Themes

IGARSS 2025 Special Scientific Themes

  • SP: Special Scientific Themes

    • SP.1: Natural disasters and disaster management
    • SP.2: Geoscience and remote sensing in developing countries
    • SP.3: Remote sensing for sustainable development in the Asia-Pacific region
    • SP.4: Remote sensing for barrier reef conservation
    • SP.5: Global warming, climate records and climate change analysis
    • SP.6: Data security in remote sensing
    • SP.7: Al for on-board satellite analytics
    • SP.8: GIS development and remote sensing
    • SP.9: Wave propagation and remote sensing
General Themes

  • T/S: SAR Imaging and Processing Techniques

    • T/S.1: Interferometry: Along and Across
    • T/S.2: Differential SAR Interferometry
    • T/S.3: Multi-Channel DBF Imaging Techniques
    • T/S.4: PolSAR and PolInSAR
    • T/S.5: Bistatic SAR
    • T/S.6: Tomography
    • T/S.7: Sub-surface sensing

  • T/D: Data Analysis

    • T/D.8: Feature Extraction and Reduction
    • T/D.9: Image Segmentation
    • T/D.10: 3D mapping
    • T/D.11: Object Detection and Recognition
    • T/D.12: Classification and Clustering
    • T/D.13: Inversion Techniques
    • T/D.14: Change Detection and Temporal Analysis
    • T/D.15: Hyperspectral Data Processing and Analysis
    • T/D.16: RFI Detection and Mitigation
    • T/D.17: Data Fusion
    • T/D.18: External Calibration

  • T/A: AI and Big Data

    • T/A.19: Data Management Systems and Computing Platforms in Remote Sensing
    • T/A.20: IoT in Geoscience and Remote Sensing
    • T/A.21: Spatio-temporal Data Harmonization
    • T/A.22: Data Analytics and AI Techniques in Remote Sensing

  • T/M: Modeling

    • T/M.23: Electromagnetic Modeling
    • T/M.24: EM Emission Modeling
    • T/M.25: EM Scattering Modeling
    • T/M.26: EM Polarimetric Scattering and Emission Modeling
    • T/M.27: EM 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: Topography, Geology and Geomorphology
    • 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) and Water Quality
    • O.2: Ocean Surface Winds and Currents
    • O.3: Ocean Temperature and Salinity
    • O.4: Coastal Zones
    • O.5: Ocean Altimetry

  • P: Remote Sensing of Planetary and other Celestial Bodies

    • P.1: Moon
    • P.2: Mars
    • P.3: Other Celestial Bodies
    • P.4: Moons
    • P.5: Planets

  • S/M: Mission, Sensors and Calibration

    • S/M.1: Spaceborne SAR Missions
    • S/M.2: Spaceborne Passive Microwave Missions
    • S/M.3: Spaceborne GNSS-R Missions
    • S/M.4: Spaceborne Hyperspectral Missions
    • S/M.5: Spaceborne LIDAR Missions
    • S/M.6: Exploration Missions (other Planets)
    • S/M.7: New Space Missions
    • S/M.8: UAV and Airborne Platforms
    • S/M.9: Ground based Systems
    • S/M.10: High Altitude Platforms

  • S/I: Sensors, Instruments and Calibration

    • S/I.11: Sensors Using Signals of Opportunity (e.g. GNSS-R)
    • S/I.12: Lidar Sensors
    • S/I.13: Passive Optical Multi- and Hyperspectral Sensors and Calibration
    • S/I.14: SAR Instrument
    • S/I.15: Advanced Future Instrument Concepts
    • S/I.16: Microwave Radiometer Calibration
    • S/I.17: SAR and Radar Instrument Calibration
    • S/I.18: Microwave Radiometer Instruments
    • S/I.19: Ground Penetrating Radar
    • S/I.20: Onboard Signal Processing
    • S/I.21: Scatterometer, Clouds and Rain Radar

  • D/E: Education and Policy

    • D/E.1: Data Management and Systems
    • D/E.2: Remote Sensing Data and Policy Decisions
    • D/E.3: Education and Remote Sensing

  • D/S: Societal Engagement and Impacts

    • D/S.4: Citizen and Open Science
    • D/S.5: Risk and Disaster Management (Extreme Weather, Earthquakes, Volcanoes, etc)
    • D/S.6: Food security
    • D/S.7: Remote Sensing for Sustainable Development
    • D/S.8: Standardization in Remote Sensing
    • D/S.9: Remote Sensing for Climate Change Impacts
Community-Contributed Sessions

