Object-based Habitat Segmentation

Object-Based Habitat Segmentation is a computational method in remote sensing image analysis that partitions deep-sea habitat data into meaningful spatial units based on spectral, textural, and contextual properties, distinguishing itself from pixel-based approaches by incorporating object-level spatial coherence and scale-dependent segmentation.

6

Publications

299

Citations

35

Authors

15

Institutions

Publications per year

2017–2026

4

Authors

35

  1. MS
    Michal Segal‐Rozenhaimer

    Ames Research Center, United States

    1 publications · 41 citations

    1

    h-index

  2. VV
    Veerle Verschoren

    University of Antwerp, Belgium

    1 publications · 24 citations

    1

    h-index

  3. AM
    Anirban Mukhopadhyay

    Technische Universität Darmstadt, Germany

    1 publications · 25 citations

    1

    h-index

  4. ÉK
    Éva Kovács

    The University of Queensland, Australia

    1 publications · 139 citations

    1

    h-index

  5. VC
    Ved Chirayath

    Ames Research Center, United States

    1 publications · 41 citations

    1

    h-index

1–5 of 35

Venues

  1. Ecological Informatics

    2 publications · 84 citations

    2

    h-index

  2. Remote Sensing of Environment

    1 publications · 139 citations

    1

    h-index

  3. GIScience & Remote Sensing

    1 publications · 11 citations

    1

    h-index

  4. 1

    h-index

  5. Hydrobiologia

    1 publications · 24 citations

    1

    h-index

1–5