Report on the 2025 IEEE GRSS Data Fusion Contest: All-Weather Land Cover and Building Damage Mapping [Technical Committees]

Over the past two decades, the annual Data Fusion Contest (DFC) has emerged as a platform that invites researchers worldwide to advance data fusion and image analysis methodologies. The contest focuses on the challenges of handling large-scale, multisensor, multimodal, and multitemporal data, fostering innovation in remote sensing research. The past editions have introduced novel and demanding problem settings, thereby creating benchmarks that have shaped progress in the field. The contest has been hosted annually since 2006 by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref>, <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref>, <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref>, <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref>, <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref>, <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref>, <xref ref-type="bibr" rid="ref7" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[7]</xref>, <xref ref-type="bibr" rid="ref8" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[8]</xref>, <xref ref-type="bibr" rid="ref9" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[9]</xref>, <xref ref-type="bibr" rid="ref10" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[10]</xref>, <xref ref-type="bibr" rid="ref11" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[11]</xref>, <xref ref-type="bibr" rid="ref12" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[12]</xref>, <xref ref-type="bibr" rid="ref13" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[13]</xref>, <xref ref-type="bibr" rid="ref14" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[14]</xref>, <xref ref-type="bibr" rid="ref15" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[15]</xref>, <xref ref-type="bibr" rid="ref16" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[16]</xref>, <xref ref-type="bibr" rid="ref17" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[17]</xref>, <xref ref-type="bibr" rid="ref18" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[18]</xref>, <xref ref-type="bibr" rid="ref19" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[19]</xref>, <xref ref-type="bibr" rid="ref20" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[20]</xref>, <xref ref-type="bibr" rid="ref21" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[21]</xref>. This year’s contest focus was all-weather land cover and building damage mapping.

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Publication Details

Journal
IEEE Geoscience and Remote Sensing Magazine
Published
2025-12-01
DOI
https://doi.org/10.1109/mgrs.2025.3609887
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
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article

Report on the 2025 IEEE GRSS Data Fusion Contest: All-Weather Land Cover and Building Damage Mapping [Technical Committees]

Junshi Xia, Hongruixuan Chen, Konrad Schindler, Claudio Persello et al.
IEEE Geoscience and Remote Sensing Magazine
Remote-Sensing Image Classification
article

Report on the 2025 IEEE GRSS Data Fusion Contest: All-Weather Land Cover and Building Damage Mapping [Technical Committees]

Junshi Xia, Hongruixuan Chen, Konrad Schindler, Claudio Persello, Naoto Yokoya, Saurabh Prasad, Gemine Vivone, Ujjwal Verma, Clifford Broni-Bediako, Olivier Dietrich, Jian Song
article en

Abstract

Over the past two decades, the annual Data Fusion Contest (DFC) has emerged as a platform that invites researchers worldwide to advance data fusion and image analysis methodologies. The contest focuses on the challenges of handling large-scale, multisensor, multimodal, and multitemporal data, fostering innovation in remote sensing research. The past editions have introduced novel and demanding problem settings, thereby creating benchmarks that have shaped progress in the field. The contest has been hosted annually since 2006 by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref>, <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref>, <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref>, <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref>, <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref>, <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref>, <xref ref-type="bibr" rid="ref7" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[7]</xref>, <xref ref-type="bibr" rid="ref8" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[8]</xref>, <xref ref-type="bibr" rid="ref9" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[9]</xref>, <xref ref-type="bibr" rid="ref10" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[10]</xref>, <xref ref-type="bibr" rid="ref11" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[11]</xref>, <xref ref-type="bibr" rid="ref12" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[12]</xref>, <xref ref-type="bibr" rid="ref13" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[13]</xref>, <xref ref-type="bibr" rid="ref14" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[14]</xref>, <xref ref-type="bibr" rid="ref15" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[15]</xref>, <xref ref-type="bibr" rid="ref16" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[16]</xref>, <xref ref-type="bibr" rid="ref17" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[17]</xref>, <xref ref-type="bibr" rid="ref18" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[18]</xref>, <xref ref-type="bibr" rid="ref19" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[19]</xref>, <xref ref-type="bibr" rid="ref20" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[20]</xref>, <xref ref-type="bibr" rid="ref21" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[21]</xref>. This year’s contest focus was all-weather land cover and building damage mapping.

IEEE Geoscience and Remote Sensing MagazineVol. 13(4)
Manipal Academy of Higher Education (IN), ETH Zurich (CH), CNR-IMIOT – Consiglio Nazionale delle Ricerche - Istituto di Metodologie Integrate per l’Osservazione della Terra (IT), RIKEN Center for Advanced Intelligence Project (JP), University of Houston (US), The University of Tokyo (JP), University of Twente (NL)
Openalex Percentile: Top 47%
Remote-Sensing Image Classification
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