3-D uncertainty-based topographic change detection with structure-from-motion photogrammetry: precision maps for ground control and directly georeferenced surveys
- Submitting institution
-
University College London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12293
- Type
- D - Journal article
- DOI
-
10.1002/esp.4125
- Title of journal
- EARTH SURFACE PROCESSES AND LANDFORMS
- Article number
- -
- First page
- 1769
- Volume
- 42
- Issue
- 12
- ISSN
- 0197-9337
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fesp.4125&file=esp4125-sup-0001-supplementary.zip
- 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
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Multidisciplinary authors (James, Robson, Smith) have uniquely developed rigorous photogrammetric measurement error maps for drone surveys. These enable quantitative comparison of subtly varying landform surfaces, fuelling the scientific take up of drone mapping across the geosciences. A highest-scoring output in the leading journal in its discipline (#27 of 901 (July 2020)) and in the top 10% of all Altmetric tracked outputs, the paper has inspired a drone mapping assessment tool [www.lancaster.ac.uk/staff/jamesm/software/sfm_georef.htm] which augments, the leading commercial software in the field [Agisoft Metashape]. International excellence and take-up are evidenced by the wide range of outputs citing the paper (129 Nov 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -