A part of HyRiver software stack for handling geospatial data manipulations

Overview
https://raw.githubusercontent.com/cheginit/HyRiver-examples/main/notebooks/_static/pygeoutils_logo.png

JOSS

Package Description Status
PyNHD Navigate and subset NHDPlus (MR and HR) using web services Github Actions
Py3DEP Access topographic data through National Map's 3DEP web service Github Actions
PyGeoHydro Access NWIS, NID, WQP, HCDN 2009, NLCD, and SSEBop databases Github Actions
PyDaymet Access Daymet for daily climate data both single pixel and gridded Github Actions
AsyncRetriever High-level API for asynchronous requests with persistent caching Github Actions
PyGeoOGC Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services Github Actions
PyGeoUtils Convert responses from PyGeoOGC's supported web services to datasets Github Actions

PyGeoUtils: Utilities for (Geo)JSON and (Geo)TIFF Conversion

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Features

PyGeoUtils is a part of HyRiver software stack that is designed to aid in watershed analysis through web services. This package provides utilities for manipulating (Geo)JSON and (Geo)TIFF responses from web services. These utilities are:

  • json2geodf: For converting (Geo)JSON objects to GeoPandas dataframe.
  • arcgis2geojson: For converting ESRIGeoJSON to the standard GeoJSON format.
  • gtiff2xarray: For converting (Geo)TIFF objects to xarray. datasets.
  • xarray2geodf: For converting xarray.DataArray to a geopandas.GeoDataFrame, i.e., vectorization.
  • xarray_geomask: For masking a xarray.Dataset or xarray.DataArray using a polygon.

All these functions handle all necessary CRS transformations.

You can find some example notebooks here.

Please note that since this project is in early development stages, while the provided functionalities should be stable, changes in APIs are possible in new releases. But we appreciate it if you give this project a try and provide feedback. Contributions are most welcome.

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). Moreover, PyGeoUtils has an optional dependency for using persistent caching, requests-cache. We highly recommend to install this package as it can significantly speedup send/receive queries. You don't have to change anything in your code, since PyGeoUtils under-the-hood looks for requests-cache and if available, it will automatically use persistent caching:

$ pip install pygeoutils

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

$ conda install -c conda-forge pygeoutils

Quick start

To demonstrate capabilities of PyGeoUtils let's use PyGeoOGC to access National Wetlands Inventory from WMS, and FEMA National Flood Hazard via WFS, then convert the output to xarray.Dataset and GeoDataFrame, respectively.

import pygeoutils as geoutils
from pygeoogc import WFS, WMS, ServiceURL
from shapely.geometry import Polygon


geometry = Polygon(
    [
        [-118.72, 34.118],
        [-118.31, 34.118],
        [-118.31, 34.518],
        [-118.72, 34.518],
        [-118.72, 34.118],
    ]
)
crs = "epsg:4326"

wms = WMS(
    ServiceURL().wms.mrlc,
    layers="NLCD_2011_Tree_Canopy_L48",
    outformat="image/geotiff",
    crs=crs,
)
r_dict = wms.getmap_bybox(
    geometry.bounds,
    1e3,
    box_crs=crs,
)
canopy = geoutils.gtiff2xarray(r_dict, geometry, crs)

mask = canopy > 60
canopy_gdf = geoutils.xarray2geodf(canopy, "float32", mask)

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",
)
r = wfs.getfeature_bybox(geometry.bounds, box_crs=crs)
flood = geoutils.json2geodf(r.json(), "epsg:4269", crs)

Contributing

Contributions are very welcomed. Please read CONTRIBUTING.rst file for instructions.

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Releases(v0.13.10)
  • v0.13.10(Dec 9, 2022)

    Release Notes

    New Features

    • Add a new function called nested_polygons for determining nested (multi)polygons in a gepandas.GeoDataFrame or geopandas.GeoSeries.
    • Add a new function called geodf2xarray for rasterizing a geopandas.GeoDataFrame to a xarray.DataArray.

