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tile-mate

PyPI license PyPI pyversions PyPI version Conda version Conda platforms

This library provides a tool to create continuous rasters of publicly available, global tile sets (in lat/lon) such as Pekel Occurence and ESA 10 m land cover. This is a simpler cousin of dem-stitcher without the need for basic post-processing (e.g. fractional pixel translation and vertical datum transformations).

The API can be summarized as

from tile_mate import get_raster_from_tiles

bounds = [-120.55, 34.85, -120.25, 35.15]
X, p = get_raster_from_tiles(bounds, tile_shortname='esa_world_cover_2021')

# X is an c x m x n numpy array, where c is the number of channels specified by rasterio `count` metadata
# p is a dictionary (or a rasterio profile) including relevant GIS metadata; CRS is assumed to be epsg:4326

The rasters are returned in the global lat/lon projection epsg:4326 and the API assumes that bounds are supplied in this format.

import rasterio

with rasterio.open('esa_world_cover_2021_subset.tif', 'w', **p) as ds:
   ds.write(X)

Installation

In order to easily manage dependencies, we recommend using dedicated project environments via Anaconda/Miniconda or Python virtual environments.

You can install the package with conda/mamba using:

mamba install tile_mate

or

pip install tile-mate

Alternatively, you can clone the repository and manage the environment using the environment.yml file provided.

  1. mamba env update -f environment.yml
  2. Activate the environment conda activate tile-mate
  3. Install the library with pip via pip install tile-mate.

For development, use pip with -e (editable) mode:

python -m pip install -e .

Python 3.9+ is supported.

Notebooks

We have notebooks to demonstrate common usage:

Datasets Supported

There are numerous tile sets. There are keyword arguments for many of the tiles. For example, for hansen_annual_mosaic the years 2013-2022 can be specified. The easiest way to see what is possible is to look at the Basic Demo. The datasets supported are:

In [1]: from tile_mate.stitcher import DATASET_SHORTNAMES

In [2]: DATASET_SHORTNAMES
Out[2]: 'pekel_water_occ_2021',
 'esa_world_cover_2020',
 'esa_world_cover_2021',
 'hansen_annual_mosaic',
 'hansen_lossyear',
 'hansen_gain',
 'hansen_treecover_2000',
 's1_coherence_2020',
 'radd_deforestation_alerts_2022',
 'hand',
 'glad_landcover',
 'glad_change'

More information about these datasets can be found below

See these notebooks to see how these tiles are generated and organized. Feel free to open a issue ticket or PR if there are modifications or new tilesets you would like to see.

Dateline/antimeridian support

We support a single dateline crossing (crossing +/- 180 longitude) within get_raster_from_tiles using in-memory translation of tiles (same as dem-stitcher's functionality). We "wrap" tiles across this dateline crossing. We assume that the supplied bounds/extent overlap the standard lat/lon CRS grid i.e. longitudes between -/+ 180 longitude and are within -/+ 90 latitude, where a buffer around the dateline (longitude axis or $x$-axis). Wrapping tiles around the North and South poles (i.e. at -/+ 90 latitude) is not supported (a different CRS is what's required) and an exception will be raised.

Contributing

We welcome contributions to this open-source package. To do so:

  1. Create an GitHub issue ticket desrcribing what changes you need (e.g. issue-1)
  2. Fork this repo
  3. Make your modifications in your own fork
  4. Make a pull-request (PR) in this repo with the code in your fork and tag the repo owner or a relevant contributor.

We use ruff and associated linting packages to ensure some basic code quality (see the environment.yml). These will be checked for each commit in a PR. Try to write tests wherever possible.

Support

  1. Create an GitHub issue ticket desrcribing what changes you would like to see or to report a bug.
  2. We will work on solving this issue (hopefully with you).

Acknowledgements

This tool was developed to support OPERA.

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Stitch global tiles into a continuous raster

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