AI Remote Sensing
A section of Remote Sensing (ISSN 2072-4292).
Section Information
In recent years, Artificial Intelligence (AI) techniques have emerged as a powerful strategy for analyzing remote sensing (RS) data and led to remarkable breakthroughs in all RS fields. Applications of AI, particularly machine learning (ML) and deep learning (DL) algorithms, range from initial RS image processing to high-level RS data understanding and knowledge discovery. AI foundation models for remote sensing are also evolving. Given this period of evolution, this section focuses on developing novel AI concepts, algorithms, and techniques with applications for geoscience and remote sensing data (e.g., spaceborne, airborne, and UAV remote sensing for earth observation).
We invite authors to submit their articles to the AI Section of Remote Sensing in order to improve our current knowledge of the AI techniques used in remote sensing. Potential topics may include, but are not limited to, the following:
The fundamentals of AI in remote sensing;
AI foundation models in remote sensing science;
AI-based information acquisition and processing of remote sensing data;
Deep learning algorithms for remote sensing data;
Machine learning algorithms for remote sensing data;
Computer vision-related tasks in remote sensing (e.g., restoration, detection, classification, recognition, segmentation, retrieval);
Natural language processing-related tasks in remote sensing (e.g., caption, generation, question answering);
Pretrained foundation remote sensing models;
Multi-modal remote sensing data processing;
Reinforcement learning techniques in remote sensing;
Algorithm optimization techniques in remote sensing;
AI security for remote sensing;
AI hardware and systems for remote sensing;
Combined model-driven and data-driven methods for remote sensing data;
Robotics and automation techniques in remote sensing;
AI for sciences in remote sensing.
Please note that research that does not directly deal with remote sensing data does not fall within the scope of this journal.
Editorial Board
Topical Advisory Panel
Special Issues
Following special issues within this section are currently open for submissions:
- Artificial Intelligence for Remote Sensing: State-of-the-Art Reviews and Future Directions (Deadline: 31 August 2026)
- Multisource Data Fusion and Reasoning in Remote Sensing: From Perception to Decision Making (Deadline: 31 August 2026)
- AI-Driven Satellite Data for Global Environment Monitoring (Second Edition) (Deadline: 31 August 2026)
- Deep Learning for Multi-Source Remote Sensing Image Interpretation: Exploring, Rethinking, and Limiting Breakthroughs (Deadline: 31 August 2026)
- Advances in Artificial Intelligence (AI) and Deep Learning (DL) in UAV-Based Remote Sensing (Deadline: 31 August 2026)
- Advanced AI Technology for Remote Sensing Analysis (Second Edition) (Deadline: 31 August 2026)
- Advances in AI-Driven Remote Sensing for Geohazard Perception (Deadline: 31 August 2026)
- Robust Perception in Open and Data-Limited Environments: From Earth to Deep Space (Deadline: 15 September 2026)
- Target Detection, Recognition, Tracking, and Positioning Using Remote Sensing and AI Techniques (Second Edition) (Deadline: 28 September 2026)
- Artificial Intelligence and Machine Learning for Multi-Modal and Multi-Spectral Remote Sensing Image Processing (Deadline: 30 September 2026)
- Artificial Intelligence for Optical Remote Sensing Image Processing (Deadline: 30 September 2026)
- Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection (Third Edition) (Deadline: 30 September 2026)
- Multimodal Remote Sensing Data Fusion, Analysis and Application (Deadline: 30 September 2026)
- Remote Sensing Target Recognition and Detection: Theory and Applications (Second Edition) (Deadline: 30 September 2026)
- AI-Enhanced Photogrammetry and Remote Sensing for Image-Based 3D Reconstruction (Deadline: 30 September 2026)
- AI-Driven Hyperspectral Remote Sensing of Atmosphere and Land (Deadline: 31 October 2026)
- Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience (Second Edition) (Deadline: 31 October 2026)
- 3D City Modeling and Observation Using Remote Sensing and Artificial Intelligence (Deadline: 31 October 2026)
- AI-Driven Hyperspectral Image Classification and Processing in Remote Sensing (Deadline: 15 November 2026)
- Artificial Intelligence and Satellite Remote Sensing in Climate Smart Agriculture (Deadline: 30 November 2026)
- Knowledge-Driven and/or Data-Driven Methods for Remote Sensing Image Processing (2nd Edition) (Deadline: 30 November 2026)
- Artificial Intelligence for Ocean Remote Sensing (Second Edition) (Deadline: 30 November 2026)
- Advanced Applications of Artificial Intelligence in Remote Sensing Image Recognition (2nd Edition) (Deadline: 31 December 2026)
- Multimodal Learning and Explainable AI for Remote Sensing Image Interpretation (Deadline: 31 December 2026)
- Global Monitoring of Inland Water Using Remote Sensing and Artificial Intelligence (Second Edition) (Deadline: 31 December 2026)
- Explainable and Trustworthy AI for Earth Observation Applications and Geospatial Science (Deadline: 31 December 2026)
- Remote Sensing and Associated Artificial Intelligence in Agricultural Applications (2nd Edition) (Deadline: 31 December 2026)
- Robust and Trustworthy AI for SAR and Multi-Modal Remote Sensing Change Detection (Deadline: 20 January 2027)
- Advanced Application of Artificial Intelligence and Machine Vision in Remote Sensing (Fourth Edition) (Deadline: 31 January 2027)
- Deep Learning Techniques and Applications of MIMO Radar Theory (Deadline: 15 February 2027)
- The Recent Progression of Machine Learning in Remote Sensing: Theory and Modelling (Second Edition) (Deadline: 15 February 2027)
- Advanced Deep Learning and Foundation Models for Hyperspectral Image Interpretation (Deadline: 28 February 2027)
- Multi-Source Sensor Collaboration for the Intelligent Perception of Targets: Detection, Sensing, and Localization (Deadline: 28 February 2027)
- Artificial Intelligence and Big Data Remote Sensing for Land Use/Land Cover Mapping and Sustainable Development (Deadline: 28 February 2027)
- Deep Learning for Hyperspectral Image Pre-Processing and Interpretation: Registration, Fusion and Change Detection (Deadline: 28 February 2027)
- Artificial Intelligence Remote Sensing Change Detection: Development and Challenges (Second Edition) (Deadline: 28 February 2027)
- Agentic Engineering and Multi-Agent Pipeline-Based Remote Sensing Data Analysis (Deadline: 15 March 2027)
- Artificial Intelligence and Machine Learning for Detection and Observation in Remote Sensing Imagery (Deadline: 31 March 2027)
- Remote Sensing Dense Prediction in the Era of Foundation Models and AI Agents (Deadline: 31 March 2027)