The 1st IEEE China conference on Information Acquisition and Processing for Remote Sensing (IAP-RS 2026)

Remote sensing technologies are fundamental tools for observing and understanding the complex dynamics of our planet. In recent years, a paradigm shift driven by breakthroughs in sensor miniaturization, artificial intelligence, high-performance computing, and integrated systems have been witnessed. These advances have significantly enhanced our capability to acquire high-resolution, multi-dimensional data and to extract actionable information with unprecedented speed and accuracy. This progress is critical for addressing global challenges such as climate change adaptation, sustainable resource management, disaster resilience, and urban planning.

The IEEE China Conference on Information Acquisition and Processing for Remote Sensing (IAP-RS 2026) is established to capture the forefront of this technological evolution. The conference aims to provide a premier international forum for researchers, engineers, and practitioners to exchange cutting-edge ideas and showcase innovative work. It will focus specifically on the synergistic development of data collection hardware and intelligent information processing methodologies, fostering interdisciplinary collaboration to push the boundaries of how we collect, process, interpret, and utilize remote sensing data.

WHEN

September 18 to 20, 2026

General Chair:

  • Prof. Li Li (Northwestern Polytechnical University, China)
  • Prof. Xiaoyong Wang (China Academy of Space Technology)

Technical Program Chairs:

  • Prof. Shaohui Mei (Northwestern Polytechnical University, China)
  • Prof. Jun Li (China University of Geosciences, China)

Topics of Interest:

We invite original, high-quality submissions on all topics related to remote sensing information acquisition and processing, including but not limited to:

  • Advanced Sensor Technology & Data Acquisition:
    • Novel designs for optical, SAR, LiDAR, hyperspectral, and multispectral sensors.
    • Emerging platforms: UAV/drones, CubeSats, HAPS, and airborne/ground-based systems.
    • Integrated Sensing and Communications (ISAC).
    • Sensor calibration, validation, and system performance modeling.
  • Intelligent Information & Signal Processing:
    • AI, machine learning, and deep learning for remote sensing data analysis.
    • Image/signal processing, classification, segmentation, and target detection.
    • Multi-source, multi-temporal, and multi-modal data fusion.
    • Edge computing and real-time onboard processing.
  • Data Management, Applications & Systems:
    • Big data platforms, cloud computing, and data democratization for remote sensing.
    • Quality assessment, robust preprocessing, and error correction.
    • Applied solutions in environmental monitoring, precision agriculture, urban informatics, and disaster management.
    • End-to-end system design and performance evaluation.

Submission Guidelines:

Prospective authors are invited to submit original research through the conference submission system.

  1. Full papers (4 pages including references)
  2. Extended abstracts (2 pages including references)

All submissions must adhere to the official IEEE conference template [会议论文模版文件].

Publication Opportunities:

Accepted papers meeting IEEE quality standards will be submitted for inclusion in IEEE Xplore®. Distinguished contributions will receive special recognition:

  • Best Paper Awards with certificate of excellence
  • Invitation for extended versions in special issues of:
    • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS, SCI-indexed)
    • Remote Sensing (SCI-indexed)

Important Dates:

  • Abstract or Full Paper Submission Deadline: July. 31, 2026
  • Notification of Acceptance: Aug. 15, 2026
  • Full Paper Submission Deadline: Sept. 1, 2026
  • Early bird Registration Deadline: Sept. 1, 2026
  • Conference Date: Sept. 18-20, 2026

Ethical Requirements:

All submissions must represent original work. By submission, authors affirm:

  • The paper contains no plagiarized content
  • No concurrent submission to other venues
  • All co-authors consent to publication