The Roaring Landmask

Have you ever needed to know whether you are in the ocean or on land? And you need to know it fast? And you need to know it without using too much memory or too much disk? Then try the Roaring Landmask!

The roaring landmask is a Rust + Python package for quickly determining whether a point given in latitude and longitude is on land or not. A landmask is stored in a tree of Roaring Bitmaps. Points close to the shore might still be in the ocean, so a positive value is then checked against the vector shapes of the coastline.

(source)

The landmask is generated from the GSHHG shoreline database (Wessel, P., and W. H. F. Smith, A Global Self-consistent, Hierarchical, High-resolution Shoreline Database, J. Geophys. Res., 101, 8741-8743, 1996).

An alternative is the opendrift-landmask-data, which is slightly faster, is pure Python, but requires more memory and disk space (memory-mapped 3.7Gb).

Performance

Microbenchmarks:

test tests::test_contains_in_ocean ... bench: 24 ns/iter (+/- 0) test tests::test_contains_on_land ... bench: 3,795 ns/iter (+/- 214)

Many points, through Python:

``` ------------------------------------------------ benchmark: 1 tests -----------------------------------------------

Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations

testlandmaskmany 147.9902 150.2231 149.2532 1.0469 149.7798 1.8760 1;0 6.7000 5 1

```

opendrift-landmask-data uses about 120 ms on the same benchmark.

Usage from Python

```python from roaring_landmask import RoaringLandmask

l = RoaringLandmask.new() x = np.arange(-180, 180, .5) y = np.arange(-90, 90, .5)

xx, yy = np.meshgrid(x,y)

print ("points:", len(xx.ravel())) onland = l.containsmany(xx.ravel(), yy.ravel()) ```

Building & installing

Pre-built wheels are available on PyPI:

1) pip install roaring-landmask

To build from source, you can use pip:

1) pip install .

or maturin:

1) Install maturin.

2) Build and install

maturin build --release pip install target/wheels/... # choose your whl