advocate an imminent and necessary paradigm change in both research and learning of photogrammetry.
作者简介
单 杰 美国普渡大学Lyles土木工程学院教授，研究方向包括从图像和点云中提取和重建物体，城市遥感，以及时空数据和语义数据的挖掘。
Jie Shan is a Professor with the Lyles School of Civil Engineering, Purdue University, USA. His research interests include object extraction and reconstruction from images and point clouds, urban remote sensing, and data mining of spatial, temporal, and semantic data.
Zhihua Hu 摄影测量和遥感专业博士生。他目前的研究方向包括网格细化和多视图图像三维重建。
Zhihua Hu is working toward PhD degree in photogrammetry and remote sensing. His current research interests include mesh refinement, and multi-view images 3D reconstruction.
Pengjie Tao副研究员。他的研究方向包括摄影测量学、光学图像和激光雷达点的配准以及多视点图像的三维重建。
Pengjie Tao is currently an associate research fellow. His research interests include photogrammetry, registration of optical images and LiDAR points, and multi-view images 3D reconstruction.
Lei Wang 摄影测量和遥感专业博士生，研究方向为三维计算机视觉，机器/深度学习和三维感知。
Lei Wang is working toward PhD degree in photogrammetry and remote sensing. His research interests include 3D computer vision, machine/deep learning, and 3D understanding.
Shenman Zhang 摄影测量和遥感专业博士生，研究方向为点云配准和建筑物重建。
Shenman Zhang is pursuing toward PhD degree in photogrammetry and remote sensing. His current research interests include point clouds registration, and building reconstruction.
季顺平 武汉大学遥感信息工程学院教授。主要研究方向为摄影测量，遥感图像处理，移动制图系统和机器学习。
Shunping Ji is a Professor with the School of Remote Sensing and Information Engineering, Wuhan University. His research interests include photogrammetry, remote sensing image processing, mobile mapping system, and machine learning.
09
Geospatial technologies for Chang’e-3 and Chang’e-4 lunar rover missions
嫦娥三号和嫦娥四号月球车任务的地球空间技术
Kaichang Di,Zhaoqin Liu,Wenhui Wan,Man Peng,Bin Liu,Yexin Wang,Sheng Gou，Zongyu Yue
文章简介
本文简要介绍了嫦娥四号月球探测器的研制和应用情况。利用摄影测量测绘技术，在着陆前利用轨道影像生成具有米级分辨率的着陆场地形产品，并在着陆后实时生成厘米级分辨率的地形产品。在着陆后立即使用下降图像和轨道底图，利用视觉定位技术确定两个着陆器的位置。在地面作业期间，基于视觉定位的月球车定位是在每个航路点使用导航摄像头图像进行的。地形分析和月球车定位结果直接支持航路点到航路点的路径规划、科学目标选择和科学研究。开发了基于GIS的数字地图制图系统，用于支持移动机器人遥操作。
This paper presents a brief overview of the geospatial technologies developed and applied in Chang’e-3 and Chang’e-4 lunar rover missions. Photogrammetric mapping techniques were used to produce topographic products of the landing site with meter level resolution using orbital images before landing, and to produce centimeter-resolution topographic products in near real-time after landing. Visual positioning techniques were used to determine the locations of the two landers using descent images and orbital basemaps immediately after landing. During surface operations, visual-positioning-based rover localization was performed routinely at each waypoint using Navcam images. The topographic analysis and rover localization results directly supported waypoint-to-waypoint path planning, science target selection and scientific investigations. A GIS-based digital cartography system was also developed to support rover teleoperation.
作者简介
邸凯昌 中国科学院遥感与数字地球研究所（RADI）教授。他的研究兴趣包括行星摄影测量和遥感、视觉定位和导航以及行星科学。他是国际摄影测量和遥感学会委员会间第三/第二工作组“行星遥感和制图”的现任主席。
Kaichang Di is a professor at Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences. His research interests include planetary photogrammetry and remote sensing, visual localization and navigation, and planetary science. He is currently the chair of Inter-Commission Working Group III/II “Planetary Remote Sensing and Mapping” of International Society for Photogrammetry and Remote Sensing.
Zhaoqin Liu 中国科学院遥感与数字地球研究所（RADI）副教授。研究方向为行星制图和行星GIS。
Zhaoqin Liu is an associate professor at RADI. His research interests include planetary mapping, and planetary GIS.
Wenhui Wan 中国科学院遥感与数字地球研究所（RADI）助理教授。研究方向为视觉定位与机器人导航。
Wenhui Wan is an assistant professor at RADI. His research interests include visual localization and robot navigation,
Man Peng 中国科学院遥感与数字地球研究所（RADI）副教授。研究方向为行星摄影测量和地形分析。
Man Peng is an associate professor at RADI. Her research interests include planetary photogrammetry, and topographic analysis.
Bin Liu 中国科学院遥感与数字地球研究所（RADI）副教授。研究方向为轨道影像的几何建模和高精度地形测绘。
Bin Liu is an associate professor at RADI. His research interests include geometric modeling orbital imagery, and high-precision topographic mapping.
