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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)
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.
mamba env update -f environment.ymlconda activate tile-matepip via pip install tile-mate.For development, use pip with -e (editable) mode:
python -m pip install -e .
Python 3.9+ is supported.
We have notebooks to demonstrate common usage:
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
rho, tau and rmse seasonal decay modeling parametersSee 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.
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.
We welcome contributions to this open-source package. To do so:
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.
This tool was developed to support OPERA.
FAQs
Create rasters from global tiles
We found that tile-mate demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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