Multimodal Data Fusion for Remote-Sensing Object Detection: A Systematic Review

NISHI MADAAN

doi:10.17605/osf.io/xfbj6

July 14, 2026Open Access

Multimodal Data Fusion for Remote-Sensing Object Detection: A Systematic Review

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Key Points

This review aims to summarize techniques and trends in multimodal data fusion for remote-sensing object detection.
Conducted a PRISMA 2020 systematic review and cross-dimensional meta-analysis.
Screened 145 studies, with 100 included in random-effects meta-analysis.
Analyzed data from studies spanning 2016 to 2026.
Identified a diverse range of methodologies utilized in multimodal data fusion.
Noted a significant improvement in object detection accuracy across integrated data sources.
Highlighted trends indicating increasing adoption of advanced fusion techniques.

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Implication

Systematic review and meta-analysis reveal trends in multimodal data fusion for remote-sensing object detection.

Abstract

PRISMA 2020 systematic review and cross-dimensional meta-analysis of multimodal data fusion for remote-sensing object detection (2016-2026). 145 studies screened, 100 pooled in random-effects meta-analysis

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NISHI MADAAN (2026) studied this question.

synapsesocial.com/papers/6a5875cb2b46c88ba9ad180f https://doi.org/10.17605/osf.io/xfbj6

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Multimodal Data Fusion for Remote-Sensing Object Detection: A Systematic Review

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Multimodal Data Fusion for Remote-Sensing Object Detection: A Systematic Review

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