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Changelog

tidymapr 0.1.0

  • First CRAN release.

User guide (November 2026)

  • A seven-chapter User guide on the website: installing and running tidymapr in RStudio; cartography concepts; spatial autocorrelation; interpolation and kriging; species distribution models; remote sensing and terrain; point clusters and landscape metrics. Each chapter gives the concept and theory, runnable code on real data, figures and tables, how to interpret them and a model paragraph for reporting.
  • geo_moran() accepts sf tables and projected coordinates: distances are now great-circle metres for longitude/latitude and straight-line distances in the CRS units otherwise. Before, projected coordinates were read as degrees, which hid real autocorrelation.
  • map_points(), map_lines() and map_polygons() honour a named palette for categories (for example c(hot = "red", cold = "blue")); before, the colours were assigned in alphabetical order of the categories, whatever their names. Factor columns keep their level order.

New documentation (November 2026)

  • The website is rewritten around the current features: a new Get started guide, two case studies (species distribution of the brown-throated sloth; tree diversity across Barro Colorado Island), a spatial analysis guide and a gallery with the code of every map. All use real, published data. The navigation now matches tidydiversity’s.
  • geo_hotspot() and geo_lisa() accept sf tables directly.
  • map_raster() gains limits, so rasters in several panels can share one colour scale and one legend.
  • geo_panels(guides = "keep") no longer overrides each map’s own legend position (including legend = "none").
  • Web map legends round their labels to the precision of the data.
  • World maps from geo_automap() are centred on Greenwich again, features crossing the date line (Russia, Fiji) are split there instead of being stretched across the map, and the frame shows the whole globe.
  • Coordinate labels that would overlap on narrow maps and panels are dropped.
  • tidymapr ships a 90 m Copernicus elevation model of Mt Wilhelm, Papua New Guinea (inst/extdata/wilhelm-dem.tif), used in the 3D examples.
  • The case studies and README explain how to read the uncertainty and disagreement maps.

Interactive web maps (November 2026)

  • geo_webmap() turns a geo_map() (or one sf or raster layer) into a self-contained interactive web page built on Leaflet: pan and zoom, four basemaps, layers that switch on and off, attribute pop-ups, permanent labels, a scale bar and a legend with the same symbols, classes and presets as the printed map. Features are embedded as GeoJSON and rasters as images, so the single HTML file can be emailed or published; Leaflet is loaded with Subresource Integrity.

Symbology presets (November 2026)

  • map_polygons(), map_lines() and map_points() take preset, a standard cartographic symbol by name (water, forest, protected area, administrative unit, river, main road, railway, boundary, contour, town, peak, sample site and more); arguments you set yourself override it. map_presets() lists them. Polygons gain linetype for dashed outlines.

GeoSpaX plug-in tools (November 2026)

  • geo_dbscan() clusters points with DBSCAN in C++ (grid index), with eps in metres on the ground for geographic data and a convex-hull outline per cluster. It gives the same partition as the dbscan package.
  • geo_landscape() computes FRAGSTATS fragmentation metrics by class (np, ca, pland, lpi, area_mn, ed, ai, mesh) and for the landscape (with Shannon’s and Simpson’s diversity). They match landscapemetrics on projected rasters to machine precision, and unlike landscapemetrics they measure geographic (degree) rasters in true hectares and metres.
  • Projections chosen from data that cross the antimeridian (Fiji, New Zealand, Kiribati) now centre on the data, not on longitude 0.

3D terrain maps (November 2026)

  • geo_map3d() renders a DEM as a 3D block diagram with sun lighting and cast shadows, any viewing direction and angle, automatic vertical exaggeration, hypsometric tints or any raster draped on the surface, and sites or routes placed on the terrain and hidden behind hills. The renderer is written in C++ (no OpenGL, rgl or rayshader), so it runs on servers and in reports and returns an ordinary ggplot. Empty wedges left by reprojection are trimmed so the block has clean sides.

Maxent and ensemble models in C++ (November 2026)

  • sdm_maxent() fits Maxent as maxnet does (infinitely weighted logistic regression with the lasso, the same feature classes and default regularisation), with the lasso path solved in C++ (coordinate descent with strong rules and active sets, on several cores): no Java and no glmnet. It agrees with maxnet to a correlation of 0.999 or more on the Bradypus data (Phillips et al. 2006). It fixes three weaknesses of maxnet:

    • predictors are standardised to 0-1 before features are built (as in the original Java Maxent), so quadratic and product features no longer depend on where zero lies: in maxnet, temperatures in Kelvin instead of Celsius change predicted suitability by up to 0.13 on the Bradypus data; here they change nothing. standardize = FALSE reproduces maxnet;
    • the duplicated outermost hinge feature that maxnet builds for every predictor is kept once;
    • the solver centres features internally, which makes it converge reliably where unscaled features stall coordinate descent.

