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@@ -28,4 +28,4 @@ Before you submit a pull request, check that it meets these guidelines:
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1. The pull request should include tests.
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1. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.md.
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1. The pull request should work for Python 3.8, 3.9, 3.10 and 3.11. Check https://github.com/martibosch/multilandpy/actions and make sure that the tests pass for all supported Python versions.
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1. The pull request should work for Python 3.8, 3.9, 3.10 and 3.11. Check https://github.com/martibosch/focalpy/actions and make sure that the tests pass for all supported Python versions.
Computing multi-scale landscape features for vector and raster layers (terrain/topographic indices, vegetation, building areas and volumes...) in Python.
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> *multilandpy* is an analogy to the [multilandr](https://github.com/phuais/multilandR) package [1] to compute multi-scale landscape metrics in R. However, instead of lansdcape metrics<sup>[1](#pylandstats)</sup>, multilandpy computes generic mutli-scale landscape features for vector and raster layers, such as topographic features, tree canopy cover as well as building areas and volumes.
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Toolkit for focal site multi-scale studies in Python
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Example application to compute the proportion of tree canopy around (with multiple buffer radii) weather stations in Zurich, Switzerland:
See the [overview notebook](https://multilandpy.readthedocs.io/en/latest/overview.html) and the [API documentation](https://multilandpy.readthedocs.io/en/latest/api.html) for more details on the features of multilandpy.
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See the [overview notebook](https://focalpy.readthedocs.io/en/latest/overview.html) and the [API documentation](https://focalpy.readthedocs.io/en/latest/api.html) for more details on the features of focalpy.
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## Installation
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Like many other geospatial Python packages, multilandpy requires many base C libraries that cannot be installed with pip. Accordingly, the best way to install multilandpy is to use conda/mamba, i.e., in a given conda environment, run:
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Like many other geospatial Python packages, focalpy requires many base C libraries that cannot be installed with pip. Accordingly, the best way to install focalpy is to use conda/mamba, i.e., in a given conda environment, run:
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```bash
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# or mamba install -c conda-forge geopandas
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conda install -c conda-forge geopandas
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```
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Within the same conda environment, you can then install multilandpy using pip:
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Within the same conda environment, you can then install focalpy using pip:
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