AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Institute of Advanced Research in Artificial Intelligence（人工智能高等研究院）；Nanyang Technological University（南洋理工大学）；Helmholtz-Zentrum Dresden-Rossendorf（亥姆霍兹德累斯顿罗森多夫研究中心）；Lancaster University（兰卡斯特大学）；University of Southampton（南安普顿大学）
Yonghao Xu, Tao Bai, Weikang Yu, Shizhen Chang, Peter M. Atkinson, Pedram Ghamisi
Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based ones, have been developed and applied widely to RS data analysis. The successful application of AI covers almost all aspects of Earth observation (EO) missions, from low-level vision tasks like super-resolution, denoising and inpainting, to high-level vision tasks like scene classification, object detection and semantic segmentation. While AI techniques enable researchers to observe and understand the Earth more accurately, the vulnerability and uncertainty of AI models deserve further attention, considering that many geoscience and RS tasks are highly safety-critical. This paper reviews the current development of AI security in the geoscience and RS field, covering the following five important aspects: adversarial attack, backdoor attack, federated learning, uncertainty and explainability. Moreover, the potential opportunities and trends are discussed to provide insights for future research. To the best of the authors' knowledge, this paper is the first attempt to provide a systematic review of AI security-related research in the geoscience and RS community. Available code and datasets are also listed in the paper to move this vibrant field of research forward.
Coarse-to-fine Task-driven Inpainting for Geoscience Images
Cleveland State University（克利夫兰州立大学）；Nanyang Technological University（南洋理工大学）；Wuhan University（武汉大学）；Beijing University of Technology（北京工业大学）；Brookhaven National Laboratory（布鲁克海文国家实验室）
GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensing
RIKEN AIP（日本理化学研究所革新智能研究中心）；Wuhan University（武汉大学）；Linköping University（林雪平大学）；University of Tokyo（东京大学）；Nanjing University of Information Science and Technology（南京信息工程大学）
Backdoor Attacks for Remote Sensing Data with Wavelet Transform
Institute of Advanced Research in Artificial Intelligence（人工智能高级研究院）；TU Wien（维也纳工业大学）；Helmholtz-Zentrum Dresden-Rossendorf（亥姆霍兹德累斯顿罗森多夫研究中心）；Helmholtz Institute Freiberg for Resource Technology（亥姆霍兹弗赖贝格资源技术研究所）
RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation
the Future Network of Intelligence Institute (FNii), the Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）未来网络智能研究院）；School of Information Science and Engineering, Wuhan University of Science and Technology（武汉科技大学信息科学与工程学院）
SpectralGPT: Spectral Remote Sensing Foundation Model
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）；Southeast University（东南大学）；The University of Tokyo（东京大学）；Technical University of Munich（慕尼黑工业大学）；Helmholtz-Zentrum Dresden-Rossendorf（德累斯顿-罗森多夫亥姆霍兹中心）；Institute of Advanced Research in Artificial Intelligence（高级人工智能研究所）；University of New South Wales（新南威尔士大学）
DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes
Department of Electrical and Computer Engineering, Vanderbilt University（电气与计算机工程系，范德比尔特大学）；Department of Anthropology, Vanderbilt University（人类学系，范德比尔特大学）；Data Science Institute, Vanderbilt University（数据科学研究院，范德比尔特大学）；Department of Computer Science, Vanderbilt University（计算机科学系，范德比尔特大学）；Department of Mathematics, Vanderbilt University（数学系，范德比尔特大学）；Oak Ridge National Laboratory（橡树岭国家实验室）；Department of Anthropology, Brown University（人类学系，布朗大学）；Department of Radiology, Weill Cornell Medicine（放射学系，韦尔·科恩医学中心）
Towards a Collective Agenda on AI for Earth Science Data Analysis
Wageningen University（瓦赫宁根大学）；Ecole Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）；University of Bonn（波恩大学）；ETH Zurich（苏黎世联邦理工学院）；University of Kentucky（肯塔基大学）；Technical University of Munich（慕尼黑工业大学）；German Aerospace Center（德国航空航天中心）；Universitat de València（瓦伦西亚大学）
Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model
Remote Sensing Technology Institute, German Aerospace Center（德国航空航天中心遥感技术研究所）；Technical University of Munich（慕尼黑工业大学）；Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；Univ. Grenoble Alpes（格勒诺布尔阿尔卑斯大学）；INRIA（法国国家信息与自动化研究所）；CNRS（法国国家科学研究中心）；Grenoble INP（格勒诺布尔理工学院）
Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）理工学院）；School of Information Science and Engineering, Wuhan University of Science and Technology（武汉科技大学信息科学与工程学院）；School of Cyber Science and Engineering, Wuhan University（武汉大学网络空间安全学院）；School of Electronic Engineering and Computer Science, Peking University（北京大学电子工程与计算机科学学院）
