Terrain Data Fusion

Terrain Data Fusion is a methodological framework that integrates heterogeneous terrain datasets from multiple sources into a unified, coherent representation by resolving inconsistencies in spatial resolution, geometry, and semantics to enhance modeling accuracy and completeness.

27

Publications

744

Citations

97

Authors

54

Institutions

Publications per year

2017–2026

11

Authors

97

  1. EN
    Eric Nettleton

    The University of Sydney, Australia

    2 publications · 40 citations

    2

    h-index

  2. HD
    Hugh Durrant‐Whyte

    The University of Sydney, Australia

    2 publications · 40 citations

    2

    h-index

  3. SV
    Shrihari Vasudevan

    Australian Centre for Robotic Vision, Australia

    2 publications · 40 citations

    2

    h-index

  4. LY
    Linwei Yue

    Wuhan University, China

    1 publications · 50 citations

    1

    h-index

  5. NS
    Nikolaos Soulakellis

    University of the Aegean, Greece

    1 publications · 28 citations

    1

    h-index

1–5 of 97

Venues

  1. 2

    h-index

  2. IEEE Robotics and Automation Letters

    1 publications · 28 citations

    1

    h-index

  3. Journal of Sensors

    1 publications · 14 citations

    1

    h-index

  4. Open Geospatial Data Software and Standards

    1 publications · 40 citations

    1

    h-index

  5. 1

    h-index

1–5