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A Rasterio plugin command that exports MBTiles

Project description

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A plugin for the Rasterio CLI that exports a raster dataset to the MBTiles (version 1.1) format. Features include automatic reprojection and parallel processing.

Usage

$ rio mbtiles --help
Usage: rio mbtiles [OPTIONS] INPUT [OUTPUT]

  Export a dataset to MBTiles (version 1.1) in a SQLite file.

  The input dataset may have any coordinate reference system. It must have
  at least three bands, which will be become the red, blue, and green bands
  of the output image tiles.

  An optional fourth alpha band may be copied to the output tiles by using
  the --rgba option in combination with the PNG format. This option requires
  that the input dataset has at least 4 bands.

  If no zoom levels are specified, the defaults are the zoom levels nearest
  to the one at which one tile may contain the entire source dataset.

  If a title or description for the output file are not provided, they will
  be taken from the input dataset's filename.

  This command is suited for small to medium (~1 GB) sized sources.

  Python package: rio-mbtiles (https://github.com/mapbox/rio-mbtiles).

Options:
  -o, --output PATH               Path to output file (optional alternative to
                                  a positional arg).

  --append                        Append tiles to an existing file.
  --overwrite                     Always overwrite an existing output file.
  --title TEXT                    MBTiles dataset title.
  --description TEXT              MBTiles dataset description.
  --overlay                       Export as an overlay (the default).
  --baselayer                     Export as a base layer.
  -f, --format [JPEG|PNG]         Tile image format.
  --tile-size INTEGER             Width and height of individual square tiles
                                  to create.  [default: 256]

  --zoom-levels MIN..MAX          A min...max range of export zoom levels. The
                                  default zoom level is the one at which the
                                  dataset is contained within a single tile.

  --image-dump PATH               A directory into which image tiles will be
                                  optionally dumped.

  -j INTEGER                      Number of workers (default: number of
                                  computer's processors).

  --src-nodata FLOAT              Manually override source nodata
  --dst-nodata FLOAT              Manually override destination nodata
  --resampling [nearest|bilinear|cubic|cubic_spline|lanczos|average|mode|gauss|max|min|med|q1|q3]
                                  Resampling method to use.  [default:
                                  nearest]

  --version                       Show the version and exit.
  --rgba                          Select RGBA output. For PNG only.
  --implementation [cf|mp]        Concurrency implementation. Use
                                  concurrent.futures (cf) or multiprocessing
                                  (mp).

  -#, --progress-bar              Display progress bar.
  --cutline PATH                  Path to a GeoJSON FeatureCollection to be
                                  used as a cutline. Only source pixels within
                                  the cutline features will be exported.

  --oo NAME=VALUE                 Format driver-specific options to be used
                                  when accessing the input dataset. See the
                                  GDAL format driver documentation for more
                                  information.

  --wo NAME=VALUE                 See the GDAL warp options documentation for
                                  more information.

  --help                          Show this message and exit.

Performance

The rio-mbtiles command is suited for small to medium (~1 GB) raster sources. On a MacBook Air, the 1:10M scale Natural Earth raster (a 21,600 x 10,800 pixel, 700 MB TIFF) exports to MBTiles (levels 1 through 5) in 45 seconds.

$ time GDAL_CACHEMAX=256 rio mbtiles NE1_HR_LC.tif \
> -o ne.mbtiles --zoom-levels 1..5 -j 4

real    0m44.925s
user    1m20.152s
sys     0m22.428s

Installation

pip install rio-mbtiles

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