  • sdm_ensemble() combines Maxent, GLM, GAM and a C++ random forest in the spirit of biomod2: spatial block cross-validation with folds balanced for presences and background, AUC, TSS and the continuous Boyce index, weights from cross-validated TSS above min_tss, balanced weighting of presences and background for every algorithm, and predictions of the weighted mean and the weighted disagreement (SD) between algorithms. The C++ random forest matches randomForest’s accuracy and is about 18 times faster.

  • geo_map(crs = "laea") and other named projections now centre on raster layers too.

  • geo_stac_search() finds scenes in any STAC catalogue (default: Element 84 Earth Search: Sentinel-2, Landsat, Copernicus DEM) by area, period and cloud cover, and returns their footprints as an sf table.

  • geo_stac_read() reads chosen bands over an area only (windowed reads of cloud-optimised GeoTIFFs), applies the catalogue’s scale and offset (skipping it where Earth Search has already applied it), mosaics tiles and takes the per-pixel median of several scenes to remove clouds. geo_stac_collections() lists a catalogue’s collections. Needs the suggested package httr2.

  • geo_spectral_index() recognises STAC band names (red, nir, …) and returns NA where a normalised difference has no signal.

Curved labels (November 2026)

  • The README shows a new gallery of maps made from real data: layered maps, automatic world maps, diversity surfaces, spectral diversity, curved labels, contours, insets, small multiples and GeoSpaX recipes.
  • map_curved_labels() writes labels that follow the shape of any feature: along lines (road and river names), along the long axis or the outline of polygons, or on an arc above points. Text stays upright, jagged paths are smoothed, and labels that do not fit are left out. map_line_labels() is the same for lines. Needs the suggested package geomtextpath.
  • map_contours() draws contour lines of a raster, with every second contour thicker and labelled with its height at its straightest stretch.

Multi-panel figures (November 2026)

  • map_zoom() zooms a geo_map() in or out (zoom = 2 is twice as close), on the centre or on a centre = c(lon, lat), or shows an exact extent; the scale bar follows the zoom.
  • geo_panels() arranges maps from geo_map(), geo_automap() or any ggplot in a grid, tagged (a), (b), …, with matching legends collected into one and a figure title and caption.
  • geo_facet_map() draws small multiples (by a grouping column, or one panel per value column) with one classification shared by all panels, one legend, and the scale bar and north arrow in the first panel only.
  • geo_inset() places a locator map on a larger map. By default (location = "auto") it takes a corner free of the scale bar, north arrow and any legend inside the map, and of those the one hiding the least of the mapped features; a corner name or any c(x, y) position also works.
  • geo_map(legend = "inside") puts the legend in a framed box on the map, in a corner chosen the same way (or set with legend_corner). map_legend(position = "inside") does the same for any map.

Layered maps (November 2026)

  • New layered-map builder in the style of a desktop GIS layout: start with geo_map() and add map_raster() (gradient legend, optional hillshade), map_polygons(), map_lines(), map_points() and map_labels() (labels with a white halo). Each layer gets its own legend section with the right symbol for its geometry, listed top layer first; numbers are classed with geo_classify(). map_build() returns an ordinary ggplot. Needs the suggested package ggnewscale.
  • Named sequential palettes now run light (low) to dark (high), except terrain and viridis-type ramps, which keep their own order.

Recipe exchange with GeoSpaX (November 2026)

  • New geo_recipe_read(), geo_recipe_write(), geo_recipe_validate() and geo_recipe_run() read, write, check and run GeoSpaX recipes (version 1 and 2 YAML), so a workflow built in GeoSpaX runs in R and the other way round. geo_recipe(), recipe_input() and recipe_step() build recipes in R.
  • Supported steps: io.open, interpolate.idw, interpolate.auto (kriging against IDW by leave-one-out error, with a standard-error map), aggregate.hexbin, stats.hotspots (Getis-Ord Gi* with FDR-corrected 90/95/99% classes), automap.style, style.apply, layout.auto, terrain.derive, rs.index, export.map/png/svg/pdf, export.data and export.report (an HTML report with the maps, decisions and run log). Steps that only GeoSpaX can run are reported by geo_recipe_validate().
  • Three GeoSpaX recipes ship in inst/recipes: interpolate-samples, points-to-hotspots and points-to-hexbins.
  • Hot spot maps use the conventional diverging colours (reds for hot, blues for cold, grey for not significant).
  • GeoSpaX is now linked: https://geospax.in4metrix.dev.

A wider scope (November 2026)

  • tidymapr is now a general toolkit for mapping, spatial analysis and publication cartography, not only for biodiversity: new title “Tidy Mapping, Spatial Analysis and Publication Cartography”. It is compatible with the GeoSpaX desktop GIS (same cartographic conventions, same formats through GDAL) and remains the mapping companion to tidydiversity for ecology. No functions were renamed.
  • The reference is regrouped into Maps and cartography, Spatial analysis, Terrain and hydrology, Remote sensing, Data input and output, and Ecology with tidydiversity.

Install the latest version with pak::pak("jmozez/tidymapr").

New maps (November 2026)

  • New plot_choropleth() shades polygons by a numeric column, grouped into classes with geo_classify() (quantile, equal, Fisher-Jenks, pretty, standard deviation or fixed breaks). It uses colour-blind-safe sequential palettes from grDevices::hcl.colors() (default "YlGnBu", light for low values and dark for high). The breaks, counts per class and goodness of variance fit are kept with the plot.
  • New plot_bubble() draws proportional-area circles for counts such as species richness or abundance, from an sf point table or a lon/lat data frame, optionally coloured by group and over a background layer. Sites with a value of zero (sampled, nothing found) are shown as small open circles, so absences stay on the map. The example maps ant species on the 16 Mt Wilhelm transects, where no ants were found above 2,200 m.
  • geo_basemap(), plot_sites(), plot_geo(), plot_topo() and plot_sdm() gain new basemaps, all free and needing no API key:
    • topographic and street tiles: "topo" (OpenTopoMap, with contours and hillshade), "osm_hot" (OpenStreetMap Humanitarian), "carto_voyager", "esri_street", "esri_relief" (shaded relief), "esri_terrain" and "esri_natgeo" (National Geographic), alongside the existing "esri", "esri_topo", "osm", "carto" and "carto_dark";
    • built from an elevation model: "hillshade", "contour" (labelled contour lines) and "terrain" (both). Pass your own DEM with dem (works offline), or let geo_elevation() download one for the map extent; set the contour interval with contour_breaks.
  • Map furniture in the GeoSpaX styles, for any ggplot map with coord_sf(). You pick the style:
    • annotation_scale_bar(): "pill", "checker", "line" or "ruler", in "metric", "imperial" or "both" units. Its length is measured on the ground when the map is drawn, so it is right on longitude/latitude and projected maps and in every facet.
    • annotation_north_arrow(): "needle", "compass", "rose" or "minimal".
    • map_legend(): legend "right", "bottom", "inside" a chosen corner or "none", with its title, renamed entries (labels), hidden legends (hide), frame, text, title and key sizes, columns, direction and order.
  • plot_sites(), plot_geo() and plot_sdm() accept these style names in scale_bar and north_arrow (TRUE keeps the default, FALSE turns them off), and plot_sites() and plot_geo() gain scale_units. Their maps keep the full planned extent around the sites.
  • Tile maps now carry each provider’s required attribution (for example “© OpenStreetMap contributors”) as the plot caption.

Spectral diversity and spectral indices (November 2026)

  • New geo_spectral_diversity() maps diversity from satellite or drone imagery in Hill numbers (q = 0, 1, 2), on the same scale as species diversity: bands are reduced by principal components, pixels grouped into spectral species by k-means (Féret and Asner 2014), and Hill numbers computed in a moving window in C++ on several cores. Results equal direct Hill-number calculations to machine precision.
  • New geo_spectral_index() computes NDVI, GNDVI, NDRE, NDWI, MNDWI, NDMI, NBR and NDBI (Sentinel-2 bands recognised automatically), with an optional Otsu threshold that reports the area above the cut, as in GeoSpaX’s Forestry plug-in.
  • Examples use the Sentinel-2 Level-2A scene of Luxembourg shipped with terra.

Automatic publication maps (November 2026)

  • New geo_automap() draws a finished map from one call and explains every choice; geo_automap_explain() returns the decisions as a table for a methods section. Following GeoSpaX’s AutoMap and ArcGIS/QGIS practice:
    • projection by extent: Equal Earth for world data, Lambert equal-area for regions, the local UTM zone for study areas (longitude/latitude when raster tiles or a surface are drawn);
    • numbers on points, lines and polygons get graduated colours in classes (a classed legend, never a continuous ramp): equal intervals when roughly symmetric, natural breaks when skewed, quantiles when heavy-tailed; 5 classes for 30 or more features, fewer for small samples; the colour ramp follows the field’s meaning (blues for water, greens for vegetation, viridis for elevation, diverging across zero);
    • small counts on points get proportional circles, categories get Okabe-Ito colours, plain sites a single symbol;
    • a continuous surface (a raster, or a new background such as a DEM under the sites) gets a stretched ramp with a gradient legend, while the sites keep their own symbol legend;
    • topographic tiles as muted context for study areas; graticule and world outline on world maps; scale bar and north arrow in the emptiest corners on regional and local maps.
  • geo_automap() takes palette and background_palette: "auto", any grDevices::hcl.pals() name (for example "viridis", "Blues 3", "Terrain 2") or your own colours. Every map is also a ggplot, so any scale_fill_*() or scale_colour_*() can replace a ramp with +.
  • Scale bars drop the middle label when the bar is short, so labels never collide.

