belian-earth

belian-earth / a5R

Public

An R wrapper of the a5 rust crate

belian-earth.github.ioa5R
11
0
100% credibility
Found Feb 20, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
R
AI Summary

a5R is an R package providing tools to work with the A5 pentagonal discrete global grid system for converting geographic coordinates to equal-area cells and generating grids.

How It Works

1
🗺️ Discover fair Earth mapping

You hear about a special way to divide the whole Earth into equal pentagon shapes for better maps and data analysis.

2
📦 Get the mapping tool

You easily add this handy tool to your mapping software with a quick download.

3
🌍 Pick a spot on Earth

You choose longitude and latitude for a place like Edinburgh and turn it into a unique pentagon label.

4
🔍 Build a grid over any area

You draw a box around a region, like a city or country, and instantly get all the pentagons covering it perfectly.

5
📏 Explore the shapes

You see the exact outlines and sizes of these pentagons, even zooming in or out across levels.

🎉 Perfect map ready

Your map now has a beautiful, precise grid of equal-area pentagons, ready for analysis or visualization.

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AI-Generated Review

What is a5R?

a5R brings the A5 pentagonal discrete global grid system to R via a thin Rust wrapper, letting you snap lon/lat points to equal-area 64-bit cell IDs at 31 resolutions down to millimeter precision. You get vectorized ops for cell centroids, pentagonal boundaries as wk geometries, parent/child navigation, compaction, and grid generation over bboxes or sf shapes—even antimeridian-spanning ones. It slots into tidyverse workflows with vctrs-backed cell vectors and wk/sf/terra integration.

Why is it gaining traction?

Benchmarks crush Python/JS on 10k-element batches (36ms lonlat_to_cell vs 4s+), rivaling DuckDB thanks to Rust vectorization. No loops needed; feed tibbles directly for instant hierarchies or grids. Handles poles and dateline without hacks, outputting CRS-aware geometries that plot or pipe seamlessly.

Who should use this?

R spatial analysts discretizing global satellite/sensor data into compact IDs for aggregation. GIS devs building hierarchical indexes for environmental modeling or climate grids. Teams ditching lon/lat joins for faster, equal-area analysis in sf/terra pipelines.

Verdict

Experimental with 11 stars and 1.0% credibility score, but killer docs, CI checks, and codecov make it production-ready for niches. Use if A5 fits your workflow; track for wider adoption.

(178 words)

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