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Python tools for working with the Danish Kvadratnet tiling scheme.

Project description

Kvadratnet is a set of tools that makes working with the Danish Kvadratnet easier.

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The Danish Kvadratnet is a geographical tiling scheme based on UTM coordinates. The tiling scheme is a national standard for dividing nation-wide geographical datasets into smaller pieces.

The Danish Kvadratnet was originally created as a collaboration between Statistics Denmark and the National Survey and Cadastre of Denmark as a static administrative geographical subdivision of the country. The reasoning behind this was that usual administrative boundaries, such as municipal boundaries, are known to change from time to time and are therefore not very suitable as a geographical administrative index.

The Danish Kvadratnet consist of a several networks that covers the country with square tiles of varying sizes. Supported tile sizes are: 100m, 250m, 1km, 10km, 50km and 100km. Individual tiles are identified by tile size and the coordinates of the lower left corner of a tile. The coordinates are truncated accordinging to the size of the tile i.e. 1km_6452_523. Examples of tile identifiers can be seen in the table below:

Network Tile name example
100km 100km_62_5
50km 50km_620_55
10km 10km_622_57
1km 1km_6223_576
250m 250m_622375_57550
100m 100m_62237_5756

Use of the kvadratnet module is not limited to the geographical area of Denmark. The tiling scheme can be applied to any region on earth as the UTM coordinate system is defined worlwide. Care has to be taken in case use of the tiling scheme spans more than one UTM zone, since coordinates are duplicated across zones. This can be solved by keeping all data in the same UTM zone, even though some of it might be placed outside the zone. By using robust UTM coordinate transformation libraries, such as the Extended Transverse Mercator implementation in proj.4, data can be kept in the same coordinate system even though it spans several UTM zones. This exact procedure is used by the Grenland Survey, Asiaq, which organizes data across 10 UTM zones.


Example of using kvadratnet

Suppose you have a range of files organized in the 1km network. We want to count how many 1km tiles are present in each parent 10km tile.

from collections import Counter
import kvadratnet

files = ['dtm_1km_6121_867.tif', 'dtm_1km_6125_866.tif',
         'dtm_1km_6125_862.tif', 'dtm_1km_6423_512.tif',
         'dtm_1km_6253_234.tif', 'dtm_1km_6235_634.tif',
         'dtm_1km_6424_513.tif', 'dtm_lkm_5223_523.tif',
         'dtm_1km_6251_236.tif', 'dtm_1km_6424_517.tif']

counter = Counter()

for filename in files:
        name = kvadratnet.tile_name(filename)
        counter['bad_name'] += 1
    parent = kvadratnet.parent_tile(name, '10km')
    counter[parent] += 1

# Counter({'10km_642_51': 4, '10km_612_86': 3, '10km_625_23': 2, '10km_623_63': 1, 'bad_name': 1})

knet - command line interface

kvadratnet also has a command line interface called knet. The knet command is a front for various tools that make life managing files with kvadratnet naming a lot easier. For instance renaming many files:

# add a prefix before the cell identifier
$ knet rename --prefix PUNKTSKY_ "*.laz"

# strip anything but the cell identifier
$ knet rename PUNKTSKY*.laz

With knet organizing files in subfolders according to which parent tiles they belong to is easy:

# divide files into 100km and 10km folders
$ knet organize "1km*.tif" 100km 10km


Installation can be done either via

pip install kvadratnet

or by downloading the source code and running

python install


nose is used for testing. The test-suite can be invoked by running

nosetests -v

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