Automated co-registration and calibration in SfM photogrammetry for landslide change detection
- Submitting institution
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University of Newcastle upon Tyne
- Unit of assessment
- 12 - Engineering
- Output identifier
- 251165-71176-1293
- Type
- D - Journal article
- DOI
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10.1002/esp.4502
- Title of journal
- Earth Surface Processes and Landforms
- Article number
- -
- First page
- 287
- Volume
- 44
- Issue
- 1
- ISSN
- 0197-9337
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- URL
-
https://doi.org/10.1002/esp.4502
- Supplementary information
-
-
- 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
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Doctoral research by Peppa from which this manuscript originated, funded by EPSRC/BGS and supervised by Mills, received the Remote Sensing and Photogrammetry Society Student Award for Best 2018 PhD Thesis. Ranked in the top 10% of papers published in ESP&L during 2018/19 for most downloads in the 12 months following online publication. Post-acceptance, Mills was invited to co-author "guidelines on the use of structure-from-motion photogrammetry in geomorphic research" for ESP&L (James et al., 2019) and present the research in an invited keynote (University of Bergen’s GEO Partner Day, Norway, 2018).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -