equi7grid-lite 0.1.0

A user-friendly Python interface to interact with the Equi7Grid grid system

equi7grid-lite

No one will drive us from the paradise which EquiGrid created for us

The equi7grid-lite package implements a user-friendly Python interface to interact with the Equi7Grid grid system.

equi7grid-lite is an unofficial Python implementation of Equi7Grid. With this package, users can convert geographic coordinates to Equi7Grid tiles and vice versa. This implementation differs from the official version in tree key ways:

• Quad-Tree Grid Splitting: Users are required to split the grid in a Quad-Tree fashion, meaning each grid level is divided into four tiles. For example, transitioning from level 1 to level 0 involves splitting each tile into four regular smaller tiles.

• Revised Grid ID Encoding: The grid ID is always encoded in meters, and the reference to the tile system (e.g., "T1", "T3", "T6") is removed. Instead, tiles are dynamically defined by the min_grid_size parameter. Here is a comparison between the original Equi7Grid and equi7grid-lite:

  • 'EU500M_E036N006T6' -> 'EU2560_E4521N3011'

  Where 'EU' and 'AF' are the zones, '2560' is the min_grid_size, 'E4521' is the position in the x tile axis, and 'N3011' is the position in the y tile axis.

• Upper Bound Level: The maximum grid level is determined as the nearest lower distance to 2_500_000 meters. This threshold serves as a limit to create the Quad-Tree grid structure.

Please refer to the Equi7Grid repository for more information of the official implementation.

Installation

The equi7grid-lite package is available on PyPI and can be installed using pip:

pip install equi7grid-lite

Usage

The equi7grid-lite package provides a single class, Equi7Grid, which can be used to convert between geographic coordinates and Equi7Grid tiles.

from equi7grid_lite import Equi7Grid

grid_system = Equi7Grid(min_grid_size=2560)
grid_system

# Convert geographic coordinates to Equi7Grid tile
lon, lat = -79.5, -5.49
results = grid_system.lonlat2grid(lon=lon, lat=lat, level=7)

# Convert Equi7Grid tile to geographic coordinates
grid_system.grid2lonlat(grid_id=results)
# ?, ?

The Equi7Grid class also provides a method for creating a grid of Equi7Grid tiles that cover a given bounding box.

import geopandas as gpd

from equi7grid_lite import Equi7Grid

# Define a POLYGON geometry
world_filepath = gpd.datasets.get_path('naturalearth_lowres')
world = gpd.read_file(world_filepath)
country = world[world.name == "Peru"].geometry[0]

# Create a grid of Equi7Grid tiles
grid_system = equi7grid_lite.Equi7GridLite(t1_tile_size=2560)
grid_system

# Create a grid of Equi7Grid tiles that cover the bounding box of the POLYGON geometry
grid = grid_system.create_grid(
    level=8,
    zone="SA",
    mask=polygon, # Only include tiles that intersect the polygon
    landcover=True # Only include tiles with landmasses    
)

# Export the grid to a GeoDataFrame
grid.to_file("grid.shp")

By running create_grid with different levels, you can obtain for any region its corresponding Equi7Grid Quad-Tree grid structure.

Obtain the metadata of each Equi7Grid zone:

from equi7grid_lite import Equi7Grid

# Zones: SA, EU, AF, AS, NA, AU
Equi7Grid.SA

Each zone has the following attributes:

• id: The zone ID code.
• crs: The WKT representation of the CRS.
• geometry_geo: The geometry of the zone in EPSG:4326.
• geometry_equi7grid: The geometry of the zone in the Equi7Grid CRS.
• bbox_geo: The bounding box of the zone in EPSG:4326.
• bbox_equi7grid: The bounding box of the zone in the Equi7Grid CRS.
• landmasses_equi7grid: The landmasses of the zone in the Equi7Grid CRS.

License

This package is released under the MIT License. For more information, see the LICENSE file.

Contributing

Contributions are welcome! For bug reports or feature requests, please open an issue on GitHub. For contributions, please submit a pull request with a detailed description of the changes.

Citation

This is a simple adaptation of the Equi7Grid paper and code. If you use this package in your research, please consider citing the original Equi7Grid package and paper.

Package:

@software{bernhard_bm_2023_8252376,
  author       = {Bernhard BM and
                  Sebastian Hahn and
                  actions-user and
                  cnavacch and
                  Manuel Schmitzer and
                  shochsto and
                  Senmao Cao},
  title        = {TUW-GEO/Equi7Grid: v0.2.4},
  month        = aug,
  year         = 2023,
  publisher    = {Zenodo},
  version      = {v0.2.4},
  doi          = {10.5281/zenodo.8252376},
  url          = {https://doi.org/10.5281/zenodo.8252376}
}

Paper:

@article{BAUERMARSCHALLINGER201484,
title = {Optimisation of global grids for high-resolution remote sensing data},
journal = {Computers & Geosciences},
volume = {72},
pages = {84-93},
year = {2014},
issn = {0098-3004},
doi = {https://doi.org/10.1016/j.cageo.2014.07.005},
url = {https://www.sciencedirect.com/science/article/pii/S0098300414001629},
author = {Bernhard Bauer-Marschallinger and Daniel Sabel and Wolfgang Wagner},
keywords = {Remote sensing, High resolution, Big data, Global grid, Projection, Sampling, Equi7 Grid}
}