Sentinel-1
Sentinel-1 is a satellite-borne radar system that was recently launched and showed great potential for mapping biodiversity across large areas of temperate forests in central Europe. The study compared Sentinel-1's performance to airborne laser scanning (ALS), which is currently considered the best method for measuring forest structure.
The researchers found that Sentinel-1's sensitivity to habitat structure is comparable to that of ALS. When modeling different aspects of biodiversity for twelve taxa, Sentinel-1 performed as well as ALS, with median R² values of 0.57 and 0.51, respectively, for the first non-metric multidimensional scaling axes representing assemblage composition.
Furthermore, the study validated the predictive ability of Sentinel-1 data using external data on the species composition of birds and saproxylic beetles. The authors suggest that to establish new large-scale biodiversity monitoring using remote sensing, it will be necessary to combine Sentinel-1 data with stratified and standardized local species data collection.
Topic
Biodiversity;Mapping;Metagenomic sequencing
Detail
Operation: Scatter plot plotting;Standardisation and normalisation;Mapping
Software interface: Command-line user interface
Language: R
License: Not stated
Cost: Free of charge
Version name: v1.0
Credit: The Deutsche Forschungsgemeinschaft (DFG).
Input: -
Output: -
Contact: Soyeon Bae soyeon.grace.bae@gmail.com
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Maturity: -
Publications
- Radar vision in the mapping of forest biodiversity from space.
- Bae S, et al. Radar vision in the mapping of forest biodiversity from space. Radar vision in the mapping of forest biodiversity from space. 2019; 10:4757. doi: 10.1038/s41467-019-12737-x
- https://doi.org/10.1038/S41467-019-12737-X
- PMID: 31628336
- PMC: PMC6802221
Download and documentation
Source: https://github.com/So-YeonBae/Sentinel1-Biodiversity/releases/tag/v1.0
Documentation: https://github.com/So-YeonBae/Sentinel1-Biodiversity/blob/master/README.md
Home page: https://github.com/So-YeonBae/Sentinel1-Biodiversity
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