Yexin Wang 中国科学院遥感与数字地球研究所（RADI）副教授。研究方向为行星制图和目标识别。
Yexin Wang is an associate professor at RADI. Her research interests include planetary mapping and target recognition.
Sheng Gou 中国科学院遥感与数字地球研究所（RADI）助理教授。研究方向为利用高光谱数据对行星矿物进行反演以及行星地质学。
Sheng Gou is an assistant professor at RADI. His research interests include planetary mineral retrieval using hyperspectral data, and planetary geology.
Zongyu Yue 中国科学院遥感与数字地球研究所（RADI）教授。研究方向为行星遥感和行星科学。
Zongyu Yue is a professor at RADI. His research interests include planetary remote sensing and planetary science.
10
Review on graph learning for dimensionality reduction of hyperspectral image
高光谱图像降维的图形学习
Liangpei Zhang & Fulin Luo
文章简介
图学习是分析数据内在特性的一种有效方法。它在数据降维和分类等领域得到了广泛的应用。本文主要研究基于图学习的高光谱图像降维问题。
本文首先回顾了图学习的发展及其在高光谱图像中的应用。然后重点讨论了几种有代表性的图学习方法，包括两种流形学习方法、两种稀疏图学习方法和两种超图学习方法。对于流形学习，我们分析了两种经典的流形学习方法：邻域保持嵌入和局部保持投影，它们可以转化为图的形式。对于稀疏图，我们引入了稀疏保持图嵌入和基于稀疏图的判别分析，它可以自适应地揭示数据结构来构造图。对于超图学习，我们回顾了二元超图和判别超拉普拉斯投影，它们可以表示数据的高阶关系。
Graph learning is an effective manner to analyze the intrinsic properties of data. It has been widely used in the fields of dimensionality reduction and classification for data. In this paper, we focus on the graph learning-based dimensionality reduction for a hyperspectral image. Firstly, we review the development of graph learning and its application in a hyperspectral image. Then, we mainly discuss several representative graph methods including two manifold learning methods, two sparse graph learning methods, and two hypergraph learning methods. For manifold learning, we analyze neighborhood preserving embedding and locality preserving projections which are two classic manifold learning methods and can be transformed into the form of a graph. For sparse graph, we introduce sparsity preserving graph embedding and sparse graph-based discriminant analysis which can adaptively reveal data structure to construct a graph. For hypergraph learning, we review binary hypergraph and discriminant hyper-Laplacian projection which can represent the high-order relationship of data.
作者简介
张良培 1982年获得湖南师范大学物理学士学位，1988年获得中国科学院西安光学与精密力学研究所光学硕士学位，1998年获得武汉测绘科技大学摄影测量与遥感博士学位。现任武汉大学测绘遥感信息工程国家重点实验室遥感所主任。中国教育部长江学者”讲座教授，中国国家科学技术部 2011-2016年中国国家重点基础研究项目中国遥感项目首席科学家。他的研究兴趣包括高光谱遥感、高分辨率遥感、图像处理和人工智能。
Liangpei Zhang received the B.S. degree in physics from Hunan Normal University, Changsha, China, in 1982, the M.S. degree in optics from the Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China, in 1988, and the Ph.D. degree in photogrammetry and remote sensing from Wuhan University, Wuhan, China, in 1998. He is currently the Head of the Remote Sensing Division with the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University. He is also a “Chang-Jiang Scholar” Chair Professor appointed by the Ministry of Education of China, Beijing, China, and a Principal Scientist for the China State Key Basic Research project 2011-2016 appointed by the Ministry of the National Science and Technology of China to lead the remote sensing program in China. His research interests include hyperspectral remote sensing, high-resolution remote sensing, image processing, and artificial intelligence.
罗甫林 2016年和2013年分别获得重庆大学仪器科学与技术博士学位和硕士学位。现任武汉大学测绘遥感信息工程国家重点实验室副研究员。他的研究方向是高光谱图像分类、图像处理、稀疏表示和流形学习。
Fulin Luo received the Ph.D and M.S. degree in Instrument Science and Technology from Chongqing University, Chongqing, China, in 2016 and 2013, respectively. He is currently an Associate Researcher with the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University. His research interests are hyperspectral image classification, image processing, sparse representation and manifold learning in general.
