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This is a template repository for Python projects that use Poetry for their dependency management.

Project description

austriadownloader

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Getting started with your project

Clone this repository to start developing. All required datasets are available in austriadownloader/austria_data/ and can be created by executing austriadownloader/austria_data/metadata_creation.py.

To access and download Austrian Orthophoto and matching cadastral classes, execute the demo.py script. Provide POIs as a dataframe with the following scheme in the WGS84 format (EPSG:4326):

Column Type Description
id str Unique identifier for each location
lat float Latitude coordinate in decimal degrees
lon float Longitude coordinate in decimal degrees

Other input parameters are:

Column Type Description
pixel_size float Pixel resolution in meters. Must be a predefined value from (0.2, 0.4, 0.8, ... 204.8)
shape tuple[int, int, int] Image dimensions as (channels, height, width). Channels must be 3 (RGB) or 4 (RGBN).
outpath Path or str Directory path where output files will be saved.
mask_label list, tuple[int] or int Cadastral mask(s) to be extracted. Values are merged into a binary mask. Multi-class masks are not supported.
create_gpkg bool (default: False) Indicates whether vectorized but unclipped tiles should be saved as .GPKG.
nodata_mode str (default: 'flag') Mode for handling no-data values ('flag' or 'remove').
nodata_value int (default: 0) Value assigned to no-data pixels.

Results

General overview of different classes:

Sample Image

Unique selection of classes:

Sample Image

Available Classes

To select your class labels, select one or more from the following list:

Category Code Subcategory
Building areas 41 Buildings
83 Adjacent building areas
Water body 59 Flowing water
60 Standing water
61 Wetlands
64 Waterside areas
Agricultural 40 Permanent crops or gardens
48 Fields, meadows or pastures
57 Overgrown areas
Forest 55 Krummholz
56 Forests
58 Forest roads
Other 42 Car parks
62 Low vegetation areas
63 Operating area
65 Roadside areas
72 Cemetery
84 Mining areas, dumps and landfills
87 Rock and scree surfaces
88 Glaciers
92 Rail transport areas
95 Road traffic areas
96 Recreational area
Gardens 52 Gardens
Alps 54 Alps

Releasing a new version

  • Create an API Token on PyPI.
  • Add the API Token to your projects secrets with the name PYPI_TOKEN by visiting this page.
  • Create a new release on Github.
  • Create a new tag in the form *.*.*.
  • For more details, see here.

Repository initiated with fpgmaas/cookiecutter-poetry.

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