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rspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 15 hours ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
560 stars 17.65 score 17k scripts 856 dependents
hypertidy
gdalio:Read Data to via GDAL Warper to an Assumed Grid
Convenience wrapper for the GDAL raster warper library. Set a default context grid, an extent, dimension, projection, and then read any GDAL raster source into that grid. There are controls to augment metadata-poor sources (to override missing or incorrect extent or projection metadata), to set a desired grid for subsequent use, and ability to control options available by the GDAL warp library itself. This can be used to easily read data from any kind of raster data source, local files, online servers, bare URLs, and database connections. Data is read in generic form but we provide example wrappers for commonly used formats for raster data.
Maintained by Michael D. Sumner. Last updated 3 years ago.
27 stars 4.56 score 27 scripts