    Internal Changes

    • Modify the codebase based on Refurb suggestions.
    • In xarray_geomask, if drop=True recalculate its transform to ensure the correct geo references are set if the shape of the dataset changes.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.9(Nov 5, 2022)

    Release Notes

    Internal Changes

    • Improve the performance of xarray_geomask significantly by first clipping the data to the geometry's bounding box, then if the geometry is a polygon, masking the data with the polygon. This is much faster than directly masking the data with the polygon. Also, support passing a bounding box to xarray_geomask in addition to polygon and multipolygon.
    • Fix deprecation warning of pandas when changing the geometry column of a GeoDataFrame in then break_lines function.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.8(Nov 5, 2022)

    Release Notes

    Internal Changes

    • When combining the responses, now dask handles data chunking more efficiently. This is especially important for handling large responses from WMS services.
    • Improve type hints for CRS-related arguments of all functions by including string, integer, and pyproj.CRS types.
    • In gtiff2xarray use rasterio engine to make sure all rioxarray attrs are read.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.7(Nov 4, 2022)

    Release Notes

    Internal Changes

    • When combining the responses, now dask handles data chunking more efficiently. This is especially important for handling large responses from WMS services.
    • Improve type hints for CRS-related arguments of all functions by including string, integer, and pyproj.CRS types.
    • In gtiff2xarray use rasterio engine to make sure all rioxarray attrs are read.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.6(Aug 30, 2022)

  • v0.13.5(Aug 29, 2022)

  • v0.13.2(Jun 14, 2022)

    Release Notes

    Breaking Changes

    • Set the minimum supported version of Python to 3.8 since many of the dependencies such as xarray, pandas, rioxarray have dropped support for Python 3.7.
    • Bump min versions of rioxarray to 0.10 since it adds reading/writing GCPs.

    Internal Changes

    • Use micromamba for running tests and use nox for linting in CI.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.1(Jun 12, 2022)

    Release Notes

    New Features

    • Add support for passing a custom bounding box in the Coordinates class. The default is the bounds of EPSG:4326 to retain backward compatibility. This new class parameter allows a user to check if a list of coordinates is within a custom bounding box. The bounds should be the EPSG:4326 coordinate system.
    • Add a new function called geometry_list for converting a list of multi-geometries to a list of geometries.
    Source code(tar.gz)
    Source code(zip)
  • v0.13.0(Apr 3, 2022)

    Release Notes

    Internal Changes

    • Write nodata attribute using rioxarray in geotiff2xarray since the clipping operation of rioxarray uses this value as fill value.

    Bug Fixes

    • In the break_lines function, convert MultiLineString into LineString since shapely.ops.substring only accepts LineString.
    Source code(tar.gz)
    Source code(zip)
  • v0.12.3(Feb 4, 2022)

    Release Notes

    New Features

    • Add a function called break_lines for breaking lines at given points.
    • Add a function called snap2nearest for snapping points to the nearest point on a line with a given tolerance. It accepts a geopandas.GeoSeries of points and a geopandas.GeoSeries or geopandas.GeoDataFrame of lines. It automatically snaps to the closest lines in the input data.
    Source code(tar.gz)
    Source code(zip)
  • v0.12.2(Jan 15, 2022)

    Release Notes

    New Features

    • Add a new class called GeoBSpline that generates B-splines from a set of coordinates. The spline attribute of this class has five attributes: x and y coordinates, phi and radius which are curvature and radius of curvature, respectively, and distance which is the total distance of each point along the B-spline from the starting points.
    • Add a new class called Coordinates that validates a set of lon/lat coordinates. It normalizes longitudes to the range [-180, 180) and has a points property that is geopandas.GeoSeries with validated coordinates. It uses spatial indexing to speed up the validation and should be able to handle large datasets efficiently.
    • Make transform2tuple a public function.

    Internal Changes

    • The geometry and geo_crs arguments of gtiff2xarray are now optional. This is useful for cases when the input GeoTiff response is the results of a bounding box query and there is no need for a geometry mask.
    • Replace the missing values after adding geometry mask via xarray_geomask by the nodatavals attribute of the input xarray.DataArray or xarray.Dataset. Therefore, the data type of the input xarray.DataArray or xarray.Dataset is conserved.
    • Expose connectivity argument of rasterio.features.shapes function in xarray2geodf function.
    • Move all private functions to a new module to make the main module less cluttered.
    Source code(tar.gz)
    Source code(zip)
  • v0.12.1(Dec 31, 2021)

    Release Notes

    Internal Changes

    • Refactor arcgis2geojson for better readability and maintainability.
    • In arcgis2geojson set the geometry to null if its type is not supported, such as curved polylines.
    Source code(tar.gz)
    Source code(zip)
  • v0.12.0(Dec 27, 2021)

    Release Notes

    Internal Changes

    • Add all the missing types so mypy --strict passes.
    • Bump version to 0.12.0 to match the release of pygeoogc.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.7(Nov 10, 2021)

    Release Notes

    Internal Changes

    • Use rioxarray for dealing with GeoTIFF binaries since xarray deprecated the xarray.open_rasterio function, as it's discussed in this PR.
    • Use importlib-metadata for getting the version insead of pkg_resources to decrease import time as discussed in this issue.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.6(Oct 6, 2021)

  • v0.11.5(Sep 17, 2021)

    Release Notes

    Bug Fixes

    • Fix an issue with gtiff2xarray where the scales and offsets attributes of the output DataArray were floats rather than tuples (:issue_3dep:[30]{.title-ref}).

