tile-mate 0.0.11

Create rasters from global tiles

tile-mate

This tool provides a tool to create continuous rasters of global publicly available tiles 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 `count`
# p is a dictionary (or a rasterio profile) including relevant GIS metadata; CRS is 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:

• Basic Demo

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',
 'cop_100_lulc_discrete',
 'radd_deforestation_alerts_2022',
 'hand',
 'glad_landcover',
 'glad_change'

More information about these datasets can be found below

• Pekel water occurence: https://global-surface-water.appspot.com/download
• ESA World Cover (10 m) for 2020 and 2021: https://aws.amazon.com/marketplace/pp/prodview-7oorylcamixxc
• Hansen annual mosaic, treecover 2000, gain, and loss year: https://data.globalforestwatch.org/documents/941f17325a494ed78c4817f9bb20f33a/explore
• S1 Coherence from December 2019 - Nov 2020: https://aws.amazon.com/marketplace/pp/prodview-iz6lnjbdlgcwa#resources
  • Include all temporal baselines and seasons for VV coherence
  • Include rho, tau and rmse seasonal decay modeling parameters
• The copernicus 100 m LULC dataset from 2015 - 2019: https://land.copernicus.eu/global/content/annual-100m-global-land-cover-maps-available
• Height above nearest drainage (distributed and generated by ASF) in 2021 derived from Copernicus Global DEM: https://github.com/asjohnston-asf/agu-2022-notebooks/blob/main/hand-notebook.ipynb (and their tool to do the exact same thing)
• RADD Deforestation alerts (ongoing): https://data.globalforestwatch.org/datasets/gfw::deforestation-alerts-radd/about
• Glad landcover maps (2000, 2005, 2010, 2015, 2020) and change map (2020 changes when compared to 2000): https://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html

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 support

None curently.

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 flake8 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.