Geospatial Data Fusion

Geospatial Data Fusion is the integration of heterogeneous spatially referenced data from multiple sources or modalities into a unified representation, distinguished by its explicit consideration of geographic context, scale, and spatiotemporal relationships to enhance accuracy, completeness, and interpretability in geospatial analysis.

999

Publications

53.7K

Citations

3.1K

Authors

986

Institutions

Publications per year

2017–2026

570

Authors

3.1K

  1. BH
    Bo Huang

    Chinese University of Hong Kong, Hong Kong SAR China

    13 publications · 1.2K citations

    12

    h-index

  2. NY
    Naoto Yokoya

    The University of Tokyo, Japan

    12 publications · 699 citations

    12

    h-index

  3. XZ
    Xiaolin Zhu

    Hong Kong Polytechnic University, Hong Kong SAR China

    10 publications · 1.1K citations

    11

    h-index

  4. XX
    Xiao Xiang Zhu

    Technical University of Munich, Germany

    13 publications · 830 citations

    11

    h-index

  5. JC
    Jocelyn Chanussot

    Institut polytechnique de Grenoble, France

    10 publications · 2.3K citations

    10

    h-index

1–5 of 3.1K

Venues

  1. 38

    h-index

  2. Remote Sensing

    75 publications · 3.5K citations

    32

    h-index

  3. Remote Sensing of Environment

    23 publications · 3.7K citations

    22

    h-index

  4. 21

    h-index

  5. Information Fusion

    21 publications · 1.9K citations

    20

    h-index

1–5