  • CCS: Community-Contributed Sessions

    • CCS.1: International Standards for LCLU and SDG Reporting
    • CCS.2: Emerging Technologies for Microwave Radiometers
    • CCS.3: Polarimetric SAR Methods and Applications
    • CCS.4: Satellite RS for Coastal Hazard Monitoring and Risk Prediction
    • CCS.5: Signal Processing for Geoscience and RS Applications
    • CCS.6: Forest Height Inversion Using Microwave RS
    • CCS.7: DL for SAR RS Applications
    • CCS.8: Advances in Hydrology using Topography Mission
    • CCS.9: Hyperspectral RS for Agriculture, Forestry, and Wetlands
    • CCS.10: Image Analysis and Data Fusion for SDGs
    • CCS.11: Advances in ML for Agricultural LULC
    • CCS.12: RS and AI for Weather and Aerosols
    • CCS.13: Multimodal RS Image Processing and Interpretation
    • CCS.14: RPAS for Data Collection, Processing and Analysis
    • CCS.15: Advances in SAR Image Quality Metrics
    • CCS.16: Crop Yield Estimation with EO
    • CCS.17: Advances on Polarimetric GNSS-R
    • CCS.18: Monitoring Climate Change Impacts on Vegetation
    • CCS.19: AI and Hyperspectral Data Analytics
    • CCS.20: ALOS Series Mission, Cal/Val, and Applications
    • CCS.21: Hyperspectral Data for Critical Metal Exploration
    • CCS.22: RS for Urban Climate and Sustainability
    • CCS.23: Applications of Very High Resolution X-Band SAR data
    • CCS.24: AI for Soil Health
    • CCS.25: NASA’s ICESat-2 Spaceborne Lidar Mission
    • CCS.26: Space-Based Imaging Spectrometer Cal/Val
    • CCS.27: FAIR RS Data Systems
    • CCS.28: Challenges and Opportunities for Polar EO
    • CCS.29: Ocean RS for Sustainable Development
    • CCS.30: Close-range Sensing of Environment
    • CCS.31: RS Data Assimilation
    • CCS.32: Data-centric AI for Geospatial Applications
    • CCS.33: RS Datasets and Benchmarking for Damaged Bulding Detection
    • CCS.34: Datasets and evaluation for RS algorithms
    • CCS.35: Deep Learning and RS for Rapid Disaster Response
    • CCS.36: Deep Learning for Multi-channel SAR processing
    • CCS.37: RS for Detecting and Tracking Marine Animals
    • CCS.38: Disaster RS Algorithms and Applications
    • CCS.39: Distributed SAR Systems, Algorithms, and Applications
    • CCS.40: RS-based Decision Support Systems for Disaster Management
    • CCS.41: RS for Sustainable Water Resources & Terrestrial Ecosystems
    • CCS.42: Earth Observation Foundation Models
    • CCS.43: EO Equitable Workforce for Climate Change
    • CCS.44: SMAP Applications in Earth System Science
    • CCS.45: Crop Growth Models and RS
    • CCS.46: Enhancing Safety and Security through EO
    • CCS.47: Enhancing the Interpretation of Complex Earth Materials
    • CCS.48: EO Data Cubes
    • CCS.49: New Satellite Applications for Weather and Climate Science
    • CCS.50: Foundation Models for Geospatial AI
    • CCS.51: RS of Aerosols and Radiative Impacts
    • CCS.52: GeoAI and EO for Emergecy Response
    • CCS.53: AI Algorithms for Environmental Monitoring
    • CCS.54: Google Earth Engine
    • CCS.55: Ground Validation of Optical EO
    • CCS.56: Hybrid Quantum-Classical Computing for Earth Observation
    • CCS.57: Parallel and Efficient Computing for RS
    • CCS.58: RS and High-end Computing for LULC Mapping
    • CCS.59: SAR for HiRes Tropical Cyclone Wind Vectors
    • CCS.60: The Role of AI in Unveiling Climate Change Patterns
    • CCS.61: Hyperspectral Geoscience Mapping in Developing Countries.
    • CCS.62: IEEE GRSS Data Fusion Contest
    • CCS.63: Image Analysis and Data Fusion: The AI Era
    • CCS.64: Imaging Spectroscopy for Defense and Intelligence
    • CCS.65: AI and RS for Wildfires and Environmental Impacts
    • CCS.66: Innovations in RS Instrument Design and Calibration
