| Kategorie |
Textpublikation |
| Referenztyp |
Zeitschriften |
| DOI |
10.1111/2041-210X.14226
|
Lizenz  |
|
| Titel (primär) |
hydrographr: An R package for scalable hydrographic data processing |
| Autor |
Schürz, M.; Grigoropoulou, A.; García Márquez, J.; Torres-Cambas, Y.; Tomiczek, T.; Floury, M.; Bremerich, V.; Schürz, C.; Amatulli, G.; Grossart, H.-P.; Domisch, S. |
| Quelle |
Methods in Ecology and Evolution |
| Erscheinungsjahr |
2023 |
| Department |
CLE |
| Band/Volume |
14 |
| Heft |
12 |
| Seite von |
2953 |
| Seite bis |
2963 |
| Sprache |
englisch |
| Topic |
T5 Future Landscapes |
| Daten-/Softwarelinks |
https://doi.org/10.15468/dl.hpt8k8
https://doi.org/10.15468/8cxijb
https://doi.org/10.18728/igb-fred-778.3 |
| Supplements |
https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F2041-210X.14226&file=mee314226-sup-0001-Supporting_InformationS1-S5.zip |
| Keywords |
connectivity; hydrographic data processing; Hydrography90m; river; R-package; scalability; spatial freshwater biodiversity; stream network |
| Abstract |
- Freshwater
ecosystems are considered biodiversity hotspots, but assessing the spatial
distribution of species remains challenging. One major obstacle lies in
the complex geospatial processing of large amounts of data, such as stream
network, sub-catchment and basin data, that are necessary for addressing
the longitudinal connectivity among water bodies. Workflows thus need to
be scalable, especially when working across large spatial extents and at
high spatial resolution. This in turn requires advanced command-line GIS
skills and programming language integration, which often poses a challenge
for freshwater researchers.
- To address
this challenge, we developed the package hydrographr that
provides scalable hydrographic data processing in R. The package contains
functions for downloading data of the high-resolution Hydrography90m
dataset, processing, reading and extracting information, as well as
assessing network distances and connectivity. While the functions are, by
default, tailored toward the Hydrography90m data, they can also be
generalised toward other data and purposes, such as efficient cropping and
merging of raster and vector data, point-raster extraction, raster
reclassification and data aggregation. The package depends on the
open-source software GDAL/OGR, GRASS-GIS and the AWK programming language
in the Linux environment, allowing a seamless language integration. Since
the data is processed outside R, hydrographr allows creating
scalable geo-processing workflows.
- We
illustrate the hydrographr functions using two workflows that focus on (i) a freshwater
species distribution modelling approach, and (ii) assessing stream
connectivity given the fragmentation by dams. We also provide a detailed
guide for the initial installation of the required software. Windows users
need to first enable the Windows Subsystem for Linux (WSL) feature, and
can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr.
- hydrographr
provides a set of key functions for processing freshwater geospatial data.
We expect that the package will support the freshwater-related research
communities given the easy-to-use wrapper functions that allow
capitalizing on powerful open-source command-line software, which may
otherwise require a steep learning curve. Users can thus perform
large-scale freshwater-specific longitudinal connectivity and network
analyses across large geographic extents while staying within the R
environment.
|
| dauerhafte UFZ-Verlinkung |
https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=28014 |
Schürz, M., Grigoropoulou, A., García Márquez, J., Torres-Cambas, Y., Tomiczek, T., Floury, M., Bremerich, V., Schürz, C., Amatulli, G., Grossart, H.-P., Domisch, S. (2023):
hydrographr: An R package for scalable hydrographic data processing
Methods Ecol. Evol. 14 (12), 2953 - 2963 10.1111/2041-210X.14226 |