    Internal Changes

    • Add a new function, transform2tuple, for converting Affine transforms to a tuple. Previously, the Affine transform was converted to a tuple using to_gdal() method of rasterio.Affine which was not compatible with rioxarray.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.4(Aug 27, 2021)

    Release Notes

    Internal Changes

    • Use ujson for JSON parsing instead of orjson since orjson only serializes to bytes which is not compatible with aiohttp.
    • Convert the transform attribute data type from Affine to tuple since saving an data array to netcdf cannot handle the Affine type.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.3(Aug 19, 2021)

    Release Notes

    • Fix an issue in geotiff2xarray related to saving an xarray object to netcdf when its transform attribute has Affine type rather than a tuple.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.2(Jul 31, 2021)

    Release Notes

    The highlight of this release is performance improvement in gtiff2xarray for handling large responses.

    New Features

    • Automatic detection of the driver by default in gtiff2xarray as opposed to it being GTiff.

    Internal Changes

    • Make geo2polygon, get_transform, and get_nodata_crs public functions since other packages use it.
    • Make xarray_mask a public function and simplify gtiff2xarray.
    • Remove MatchCRS since it's already available in pygeoogc.
    • Validate input geometry in geo2polygon.
    • Refactor gtiff2xarray to check for the ds_dims outside the main loops to improve the performance. Also, the function tries to detect the dimension names automatically if ds_dims is not provided by the user, explicitly.
    • Improve performance of json2geodf by using list comprehension and performing checks outside the main loop.

    Bug Fixes

    • Add the missing arguments for masking the data in gtiff2xarray.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.1(Jun 19, 2021)

    Release Notes

    Bug Fixes

    • In some edge cases the y-coordinates of a response might not be monotonically sorted so dask fails. This release sorts them to address this issue.
    Source code(tar.gz)
    Source code(zip)
  • v0.11.0(Jun 19, 2021)

    Release Notes

    New Features

    • Function gtiff2xarray returns a parallelized xarray.Dataset or xarray.DataAraay that can handle large responses much more efficiently. This is achieved using dask.

    Breaking Changes

    • Drop support for Python 3.6 since many of the dependencies such as xarray and pandas have done so.
    • Refactor MatchCRS. Now, it should be instantiated by providing the in and out CRSs like so: MatchCRS(in_crs, out_crs). Then its methods, namely, geometry, bounds and coords, can be called. These methods now have only one input, geometry.
    • Change input and output types of MatchCRS.coords from tuple of lists of coordinates to list of (x, y) coordinates.
    • Remove xarray_mask and gtiff2file since rioxarray is more general and suitable.

    Internal Changes

    • Remove unnecessary type checks for private functions.
    • Refactor json2geodf to improve robustness. Use get method of dict for checking key availability.
    Source code(tar.gz)
    Source code(zip)
  • v0.10.1(Mar 27, 2021)

    Release Notes

    • Setting transform of the merged dataset explicitly to address cheginit/py3dep#3
    • Add annoucement regarding the new name for the softwate stack, HyRiver.
    • Improve pip installation and release workflow.
    Source code(tar.gz)
    Source code(zip)
  • v0.10.0(Mar 6, 2021)

  • v0.9.0(Feb 17, 2021)

  • v0.2.0(Dec 7, 2020)

  • v0.1.10(Aug 18, 2020)

    • Fixed the gtiff2xarray issue with high-resolution requests and improved the robustness of the function.
    • Replaces simplejson with orjson to speed up JSON operations.
    Source code(tar.gz)
    Source code(zip)
  • v0.1.9(Aug 12, 2020)

  • v0.1.8(Aug 4, 2020)

    • Retained the compatibility with xarray 0.15 by removing the attrs flag.
    • Added xarray_geomask function and made it a public function.
    • More efficient handling of large geotiff responses by cropping the response before converting it into a dataset.
    • Added a new function called geo2polygon for converting and transforming a polygon or bounding box into a Shapley's Polygon in the target CRS.
    • This release will be a part of Hydrodata 0.7.0.
    Source code(tar.gz)
    Source code(zip)
  • v0.1.7(Jul 27, 2020)

  • v0.1.6(Jul 24, 2020)

Owner
Taher Chegini
A hydrologist and Python developer with a knack for data analysis and visualization, working with web services, and contemplating the theory of everything
Taher Chegini
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