Diversity surfaces with uncertainty (November 2026)

  • New geo_diversity_surface() turns a community table into continuous maps of Hill-number diversity (q = 0, 1, 2) with 95% intervals:
    1. each site’s diversity is standardised to a common sample coverage with tidydiversity::div_standardise() (Chao and Jost 2012), keeping its bootstrap standard error;
    2. each order q is interpolated by kriging with measurement error (Cressie 1993) on the log scale, so poorly sampled sites count for less and the map shows the underlying diversity rather than sampling noise;
    3. the interval combines spatial and estimation uncertainty. The example maps tree diversity across the 50-ha Barro Colorado Island forest plot (vegan::BCI).
  • New plot_diversity_surface() draws the surfaces with a matching row of uncertainty maps and the sampled sites.
  • Kriging now accepts per-site measurement-error variances (C++); with a common error it equals gstat’s "Err" variogram model.

Faster: C++ and multi-core (November 2026)

  • The most demanding calculations now run in C++ and use several CPU cores (OpenMP). Set the number with options(tidymapr.threads = n); by default tidymapr uses all cores but one. Timings on 4 cores:
    • geo_lisa() permutation test (500 sites, 999 permutations): 5 s to 0.05 s;
    • kriging in geo_interpolate() (300 points to 40,000 cells): 20 s to 0.9 s; new variance = FALSE skips the kriging variance for even larger grids;
    • inverse-distance weighting: 0.8 s to 0.04 s;
    • nearest-neighbour search for geo_hotspot() and geo_lisa(): about 4 times faster;
    • geo_mem() minimum spanning tree (Prim’s algorithm): about 10 times faster and now scales to thousands of sites.
  • Results are unchanged: they still equal spdep and gstat, and permutation p-values are the same for a given seed whatever the number of cores.

Projections and graticules (November 2026)

  • New coord_projection() draws any tidymapr or ggplot map in a named projection, added with +: "equal_earth" (true areas, recommended for world choropleths), "mercator" (World Mercator), "web_mercator" (matches online tiles), "robinson", "mollweide", "winkel_tripel", "lonlat", "utm" (zone picked from your data), and "laea", "albers" and "orthographic" centred on your data. Any EPSG code or PROJ string also works, and world projections take lon0, for example lon0 = 150 for a Pacific-centred map.
  • New geo_crs() returns the CRS for those names, for reprojecting data.
  • New map_graticule() sets the latitude/longitude grid interval and line style, labels latitudes, longitudes, both or neither (on curved world projections it labels latitudes only, so longitude labels do not crowd the pole line), and can draw the edge of the world or, on orthographic maps, the horizon circle.
  • Examples use spData::world (Natural Earth and World Bank, free to use) for world maps.

Reading GIS, CAD and remote sensing files (November 2026)

  • geo_read() now reads many more formats through GDAL:
    • remote sensing and climate rasters: netCDF (.nc, .nc4, .cdf), HDF4/HDF5 (MODIS, VIIRS, GEDI), GRIB weather files, Sentinel-2 .SAFE folders and zips, JPEG 2000, ENVI cubes (a .dat/.bin with its .hdr), ERDAS Imagine, Zarr, VRT, IDRISI, SAGA and ER Mapper;
    • several band files at once (for example Landsat or Sentinel-2 bands), stacked into one multi-band raster;
    • CAD drawings: AutoCAD .dxf and .dwg and MicroStation .dgn, with cad_layer to keep chosen AutoCAD layers (DGN levels) and crs to set the coordinate system CAD files do not store;
    • vector formats: FlatGeobuf, GPX, MapInfo, SpatiaLite, TopoJSON, OpenStreetMap .osm/.pbf, S-57 nautical charts and spreadsheets (.xlsx, .xls, .ods).
  • New var argument to pick netCDF, HDF and GRIB variables by name or number; several variables are combined into one raster, and time steps stay in terra::time().
  • New geo_layers() shows what a file holds before you read it: vector layers, netCDF/HDF variables and subdatasets, CAD layers or raster bands.

Earlier additions