Skip to main content

A set of utilities for manipulating (Geo)JSON and GeoTIFF data.

Project description

https://raw.githubusercontent.com/cheginit/hydrodata/develop/docs/_static/pygeoutils_logo.png

PyPi Conda Version CodeCov Github Actions Binder

CodeFactor black pre-commit

Features

PyGeoUtils is a part of Hydrodata software stack and provides utilities for manipulating (Geo)JSON and GeoTIFF data:

  • json2geodf: For converting (Geo)JSON objects to GroPandas dataframe.

  • arcgis2geojson: For converting ESRIGeoJSON objects to standard GeoJSON format.

  • gtiff2xarray: For converting (Geo)TIFF objects to xarray datasets.

All these function handle all necessary CRS transformations. Moreover, requests for additional functionalities can be submitted via issue tracker.

Installation

You can install pygeoutils using pip after installing libgdal on your system (for example, in Ubuntu run sudo apt install libgdal-dev):

$ pip install pygeoutils

Alternatively, pygeoutils can be installed from the conda-forge repository using Conda:

$ conda install -c conda-forge pygeoutils

Quickstart

To demonstrate capabilities of PyGeoUtils lets use PyGeoOGC to access National Wetlands Inventory from WMS, and FEMA National Flood Hazard via WFS, then convert the outpus to GeoDataFrame and xarray.Dataset using PyGeoUtils.

from pygeoogc import WFS, wms_bybox, MatchCRS
from shapely.geometry import Polygon
import pygeoutils as geoutils


geometry =  Polygon(
    [
        [-118.72, 34.118],
        [-118.31, 34.118],
        [-118.31, 34.518],
        [-118.72, 34.518],
        [-118.72, 34.118],
    ]
)

url_wms = "https://www.fws.gov/wetlands/arcgis/services/Wetlands_Raster/ImageServer/WMSServer"
layer = "0"
r_dict = wms_bybox(
    url_wms,
    layer,
    geometry.bounds,
    1e3,
    "image/tiff",
    box_crs="epsg:4326",
    crs="epsg:3857",
)

wetlands = geoutils.gtiff2xarray(r_dict, geometry, "epsg:4326")

url_wfs = "https://hazards.fema.gov/gis/nfhl/services/public/NFHL/MapServer/WFSServer"
wfs = WFS(
    url_wfs,
    layer="public_NFHL:Base_Flood_Elevations",
    outformat="esrigeojson",
    crs="epsg:4269",
)
bbox = geometry.bounds
bbox = (bbox[1], bbox[0], bbox[3], bbox[2])
r = wfs.getfeature_bybox(bbox, box_crs="epsg:4326")
flood = geoutils.json2geodf(r.json(), "epsg:4269", "epsg:4326")

Contributing

Contirbutions are very welcomed. Please read CODE_OF_CONDUCT.rst and CONTRIBUTING.rst files for instructions.

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

pygeoutils-0.1.2.tar.gz (19.3 kB view hashes)

Uploaded Source

Built Distribution

pygeoutils-0.1.2-py2.py3-none-any.whl (8.9 kB view hashes)

Uploaded Python 2 Python 3

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