International Journal of Image and Data Fusion

Aims & Scope

International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications.

Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making.

Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information.

This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management.

The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.3
2024	1.80

Journal Rank

Year	Value
2024	12427

Journal Citation Indicator

Year	Value
2024	126

SJR (SCImago Journal Rank)

Year	Value
2024	0.459

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	36

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Earth and Planetary Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Multi-source remote sensing data fusion: status and trends

  Citation: 576

  Authors: Jixian

• Multi-sensor image fusion for pansharpening in remote sensing

  Citation: 210

  Authors: Manfred, Sascha, Pär, Pablo

• Use of mobile LiDAR in road information inventory: a review

  Citation: 169

  Authors: Haiyan, Jonathan, Shuang, Yongtao

• Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran

  Citation: 147

  Authors: Jamal Jokar, Wolfgang, Ali Jafar

• Current situation and needs of change detection techniques

  Citation: 135

  Authors: Dengsheng, Guiying, Emilio

• 3D building modeling using images and LiDAR: a review

  Citation: 132

  Authors: Ruisheng

• Land-cover classification using both hyperspectral and LiDAR data

  Citation: 100

  Authors: Pedram, Jon Atli, Stuart

• Mapping of mineral resources and lithological units: a review of remote sensing techniques

  Citation: 99

  Authors: Rejith, Sundararajan

• Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing

  Citation: 98

  Authors: Jixian, Xiangguo

• Classification of SAR and PolSAR images using deep learning: a review

  Citation: 95

  Authors: Hemani, Samir, Vibha

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