A scale-invariant change detection method for land use/cover change research
- Submitting institution
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University of Newcastle upon Tyne
- Unit of assessment
- 12 - Engineering
- Output identifier
- 254698-256735-1293
- Type
- D - Journal article
- DOI
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10.1016/j.isprsjprs.2018.04.013
- Title of journal
- ISPRS Journal of Photogrammetry and Remote Sensing
- Article number
- -
- First page
- 252
- Volume
- 141
- Issue
- -
- ISSN
- 0924-2716
- Open access status
- Deposit exception
- Month of publication
- May
- Year of publication
- 2018
- URL
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https://doi.org/10.1016/j.isprsjprs.2018.04.013
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper introduces a new scale invariant land use/cover change detection algorithm that relies on scale invariant image features. Previous change detection algorithms largely rely on interpolation techniques to address the scale heterogeneity, but our method provides an alternative way with higher accuracy. When the scale difference becomes so large to invalidate most of existing algorithms, our method could still work by comparing multi-level scale-invariant features. There is a bunch of publications that implement our algorithms as the reference study. And the first author has been nominated for the William Garrison Award thanks to this paper.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -