PyLandStats

Overview

Open-source Pythonic library to compute landscape metrics within the PyData stack (NumPy, pandas, matplotlib...)

Features

Read GeoTiff files of land use/cover

import pylandstats as pls

ls = pls.read_geotiff('data/vaud_g100_clc00_V18_5.tif')

ls.plot_landscape(legend=True)

landscape-vaud

Compute pandas DataFrames of landscape metrics at the patch, class and landscape level

patch_metrics_df = ls.compute_patch_metrics_df()
patch_metrics_df.head()

patch_id	class_val	area	perimeter	perimeter_area_ratio	shape_index	fractal_dimension	euclidean_nearest_neighbor
0	1	115	10600	92.17	2.409	1.130	1431.782
1	1	13	2600	200.00	1.625	1.100	223.607
2	1	2	600	300.00	1.000	1.012	223.607
3	1	69	6000	86.96	1.765	1.088	316.228
4	1	76	8800	115.79	2.444	1.137	316.228

class_metrics_df = ls.compute_class_metrics_df(metrics=['proportion_of_landscape', 'edge_density'])
class_metrics_df

class_val	proportion_of_landscape	edge_density
1	7.702	4.459
2	92.298	4.459

Also analyze the spatio-temporal evolution of the landscape:

input_fnames = [
    'data/vaud_g100_clc00_V18_5.tif',
    'data/vaud_g100_clc06_V18_5a.tif',
    'data/vaud_g100_clc12_V18_5a.tif'
]

sta = pls.SpatioTemporalAnalysis(
    input_fnames, metrics=[
        'proportion_of_landscape',
        'edge_density',
        'fractal_dimension_am',
        'landscape_shape_index',
        'shannon_diversity_index'
    ], classes=[1], dates=[2000, 2006, 2012], 
)

fig, axes = sta.plot_metrics(
    class_val=1,
    metrics=['proportion_of_landscape', 'edge_density', 'fractal_dimension_am'],
    num_cols=3)
fig.suptitle('Class-level metrics (urban)')

spatiotemporal-analysis

See the pylandstats-notebooks repository for a more complete overview

Installation

To install use pip:

$ pip install pylandstats

If you want to use the BufferAnalysis, you will need geopandas. The easiest to install it is via conda-forge as in:

$ conda install -c conda-forge geopandas

and then install PyLandStats with the geo extras as in:

$ pip install pylandstats[geo]

Release files for pylandstats 0.4.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pylandstats 0.4.1
File	Size	Uploaded
pylandstats-0.4.1.tar.gz	22.2 kB	Apr 3, 2019	Details

Release files / pylandstats-0.4.1.tar.gz

Download URL	pylandstats-0.4.1.tar.gz
Size	22.2 kB
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Upload date	Apr 3, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.7`