Changelog

Source: NEWS.md

sciSpatialR 0.1.0

First version. Everything below is new.

Reference layers

• ab_crs(), ab_boundary(), and ab_grid() return the project CRS (NAD83 / Alberta 10-TM, EPSG:3400), the 2020 provincial boundary, and the ABMI 1 km reference grid. The boundary and grid ship with the package, so the harmonization functions need only the layer being harmonized.
• The grid template is snapped to the lattice of the ABMI’s 1 km grid polygons, so a cell’s raster row and column reproduce its source GRID_LABEL.

Harmonization

• check_alignment() compares a layer against the reference on CRS, extent, resolution, and origin, and returns the result invisibly as a named logical vector so it can gate a pipeline.
• resample_to_grid() snaps a layer onto the reference lattice, choosing the resampling method from the resolution ratio and whether the layer is categorical, and reporting what it picked. It errors rather than silently returning an empty layer when the CRS does not already match.
• mask_to_boundary() clips to Alberta by default, or to a supplied polygon; inverse = TRUE keeps the outside instead.
• harmonize_crs() transforms points to the raster CRS and warns when raster reprojection would be implied.

Extraction

• extract_points() for point-in-cell values, extract_buffer() for summary statistics within one or more radii, extract_proportion() for class composition within a buffer, and extract_vector() for point-in-polygon attribute joins.
• All four return columns in input row order, so bind = FALSE results can be combined with a single cbind().

Inspection

• raster_stats() reports per-layer cell counts, missingness, and value summaries for a SpatRaster, a path, or a directory of GeoTIFFs.
• plot_raster() and plot_hist() return ggplot objects, with the colour scale clamped to central quantiles by default so a handful of extreme cells cannot flatten the pattern.
• theme_science_map() is exported for other figures in a project.

Catalogue and metadata

• build_catalogue() scans the ABMI spatial data share and parses every dataset readme into a manifest; list_themes(), list_layers(), find_layer(), get_layer(), and layer_files() query and retrieve from it.
• spatial_root() reports where the catalogue reads from and is overridable by option or environment variable.
• The share’s top-level _temp folder is skipped by every scan, so work in progress and staging copies are neither catalogued as layers nor reported as missing readmes by check_metadata().
• read_metadata(), as_metadata_row(), layer_meta(), and check_metadata() parse and audit the readme files stored beside each layer.

Documentation

• Four vignettes: harmonizing layers to the reference grid, inspecting layers, extracting covariates at survey locations, and working with the catalogue.
• A pkgdown site published at https://ABbiodiversity.github.io/sciSpatialR/.