Themes

Abstract/paper submissions to IGARSS 2026 are solicited under the following Special and General Themes. Additional options will be included after the Community Contributed Themes (CCT) proposals are evaluated. Authors will be able to select the most appropriately related theme(s) from the full list of Special, General, or Community Contributed themes when submitting their abstracts or papers.

IGARSS 2026 Special Themes (SP):
  • SP.1 Geoscience and Remote Sensing in Developing Countries
  • SP.2 Findable, Accessible, Interoperable, Re-usable, Understandable, Secure, and Trustworthy (FAIRUST) Best Practices
  • SP.3 Artificial Intelligence Ethics and Governance in Remote Sensing
  • SP.4 Quantum Technologies for Earth Observation
  • SP.5 Commercial and Industry-led Remote Sensing
IGARSS 2026 General Themes:
  • The traditional IGARSS themes are grouped into five main general areas:
  • AI and Big Data (A): Papers are solicited on novel Artificial Intelligence (AI), Machine Learning (ML) and Big Data methodologies developed for use in analyzing remote sensing data.
  • Theory and Techniques (T): Papers are solicited on theory and techniques underlying the use of remote sensing methodologies to extract information about Earth and planetary systems.
  • Applications (C, L, M, O, P): Papers are solicited that report results of studies applying remote sensing data analysis methods in Earth and planetary science topics.
  • Sensors (S): Papers are solicited that address the hardware and technologies of remote sensing missions, platforms, and instruments.
  • Data and Society (D): Papers are solicited that address topics related to the distribution, management, policy, and security of remote sensing data along with papers on the intersection of remote sensing and society.
IGARSS 2026 Special Themes
  • SP: Special Themes
    • SP.1: Geoscience and Remote Sensing in Developing Countries
    • SP.2: Findable, Accessible, Interoperable, Re-usable, Understandable, Secure, and Trustworthy (FAIRUST) Best Practices
    • SP.3: Artificial Intelligence Ethics and Governance in Remote Sensing
    • SP.4: Quantum Technologies for Earth Observation
    • SP.5: Commercial and Industry-led Remote Sensing
General Themes
  • A: AI and Big Data
    • A.1: High Performance Computing in Remote Sensing
    • A.2: Foundation Models in Geoscience
    • A.3: Large-scale Machine Learning
    • A.4: Real-time Analytics, On-board Processing and Edge Computing
    • A.5: IoT in Geoscience and Remote Sensing
    • A.6: Digital Twins
  • T: Theory and Techniques
    • T.1: Interferometry: Along and Across
    • T.2: Differential SAR Interferometry
    • T.3: Multi-Channel DBF Imaging Techniques
    • T.4: PolSAR and POlInSAR
    • T.5: Bistatic and Multistatic SAR
    • T.6: Tomography
    • T.7: Sub-surface Sensing
    • T.8: Feature Extraction and Reduction
    • T.9: Image Segmentation
    • T.10: 3D Mapping
    • T.11: Object Detection and Recognition
    • T.12: Classification and Clustering
    • T.13: Inversion Techniques
    • T.14: Change Detection and Temporal Analysis
    • T.15: Hyperspectral Data Processing and Analysis
    • T.16: Unmixing Analysis
    • T.17: RFI Detection and Mitigation
    • T.18: Multimodal Data Fusion
    • T.19: Spatio-temporal Data Harmonization
    • T.20: Microwave Modeling
    • T.21: Optical Modeling
    • T.22: Polarimetric Modeling
    • T.23: Modeling for Signals of Opportunity (e.g. GNSS-R)
  • C: Cryosphere
    • C.1: Snow Cover
    • C.2: Ice Sheets and Glaciers
    • C.3: Sea Ice
    • C.4: Permafrost
  • L: Land Applications
    • L.1: Land Use Applications
    • L.2: Land Cover Dynamics
    • L.3: Forest and Vegetation: Application and Modelling
    • L.4: Forest and Vegetation: Biomass and Carbon Cycle
    • L.5: Agriculture
    • L.6: Urban and Built Environment
    • L.7: Land Surveying, Geodesy and Topography
    • L.8: Soils and Soil Moisture
    • L.9: Wetlands
    • L.10: Inland Waters
    • L.11: Geology and Geomorphology
  • M: Atmosphere Applications
    • M.1: Precipitation and Clouds
    • M.2: Numerical Weather Prediction and Data Assimilation
    • M.3: Atmospheric Sounding
    • M.4: Aerosols and Atmospheric Chemistry
    • M.5: Ionospheric Remote Sensing
  • O: Oceans
    • O.1: Ocean Biology (Color, coral reefs) and Water Quality
    • O.2: Ocean Surface Winds and Currents
    • O.3: Ocean Temperature and Salinity
    • O.4: Ocean Altimetry
    • O.5: Coastal Zones
  • G: Geosphere
    • G.1: Earth System Modeling
  • P: Remote Sensing of Planetary and other Celestial Bodies
    • P.1: Moon
    • P.2: Mars
    • P.3: Other Celestial Bodies
  • S: Sensors
    • S.1: Spaceborne SAR Missions
    • S.2: Spaceborne Passive Microwave Missions
    • S.3: Spaceborne GNSS-R Missions
    • S.4: Spaceborne Hyperspectral Missions
    • S.5: Spaceborne LIDAR Missions
    • S.6: Multi-platform Earth Observation
    • S.7: High Altitude Platforms
    • S.8: Unmanned Aerial Systems and Payloads
    • S.9: Ground-based Systems
    • S.10: Sensors Using Signals of Opportunity (e.g. GNSS-R)
    • S.11: Lidar Sensors
    • S.12: Passive Optical Multi- and Hyperspectral Sensors
    • S.13: SAR Instruments
    • S.14: Scatterometer, Clouds and Rain Radar
    • S.15: Microwave Radiometer Instruments
    • S.16: Ground Penetrating Radar
    • S.17: Advanced Future Instrument Concepts
  • D: Data and Society
    • D.1: Data Management Systems and Security
    • D.2: Remote Sensing Data and Policy Decisions
    • D.3: Education and Remote Sensing
    • D.4: Standards in Remote Sensing
    • D.5: Geographic Information Systems
    • D.6: Citizen and Open Science
    • D.7: Risk and Disaster Management (Extreme Weather, Earthquakes, Volcanoes, etc)
    • D.8: Remote Sensing for Food Security
    • D.9: Remote Sensing for Sustainable Development
    • D.10: Remote Sensing for Climate Change Impacts