Skip to main content

A Rasterio plugin command that exports MBTiles

Project description

https://travis-ci.org/mapbox/rio-mbtiles.svg

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rio-mbtiles-1.5b2.tar.gz (11.1 kB view details)

Uploaded Source

Built Distributions

rio_mbtiles-1.5b2-py3-none-any.whl (13.4 kB view details)

Uploaded Python 3

rio_mbtiles-1.5b2-py2-none-any.whl (13.4 kB view details)

Uploaded Python 2

File details

Details for the file rio-mbtiles-1.5b2.tar.gz.

File metadata

  • Download URL: rio-mbtiles-1.5b2.tar.gz
  • Upload date:
  • Size: 11.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/2.7.15

File hashes

Hashes for rio-mbtiles-1.5b2.tar.gz
Algorithm Hash digest
SHA256 389bfc4815aa50327ed10266a47497e1326342a8f190fa1031d946490eab1bf6
MD5 2b402b54419f20475c66c34d225fef0f
BLAKE2b-256 4f50a96c2d72db391c5f83ab2db33b18fcf4e789dd43d881aa9671b48af2a1de

See more details on using hashes here.

File details

Details for the file rio_mbtiles-1.5b2-py3-none-any.whl.

File metadata

  • Download URL: rio_mbtiles-1.5b2-py3-none-any.whl
  • Upload date:
  • Size: 13.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.7

File hashes

Hashes for rio_mbtiles-1.5b2-py3-none-any.whl
Algorithm Hash digest
SHA256 e86ad3bb8e8549c5ff09c4a7385bccea43679e1d97c5912b625955a4b5cef45d
MD5 137b844be405762fb0c5dcb059d88e29
BLAKE2b-256 faeb82261779d58ceac18d8936e3fa9c02ecf72717bfeb49bc614f44ae5297ae

See more details on using hashes here.

File details

Details for the file rio_mbtiles-1.5b2-py2-none-any.whl.

File metadata

  • Download URL: rio_mbtiles-1.5b2-py2-none-any.whl
  • Upload date:
  • Size: 13.4 kB
  • Tags: Python 2
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/2.7.15

File hashes

Hashes for rio_mbtiles-1.5b2-py2-none-any.whl
Algorithm Hash digest
SHA256 12ce4b33a7768915c41e77a33b5ba93a03eae6e0617a07b7b639a965a91132ad
MD5 2a79a92b8262fba28c286304dbc03191
BLAKE2b-256 c4d0cba0d3b3ed72103b48926ed0e27a143c21c7fff06dfd2b7601c480eaeb4b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page