Call for Papers

Submissions are invited on a comprehensive range of topics, reflecting the latest advancements and applications in the field, including but not limited to:

Author Guidelines

The final Conference Proceedings will be submitted for inclusion in IEEE Xplore, subject to meeting IEEE Xplore’s scope and quality requirements. Only those final papers for which at least one regular registration has been paid and the work has been presented at the conference (by the author, a co-author or at least a knowledgeable and qualified colleague) will be included. No-show papers are not to be published, per IEEE policy. (Application for publication with IEEE is in progress)

Outstanding papers will be invited to submit extended versions to appear in Special Issues of IEEE GRSS journals.

Publication & Indexing

Preparation: Please use the provided templates (Word | Latex) for MIGARS 2026. They closely align with the more generic IEEE Manuscript Templates for Conference Proceedings. The templates include detailed formatting guidelines.

(Final) Manuscript: Two-columns, four (4) pages maximum (including figures, tables, bibliography, and any notes/appendices). This is a strict limit for accepted submissions.

AI GENERATED TEXT POLICY and IEEE GUIDELINES

MIGARS 2026 prohibites the submission of manuscripts generated by large-scale language models (LLMs) and similar artificial intelligence (AI) systems. Only light editing of the authors’ original text, limited to spelling and grammar corrections, is allowed.

Authors must comply with the guidelines on the use and disclosure of content generated by artificial intelligence (AI) specified in the IEEE Publication Services and Products Board Operations Manual:

8.2.1.B.10:

The use of content generated by artificial intelligence (AI) in an article (including but not limited to text, figures, images, and code) shall be disclosed in the acknowledgments section of any article submitted to an IEEE publication. The AI system used shall be identified, and specific sections of the article that use AI-generated content shall be identified and accompanied by a brief explanation regarding the level at which the AI system was used to generate the content.

The use of AI systems for editing and grammar enhancement is common practice and, as such, is generally outside the intent of the above policy. In this case, disclosure as noted above is recommended.

8.2.1.C.5:

Information or content contained in or about a manuscript under review shall not be processed through a public platform (directly or indirectly) for AI generation of text for a review. Doing so is considered a breach of confidentiality because AI systems generally learn from any input.

  • Multispectral & hyperspectral remote sensing

  • Microwave remote sensing

  • LiDAR remote sensing

  • UAV-based remote sensing

  • Mission, Sensors, and Calibration

  • Big data applications for geosciences

  • Geospatial data analytics

  • Statistical machine learning

  • Deep learning

  • Expert systems

  • Computational intelligence

  • Evolutionary computing

  • Climate informatics

  • Data analysis and spatial data visualisation

  • Temporal data analysis, prediction, time series analysis

  • Uncertainty quantification in geoscience and remote sensing

  • Monitoring and damage assessment of natural disasters and hazards

  • Applications for early warning, environmental monitoring and climate change

  • Applications for land, biodiversity and soil science

  • Applications for forestry and agriculture

  • Applications for water management, sea, oceans and atmosphere

Key Topics

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