第一届“智慧森林”国际研讨会将于9月5日-7日在埃及开罗举办。“智慧森林”研讨会着重探讨多模态遥感、人工智能与机器人等前沿学科交叉融合在森林生态系统评估和监测中的应用原理、方法和实践，展示多尺度森林评估与监测的新路径，支持并加强对森林生态系统的理解，为实现森林资源智能化有效管理提供高效手段。
本次研讨会将举办5场专题报告，从深度学习大尺度森林监测、多尺度系统与方法、农林监测与评估、近距离遥感传感器与方案、单木尺度建模与分析等几个方面探讨数据获取、预处理、信息提取以及森林遥感应用的最新发展。来自中国、美国、芬兰、意大利、德国、瑞士、智利等国的专家学者将围绕智能遥感深度学习框架与模型设计、ICESAT-2 ATL08星载激光数据精度、高时空分辨率激光雷达白桦生长动态监测、深度学习卫星遥感森林监测、传感和数据分析技术推动数字林业、GPT林业探索等内容深入开展讨论，为推进全球可持续发展、构建人类命运共同体提供理论和技术支撑。
本届“智慧森林”国际研讨会由国际摄影测量和遥感学会（the International Society of Photogrammetry and Remote Sensing, ISPRS）遥感数据处理与理解、数据质量与传感器测评、农业与生态系统遥感等工作组共同组织。武汉大学多源感知与认知研究组梁欣廉教授担任会议主席。
本次研讨会邀请国际著名学者进行三场主题演讲：
龚健雅教授——面向遥感智能解译的专用深度学习框架与基础模型 （A Special Deep Learning Framework and Foundation Model for Intelligent Interpretation of Remote Sensing）
龚健雅，中国科学院院士，武汉大学教授，国家高层次人才、国家自然科学基金人才项目获得者、973项目首席科学家、国家自然科学基金创新群体学术带头人、国家测绘局科技高层次人才、国务院第六、七届学科评议组测绘学科组召集人。他曾担任国家测绘地理信息局信息工程测绘与遥感重点实验室主任，武汉大学遥感信息工程学院院长，国际摄影测量与遥感学会第六分委会主席，中国海外地理信息科学学会会长。他目前担任亚洲地理信息系统协会秘书长，中国《测绘学报》副主编，以及《大地测量与地理信息科学》期刊主编。
龚健雅教授主要从事遥感和地理信息系统的研究，承担了40多项国家和省部级科研项目，出版专著和教材13部，发表论文500多篇。获国家科技进步创新团队奖1项、国家科技进步奖一等奖1项、国家科技进步二等奖4项、省部级特等奖3项及一等奖7项、以及国际摄影测量与遥感学会（ISPRS）Dolezal成就奖。
摘要：人工智能在许多领域迅速发展并得到广泛应用。在遥感图像智能解译方面也取得了重要的研究进展，并在一些场景中得以应用。然而，大规模的遥感图像智能解译商业应用尚不够成熟。报告分析了遥感图像智能解译领域现存问题，包括样本数量不足、类别不完整、缺乏标准和规范，以及现有深度学习网络框架难以满足多源遥感图像智能解译的需求。报告介绍他团队在遥感智能解译方面的最新研究成果，包括多样化且标准化的样本集LuojiaSET的设计与研究进展，以及专用于遥感智能解译的深度学习网络框架LuojiaNET以及基于LuojiaNET的基础模型及其在遥感智能解译中的应用。
2. Christian Heipke教授, 使用深度学习的空间森林监测（Forest monitoring from space using deep learning）
Christian Heipke是德国汉诺威（Leibniz Universität Hannover）大学摄影测量与遥感学教授。主要研究方向包括摄影测量、遥感、图像理解以及它们与计算机视觉和地理信息系统（GIS）的交互与整合。发表近500篇科学论文，其中超过100篇发表在同行评审的国际期刊上。作为主要导师指导了40多名博士研究生。
Heipke教授曾获得国际摄影测量与遥感协会（ISPRS）Otto von Gruber Award（1992），2012年Fred Doyle Award，以及2013年美国摄影测量与遥感学会（ASPRS）颁发的Photogrammetric (Fairchild) Award，还获得2022年德国摄影测量与遥感学会（DGPF）颁发的Albrecht Meydenbauer奖章。
2004至2009年任欧洲空间数据研究协会（EuroSDR，前身为OEEPE）副主席。2011至2014年任德国大地测量委员会（DGK）主席。2012至2016年任国际摄影测量与遥感协会（ISPRS）秘书长，2016至2022年任ISPRS主席。目前任ISPRS荣誉主席。
摘要：当前，迅速提供最新、全面的空间信息以支持林业的最佳管理决策已成为紧迫问题。遥感数据是解决该领域诸多任务的最有效工具。该领域的发展特征在于卫星数量的快速增加与空间和时间分辨率的提高，这导致了数据量的迅速增长。这种发展一方面显著拓展了可解决的任务范围，包括森林监测；另一方面，也需要开发新算法，以确保在卫星图像中实现对象的自动快速识别。