    • CCS.67: RS and AI for Severe Storms and Impacts
    • CCS.68: Monitoring Disasters from Cyclones/Typhoons/Hurricanes
    • CCS.69: Multisensor Fusion for Forest Mapping
    • CCS.70: LiDAR for Sustainable Development Goals
    • CCS.71: LEO satellite missions for Earth Science
    • CCS.72: Microwave Radiometry Calibration
    • CCS.73: Hyperspectral Data for Mining Sites
    • CCS.74: ML and AI-Based Noise Reduction and Image Enhancement
    • CCS.75: Modeling in GNSS-R and Other Signal-of-opportunity Systems
    • CCS.76: Monitoring Natural Hazards Associated with Snow/Glacier Lakes
    • CCS.77: Moving Target Indication Using SAR
    • CCS.78: Multifrequency Microwave RS of Soil & Vegetation
    • CCS.79: Multisensor Data Fusion and Geospatial Data Intelligence
    • CCS.80: Multisource RS for Agricultural Applications
    • CCS.81: Mapping Earth’s Surface and Vegetation Structure
    • CCS.82: Satellite RS for Geohazard Monitoring
    • CCS.83: New Observations and Applications of Multidimensional SAR
    • CCS.84: New Satellite Laser Data for Terrain Modeling
    • CCS.85: Nighttime RS for SDGs
    • CCS.86: Applications of Earth Observations in the Pacific
    • CCS.87: Physical Modeling in Microwave and Optical RS
    • CCS.88: Physics Aware AI for SAR Data
    • CCS.89: Physics-Informed Machine Learning in Remote Sensing
    • CCS.90: Planetary Mission Laws Challenges Future Scope
    • CCS.91: CIMR Preparations
    • CCS.92: Probabilistic ML for EO
    • CCS.93: Quantum Sensing: Revolutionizing Earth Remote Sensing
    • CCS.94: Quantum Technology for RS
    • CCS.95: RFI and Spectrum Issues in Microwave RS
    • CCS.96: RS for Damage Detection After Natural Hazards
    • CCS.97: Remote Detection of Invasive Weed Species
    • CCS.98: RS Data Quality Assessment
    • CCS.99: RS for Coastal Sustainability
    • CCS.100: Remote Sensing for Oil & Gas
    • CCS.101: RS for Digital Twins
    • CCS.102: RS for Wetland Sustainability
    • CCS.103: RS of Ocean Processes
    • CCS.104: RS of Cryosphere from Altimeters
    • CCS.105: RS of Potential Fields
    • CCS.106: RS for SDGs and Climate Impacts
    • CCS.107: SAR Image Restoration and Deep Learning
    • CCS.108: SAR Interferometry for Assessing Land Surface Deformation
    • CCS.109: SAR Monitoring of Hazards on Coastal Environments
    • CCS.110: Satellite Gravimetry/GNSS for Water Resources across Canada
    • CCS.111: Satellite RS for Disaster Response
    • CCS.112: Earth Observation for Rice
    • CCS.113: Space Lidar: Missions, Technologies, and Observations
    • CCS.114: Space Missions on High Resolution TIR Radiometry
    • CCS.115: Space-based Imaging Spectrometers Missions
    • CCS.116: Spaceborne Bistatic SAR
    • CCS.117: Fusion of VSWIR Hyperspectral and TIR data
    • CCS.118: Technologies for Future Satellite Missions.
    • CCS.119: CubeSat and SmallSat missions: Validation and Observations
    • CCS.120: Terrestrial Radar/SAR Systems and Applications
    • CCS.121: New Developments in Real Time RS
    • CCS.122: The Future of Analysis Ready Data
    • CCS.123: The NISAR Mission: Status and Early Science
    • CCS.124: The Prospect of RS Foundation Models
    • CCS.125: TIR RS for Global Climate Change Analysis
    • CCS.126: Thermal IR RS: Techniques and Applications
    • CCS.127: Meta-constellation GNSS/SoOp reflectometry
    • CCS.128: Trends in Standardization for RS Data
    • CCS.129: UAV/Mobile-Mapping SAR Systems and Applications
    • CCS.130: UAV-based Multi-sensor Identification and Mapping
    • CCS.131: Potential of HAPs for Earth Observation
    • CCS.132: WSF-M Mission Status and Calibration
    • CCS.133: AI InSAR
    • CCS.134: Remote Sensing of Snow on Memory of Prof. Jeff Dozier