Vision-Language Models in Remote Sensing: Current Progress and Future Trends
King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）；New York University Abu Dhabi（纽约大学阿布扎比分校）；Peking University（北京大学）；Technical University of Munich（慕尼黑工业大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）
A review of machine learning in processing remote sensing data for mineral exploration
University of Tehran（德黑兰大学）；Amirkabir University of Technology (Tehran Polytechnic)（阿米尔卡比尔理工大学（德黑兰理工学院））；University of Sydney（悉尼大学）；University of New South Wales（新南威尔士大学）
Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR)（德国航空航天中心遥感技术研究所）；Univ. Grenoble Alpes（格勒诺布尔大学）；CNRS（法国国家科学研究中心）；Grenoble INP（格勒诺布尔理工学院）；RIKEN Center for Advanced Intelligence Project (AIP)（理化学研究所智能情报研究中心）；Graduate School of Frontier Sciences, the University of Tokyo（东京大学前沿科学研究生院）；Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；Wuhan University（武汉大学）；INRIA（法国国家信息与自动化研究所）；LJK（格勒诺布尔大学-法国国家科学研究中心-格勒诺布尔理工学院联合实验室）
More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification
Univ. Grenoble Alpes（格勒诺布尔阿尔卑斯大学）；CNRS（法国国家科学研究中心）；Grenoble INP（格勒诺布尔理工学院）；GIPSA-lab（GIPSA实验室）；Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；the University of Tokyo（东京大学）；RIKEN Center for Advanced Intelligence Project (AIP), RIKEN（理化学研究所革新智能综合研究中心）；Xi’an Jiaotong University（西安交通大学）；INRIA（法国国家信息与自动化研究所）；LJK（让·昆兹曼实验室）；Mississippi State University（密西西比州立大学）
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）；Liaocheng University（聊城大学）
Deep Learning for Slum Mapping in Remote Sensing Images: A Meta-analysis and Review
Centre of Excellence in Artificial Intelligence, Indian Institute of Technology Kharagpur（印度理工学院卡拉格普尔分校人工智能卓越中心）；Tata Consultancy Services Research（塔塔咨询服务公司研究院）
Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model
Beihang University（北京航空航天大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Shen Yuan Honors College of Beihang University（北京航空航天大学沈元荣誉学院）；National University of Singapore（新加坡国立大学）
PhysFlow: Frequency Decoupled with Dual-Field Rectified Flow for Remote Photoplethysmography
PCA Lab, Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院教育部高维信息智能感知与系统重点实验室PCA实验室）；College of Computer Science and Technology, Qingdao University（青岛大学计算机科学技术学院）
Estimating forest carbon stocks from high-resolution remote sensing imagery by reducing domain shift with style transfer
School of Geography and Remote Sensing, Guangzhou University（广州大学地理与遥感学院）；Innovation Center for Remote Sensing Big Data Intelligent Applications, Guangzhou University（广州大学遥感大数据智能应用创新中心）
Advancing Image Super-resolution Techniques in Remote Sensing: A Comprehensive Survey
Research Center for Space Computing System, Zhejiang Lab（空间计算系统研究中心，浙江实验室）；School of Computing and Data Science, The University of Hong Kong（计算与数据科学学院，香港大学）；School of Information Science and Engineering, Lanzhou University（信息科学与工程学院，兰州大学）
National Technical University of Athens（雅典国立技术大学）；University College London（伦敦大学学院）；NCSR Demokritos（德谟克利特国家科学研究中心）
Leon A. Gatys等人，艺术风格的神经算法，已经成为学术文献和工业应用的热门话题。神经风格转移（NST）是一个重要的工具，用于广泛的应用，如艺术风格化的2D图像，用户辅助创建工具和娱乐应用的生产工具。本研究的目的是提出一种方法，从卫星图像创建艺术地图，基于NST算法。该方法包括三个基本步骤：（i）在原始卫星图像上应用语义图像分割，将其内容划分为类别（即土地，水），（ii）对每个类别应用神经风格转移，以及（iii）创建拼贴画，即由前一步骤生成的两个风格化图像的组合组成的艺术图像。
A comprehensive review of remote sensing in wetland classification and mapping
Department of Geography, The University of Hong Kong（地理系，香港大学）；Department of Earth System Science, Tsinghua University（地球系统科学系，清华大学）；Department of Electronics and Information Engineering, Harbin Institute of Technology (Shenzhen)（电子与信息工程系，哈尔滨工业大学（深圳））；Pengcheng Laboratory（鹏城实验室）
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification
Bias Variance Labs, d.o.o.（Bias Variance Labs有限责任公司）；Faculty of Computer Science and Engineering, University Ss Cyril and Methodius（圣西里尔与美多德大学计算机科学与工程学院）；Jožef Stefan Institute（约泽夫·斯蒂芬研究所）；University of Cambridge（剑桥大学）
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）；International Research Center of Big Data for Sustainable Development Goals（可持续发展大数据国际研究中心）
Multimodal Fusion Transformer for Remote Sensing Image Classification
Jalpaiguri Government Engineering College（贾尔派古里政府工程学院）；Technical University of Munich（慕尼黑工业大学）；Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；Helmholtz-Zentrum Dresden-Rossendorf（亥姆霍兹德累斯顿罗森多夫研究中心）；University of Extremadura（埃斯特雷马杜拉大学）；Univ. Grenoble Alpes（格勒诺布尔阿尔卑斯大学）；CNRS（法国国家科学研究中心）；Grenoble INP（格勒诺布尔国立理工学院）