本次报告将介绍ForstCARe项目中的工作。我们使用最新的人工智能方法开发了基于Copernicus的森林管理辅助系统。该系统能够快速检测非法清理，监测与气候相关的森林损害（如干旱、暴风雨或虫害灾害），以及监测需要快速处理大量数据的再造林管理措施。迅速提供和分析数据对于及时获得结果至关重要，以便阻止非法清理或尽早清除虫害林地。人工智能方法的设计旨在消除在这一应用领域广泛使用Copernicus影像的两个主要障碍：（a）缺乏数量和质量足够的代表性训练数据；（b）由于云覆盖，尤其是在暴风雨后以及在热带地区等云覆盖频繁的地方，适用的传感器数据不足。
3. Songlin Fei 教授， Ayman Habib教授，数字林业的促进力量 —— 感知和数据分析技术（Sensing and Data Analytics Technologies as Facilitators for Digital Forestry）
Songlin Fei 教授，美国普渡大学 (Purdue University) 数字林业研究所所长。Fei博士的研究领域包括森林生态学、侵入生态学和数字林业。他的研究显著推动了入侵物种生态与管理的相关研究，增进对森林生态系统气候变化响应机制的理解，并将林业引入数字时代。在过去的二十年中，Fei博士已获得超过5400万美元的资助，并发表了超过140篇同行评审的研究文章。他还担任Ecosphere的副主编。
Ayman Habib教授，美国普渡大学土木工程系 the Thomas A. Page教授，任可持续环境无人机应用土木工程中心（CE-CAUSE）的联合主任，数字林业研究所的副所长，以及普渡大学联合交通研究项目的副主任。他的研究方向涵盖了使用成像和激光雷达遥感模式的陆地和航空移动测绘系统。他的研究应用领域包括交通运输、基础设施监测、环境保护、精准农业、数字林业、资源管理和考古学。
摘要：数字技术持续地改变着各行各业和我们的日常生活，然而林业领域仍大多基于基本原理和人工流程运作。在本次报告中，我们将探讨如何将传统林业领域引入数字时代。在报告的第一部分重点介绍一些示例和经验教训，说明如何将数字技术与跨学科知识相结合，从而彻底改革具有巨大经济和生态影响的林业部门。我们展示了从近距离、近中距离、航空和卫星平台的不同感知技术的使用，用于树木定位、识别和测量。在报告的第二部分详细介绍了使用背包和无人机激光雷达移动测绘系统的示例，以及应用人工智能进行个体茎级清查的情况。我们涵盖了从数据采集、配准、集成到分析的整个流程。
ISPRS地理空间周 (The ISPRS Geospatial Week, GSW) 是由国际摄影测量和遥感学会组织的一项国际活动，每两年举行一次。2023年ISPRS地理空间周将于9月2日至7日在埃及开罗举行，来自世界各地的上千名地球空间信息科学领域的专家将聚集在此，分享与探讨最新的研究成果。本次ISPRS地理空间周将包含29个专题研讨会，为与会者提供一个难得的多学科交流机会。
会议链接：
https://gsw2023.com/index.php/project/smart-forests-multi-scale-forest-ecosystem-assessment-and-monitoring-using-remote-sensing-artificial-intelligence-and-robotics/
会议安排：
The 1st Smart Forests workshop will be held in Cairo, Egypt.
The 1st Smart Forests workshop is scheduled to take place from September 5th to 7th in Cairo, Egypt. The workshop focuses on exploring the principles, methods, and practices of the application of cutting-edge disciplines such as multi-modal remote sensing, artificial intelligence, and robotics on the assessment and monitoring of forest ecosystems. It aims to present new pathways for multi-scale forest assessment and monitoring, enhance the understanding of forest ecosystems, and provide efficient means for intelligent and effective forest resource management.