11
The status of Earth Observation (EO) & Geo-Information Sciences in Africa – trends and challenges
非洲对地观测与地球信息科学的现状——趋势与挑战
Tsehaie Woldai
文章简介
过去20年来，非洲在天基技术方面取得了缓慢但稳定的进展。本文建立在一份调查问卷的结果的基础上，主要包括对非洲的工业和大学、对地观测和地理信息科学方面的服务和教育/培训，并结合文献综述和个案调查，反映了对公共部门（政府部委）、学术机构（大学/学院/国家或区域研究中心）以及空间机构和私营部门公司的乐观情绪。这些部门相互交织，对于创造有利环境，解决各种紧迫的优先事项，如创造就业、减贫和可持续的资源管理等，是至关重要的。
调查结果表明，机构和市场细分的数量有所增加。目前，非洲28个国家有90多个学术机构和53个国家空间机构。在53个国家空间机构中，11个非洲国家已经将总共36颗卫星送入轨道，预计到2021年第一季度将再发射5颗；到2025年，还将发射5颗；非洲发射46颗卫星，这是10年前无法预料的。
此外，目前在6个非洲国家和17个具有地理信息技术专门知识的国家科学协会或学会设有10个接收和跟踪站。2019年对私营公司的最新调查表明，在地球观测和地理信息科学公司中，约有4110人在130家（非洲共229家）地球观测和地理信息科学公司中工作。正在进行的调查表明，从事天基数据处理和地理信息技术及其相关派生产业的人数大道了15 000多人，到2025年这一数字将有望超过10万。
Over the last 20 years, Africa has witnessed a slow but steady advancement in space-based technologies as they are increasingly recognized as an essential tool for decision-making that can leapfrog African development. A critical review on the outcome of a survey questionnaire focused on African private sector industries and universities, services and education/training in EO and Geo-Information Sciences, combined with literature review, and personal contacts reveal optimism for success in four sectors. These include the public sector (Government ministries and departments); Academic institutions (universities/colleges/national or regional centers); and space agencies and private sector companies. These sectors are intertwined and fundamental for creating an enabling environment for solutions to a broad spectrum of pressing priorities: job creation, poverty alleviation, and sustainable resource management. The result shows that there is an uptake in the number of institutions and market segments created. To date, there are more than 90 academic institutions and over 53 national space agencies in 28 countries. Within the 53 national space agencies, 11 African countries have already launched a total of 36 satellites into orbit, and additional five are expected by the first quarter of 2021; another five by 2025; thus, amounting to 46 satellites not foreseen ten years ago. In addition, there are now ten receiving and tracking stations in six African countries and 17 scientific National Associations or Societies with specialized expertise in Geo-Information technologies. The updated survey on the private sector in 2019 ascertained that around 4110 people are working in 130 of the 229 EO and Geo-Information Science companies identified in Africa. Ongoing investigations reiterate that companies dealing with space-based datasets and Geo-Information Sciences together with the private spin-off companies today absorb more than 15,000 people and the assumption is that this number is going to exceed 100,000 by the year 2025.
作者简介
Tsehaie Woldai 在ITC工作多年。现任南非约翰内斯堡威特沃特斯兰德大学地球科学学院地质遥感客座教授，中国武汉大学测绘遥感信息工程国家重点实验室遥感客座教授。Woldai是非洲环境遥感协会（AARSE）的创始人和前任主席，非洲减少灾害风险大学网络（UNEDRA）协调员，非洲科学院院士，非洲地质学会会员，20多个著名奖项的获得者；参与了许多ISPRS委员会和工作组（担任主席/副主席/秘书）；作为主要或共同调查员参与了40多个国家/国际咨询方案和20多个国际研究。
Tsehaie Woldai has worked for many years at the Faculty of Geo-Information Science and Earth Observation (ITC). Currently, he is a Visiting Professor of Geological Remote Sensing at the School of Geosciences, University of the Witwatersrand, Johannesburg, South Africa and a Visiting Professor of remote sensing at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, China. Woldai is the Founder and Past President of the African Association of Remote Sensing of the Environment (AARSE), Coordinator of the University Network for Disaster Risk Reduction in Africa (UNEDRA), a fellow of the African Acadamy of Sciences, a Fellow of the African Geological Society, and a winner of over 20 prestigious awards; involved in many ISPRS Commissions and Working Group (as Chairman/Vice Chairman/Secretary); engaged in over 40 national/international Advisory Programmes and over 20 international research as Principle or co-investigator.
关于 Geo-spatial Information Science
GSIS 采用开放获取形式，就是大家所说的开源期刊/OA期刊（Open Access），文章一经发表，可马上被全球读者免费全文下载，这种模式可以让你的文章有更多的曝光度。
目前，在GSIS发表文章不需缴纳审稿费、发表费等任何费用，完全免费。欢迎广大测绘遥感学科的科研工作者阅读和赐稿。如果您有需要抢首发权的高质量文章，可与我们联系gsis@whu.edu.cn，主编/国际副主编亲自为您处理，编辑部提供随时随地的疑问解答与状态跟踪。
期刊官网：https://www.tandfonline.com/tgsi
投稿网址：https://rp.tandfonline.com/submission/create?journalCode=tgsi
长按二维码 关注GSIS微信号
GSIS-WHU
Geo-Spatial Information Science
SCIE数据库收录期刊
中国最具国际影响力学术期刊
中国科技期刊卓越行动计划入选期刊
https://www.tandfonline.com/tgsi
推特账号｜GSISOffice
点击下方阅读原文获取本期特刊全文