A computational framework for generalized moving windows and its application to landscape pattern analysis
- Submitting institution
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The University of Surrey
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9019023_1
- Type
- D - Journal article
- DOI
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10.1016/j.jag.2015.09.010
- Title of journal
- International Journal of Applied Earth Observation and Geoinformation
- Article number
- -
- First page
- 205-216
- Volume
- 44
- Issue
- -
- ISSN
- 0303-2434
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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-
- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The methods are shared as an open source C++ library (https://github.com/ahhz/raster), which has received “Stars” from renowned experts in scientific geospatial computing: Michael Sumner, Mateusz Loskot, Robin Lovelace and others. It has received further recognition by acceptance as a community project of the Open Source Geospatial Foundation (OSGEO) (https://www.osgeo.org/projects/pronto-raster/) , and live-streamed presentations to the open source community (https://archive.fosdem.org/2018/schedule/event/geo_blink). The methods have been re-implemented as a package in R, a leading tool in scientific computing (https://www.rdocumentation.org/packages/landscapemetrics/versions/1.5.0/topics/window_lsm). This brings new and unique capabilities to a wide audience of researchers and practitioners in environmental studies, landscape ecology, urban analytics and more.
- Author contribution statement
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- Non-English
- No
- English abstract
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