This workshop will host five sessions including large-scale forest monitoring using deep learning, multi-scale systems and methods, agricultural and forestry monitoring and assessment, close-range remote sensing sensors and solutions, and individual tree-scale modeling and analysis. These presentations will showcase the latest developments in data acquisition, preprocessing, information extraction, and applications of forest remote sensing. Experts, e.g., from China, the United States, Finland, Italy, Germany, Switzerland, and Chile, will present and discuss topics such as intelligent remote sensing deep learning frameworks and model design, precision of ICESAT-2 ATL08 satellite-borne laser data, high spatiotemporal resolution monitoring of birch tree growth dynamics, deep learning-based satellite forest monitoring, sensing and data analysis technology promoting digital forestry, GPT applications in forestry exploration. These discussions will provide theoretical and technical support for further research developments
The 1st Smart Forests workshop is co-organized by the International Society of Photogrammetry and Remote Sensing (ISPRS) working groups Remote Sensing Data Processing and Understanding (WGIII-1), Data Quality and Benchmark of Sensors (WGI-7), and Remote Sensing of Agricultural and Nature Ecosystems (WGIII-8).
This workshop will have three Keynote Presentations from internationally renowned scholars:
Prof. Jianya Gong -- A Special Deep Learning Framework and Foundation Model for Intelligent Interpretation of Remote Sensing
Dr. Jianya Gong is a professor of Wuhan University and an academician of Chinese Academy of Sciences. He is the winner of the National Outstanding Youth Fund, the chief scientist of the 973 Project, the academic leader of the Innovation Group of the National Natural Science Foundation, the leading scientific and technological talents of the State Bureau of Surveying and Mapping, and the convenor of the Surveying and Mapping Discipline Group of the sixth and Seventh Subject Review Groups of The State Council. He was the director of the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing and the Dean of the school of Remote Sensing Information Engineering of Wuhan University, president of the Commission VI of the International Society of Photogrammetry and Remote Sensing, and president of International Association of Chinese Professional in Geographic Information Science. He is currently the Secretary-General of the Asian Association for Geographic Information Systems, associate editor of Acta Geodaetica et Cartographica Sinica and Editor-in-Chief of Journal of Geodesy and GeoInformation Science.
Dr. Jianya Gong is mainly engaged in the research of remote sensing and geographic information system. He has undertaken more than 40 national and provincial scientific research projects. He has published 13 monographs and textbooks, and more than 500 papers. He has won the National Science and Technology Innovation Team Award once, the first prize once and the second prize for 4 times of the National Science and Technology Progress Award, the provincial and ministerial level special prize for 3 times and the first prize for 7 times, and the Dolezal Achievement Award of the International Society of Photogrammetry and Remote Sensing.
Abstract：Artificial intelligence has been rapidly developed and widely applied in many fields. Important research progress has also been made in intelligent interpretation of remote sensing images, and some scenarios have been applied. However, the large-scale business application of intelligent interpretation of remote sensing images is not mature enough. The report analyzes the existing problems in intelligent interpretation of remote sensing, including the small number of samples, incomplete categories, lack of standards and specifications, and the existing deep learning network framework is difficult to meet the needs of intelligent interpretation of multi-source remote sensing images. The speaker introduced his team's latest research achievements in remote sensing intelligent interpretation, including the design and research progress of LuojiaSET, a diversified and standardized sample set, and LuojiaNET, a dedicated deep learning network framework for remote sensing intelligent interpretation, as well as the foundation model based on LuojiaNET and its applications in remote sensing intelligent interpretation.
2. Prof. Christian Heipke -- Forest monitoring from space using deep learning
Dr. Christian Heipke is a professor of photogrammetry and remote sensing at Leibniz Universität 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 co-authored close to 500 scientific papers, more than 100 of which appeared in peer-reviewed international journals. He also supervised more than 40 PhD candidates as main supervisor.
He is the recipient of the 1992 Otto von Gruber Award, the 2012 Fred Doyle Award, both from the International Society of Photogrammetry and Remote Sensing (ISPRS), the 2013 Photogrammetric (Fairchild) Award from ASPRS, and the 2022 Albrecht Meydenbauer Medal from DGPF. He is an ordinary member of various learnt societies incl. DGK (German Geodetic Commission), acatech (German Academy for Technical Sciences), IAA (International Academy of Astronautics) and the European Academy of Sciences and Arts.
