Direct Change Detection

Direct Change Detection is a methodological framework in spatial analysis that identifies alterations between geographic states at different time points by directly comparing raw or minimally processed observational data, without reliance on intermediate representations or indirect inference mechanisms.

19

Publications

1K

Citations

48

Authors

38

Institutions

Publications per year

2017–2026

3

Authors

48

  1. HM
    Harumitsu Murohashi

    Hokkaido University, Japan

    2 publications · 53 citations

    2

    h-index

  2. MK
    Motohiro Kimura

    Nagoya University, Japan

    2 publications · 53 citations

    2

    h-index

  3. JK
    Jun’ichi Katayama

    Hokkaido University of Education, Japan

    2 publications · 53 citations

    2

    h-index

  4. NO
    Nicholas O’Donoughue

    Carnegie Mellon University, United States

    1 publications · 10 citations

    1

    h-index

  5. CB
    Chan Beals

    Merck & Co., Inc., Rahway, NJ, USA (United States), United States

    1 publications · 22 citations

    1

    h-index

1–5 of 48

Venues

  1. International Journal of Psychophysiology

    2 publications · 52 citations

    2

    h-index

  2. PLoS ONE

    1 publications · 12 citations

    1

    h-index

  3. Osteoarthritis and Cartilage

    1 publications · 22 citations

    1

    h-index

  4. Perception & Psychophysics

    1 publications · 53 citations

    1

    h-index

  5. BMC Genomics

    1 publications · 88 citations

    1

    h-index

1–5