From 2004 to 2009, he served as vice president of EuroSDR (European Spatial Data Research, formerly known as OEEPE). From 2011-2014 he was chair of the German Geodetic Commission (DGK), from 2012-2016 ISPRS Secretary General, and from 2016-2022 ISPRS President. Currently he serves as ISPRS Past President.
Abstract：Currently, a pressing issue is the rapid provision of up-to-date and comprehensive spatial information for making optimal management decisions in the forestry industry. Remote sensing data represents a most effective tool for addressing many tasks in this field. The development is characterized by a rapid increase in the number of operating satellites and the simultaneous increase in spatial and temporal resolution, leading to a large increase in data volume. On the one hand, this development allows for a significant expansion of the range of tasks to be solved, including forest monitoring; on the other hand, there is a need to develop new algorithms that ensure automated and fast recognition of objects in satellite images.
In this presentation we describe our work within the ForstCARe project. We developed a Copernicus-based forest management assistance system using innovative AI procedures. It supports rapid detection of illegal clearings, monitoring of climate-related forest damage (due to drought, storm, or pest calamity) and monitoring management measures for reforestation in accordance with the need for rapid processing of large amounts of data.
Rapid provision and analysis of data is essential to provide timely results, on the basis of which illegal clearings can be stopped or pest-infested stands removed as quickly as possible. AI procedures are designed to remove the two main obstacles to a broad and successful use of Copernicus imagery in this application segment: (a) The lack of representative training data in the needed quantity and quality. (b) The insufficient availability of suitable sensor data due to cloud cover, especially after storms and in the tropics and other regions with frequent cloud cover.
3. Prof. Songlin Fei & Prof. Ayman Habib -- Sensing and Data Analytics Technologies as Facilitators for Digital Forestry
Dr. Songlin Fei is the Professor and Dean’s Chair of Remote Sensing, and serves as the Director of the Institute for Digital Forestry at Purdue University. Dr. Fei’s research includes forest ecology, invasion ecology, and digital forestry. His research has significantly advanced ecology and management of invasive species, the understanding of forest responses to climate change, and modernizing forestry into the digital age. During the past twenty years, Dr. Fei has secured over $54 million grant funding and has published over 140 peer-reviewed research articles. He also serves as the associate Editor in Chief for Ecosphere.
Dr. Ayman Habib is the Thomas A. Page Professor of Civil Engineering. He serves as the Co-Director of the Civil Engineering Center for Applications of UAS for a Sustainable Environment (CE-CAUSE), the Associate Director of the Institute for Digital Forestry, and the Associate Director of the Joint Transportation Research Program at Purdue University. His research interests span terrestrial and aerial mobile mapping systems using imaging and LiDAR remote sensing modalities. The application domains of his work include transportation, infrastructure monitoring, environmental protection, precision agriculture, digital forestry, resource management, and archeology.
Abstract：Digital technology continues to transform industries and our daily lives; however, forestry still operates largely on the basis of fundamentals and manual processes. In this presentation, we discuss how to move the traditional forestry field into the digital age. In this first part of the presentation, we highlight some examples and lessons learned on how to merge digital technology and cross-disciplinary knowledge to revolutionize the forestry sector that has tremendous economic and ecological impacts. We showcase the use of different sensing technology from proximal, near-proximal, aerial, and satellite-based sensing platforms for tree localization, identification, and measurement. In the second part of the presentation, we provide a detailed example of using backpack and UAV based LiDAR mobile mapping systems, along with the application of AI, for individual stem-level inventory. We cover the whole pipeline from data acquisition, registration, integration, and analytics.
Workshop Link:
https://gsw2023.com/index.php/project/smart-forests-multi-scale-forest-ecosystem-assessment-and-monitoring-using-remote-sensing-artificial-intelligence-and-robotics/
The ISPRS Geospatial Week（GSW） is an international event organized by the International Society for Photogrammetry and Remote Sensing (ISPRS), and held biennially in odd years. The ISPRS Geospatial Week 2023 will take place in Cairo, Egypt, from September 2nd to 7th. More than one thousand experts in the field of geospatial information science from around the world will gather here to share and discuss the latest research findings. The event will encompass 29 specialized workshops, providing participants with a valuable interdisciplinary platform for exchange.
The 1st Smart Forest Workshop Schedule:
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