Metadata-Version: 2.1
Name: py3dep
Version: 0.1.5
Summary: Access USGS 3DEP database and get data such as elevation in the US
Home-page: https://github.com/cheginit/py3dep
Author: Taher Chegini
Author-email: cheginit@gmail.com
License: MIT license
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        🚨 **This package is under heavy development and breaking changes are likely to happen.** 🚨
        
        Features
        --------
        
        Hydrodata is a stack of Python libraries designed to aid in watershed analysis through
        web services. Currently, it only includes hydrology and climatology data within the US.
        Hydrodata software stack is shown in the table below.
        
        =========== ===========================================================================
        Package     Description
        =========== ===========================================================================
        Hydrodata_  Access NWIS, HCDN 2009, NLCD, and SSEBop databases
        PyGeoOGC_   Query data from any ArcGIS RESTful-, WMS-, and WFS-based services
        PyGeoUtils_ Convert responses from PyGeoOGC's supported web services to datasets
        PyNHD_      Access NLDI and WaterData web services for navigating the NHDPlus database
        Py3DEP_     Access topographic data through the 3D Elevation Program (3DEP) web service
        PyDaymet_   Access the Daymet database for daily climate data
        =========== ===========================================================================
        
        .. _Hydrodata: https://github.com/cheginit/hydrodata
        .. _PyGeoOGC: https://github.com/cheginit/pygeoogc
        .. _PyGeoUtils: https://github.com/cheginit/pygeoutils
        .. _PyNHD: https://github.com/cheginit/pynhd
        .. _Py3DEP: https://github.com/cheginit/py3dep
        .. _PyDaymet: https://github.com/cheginit/pydaymet
        
        Py3DEP provides access to the `3DEP <https://www.usgs.gov/core-science-systems/ngp/3dep>`__
        database which is a part the `National Map services <https://viewer.nationalmap.gov/services/>`__.
        The 3DEP service has multi-resolution sources and depending on the user provided resolution,
        the data is resampled on the server-side based on all the available data sources. Py3DEP returns
        the requestes as `xarray <https://xarray.pydata.org/en/stable>`__ dataset. The 3DEP includes
        the following layers:
        
        - DEM
        - Hillshade Gray
        - Aspect Degrees
        - Aspect Map
        - GreyHillshade Elevation Fill
        - Hillshade Multidirectional
        - Slope Map
        - Slope Degrees
        - Hillshade Elevation Tinted
        - Height Ellipsoidal
        - Contour 25
        - Contour Smoothed 25
        
        Moreover, Py3DEP offers some additonal utilities:
        
        - ``elevation_bygrid``: For getting elevations of all the grid points in a 2D grid.
        - ``elevation_byloc``: For getting elevation of a single point which is based on the National
          Map's `Elevation Point Query Service <https://nationalmap.gov/epqs/>`__.
        - ``deg2mpm``: For converting slope dataset from degree to meter per meter.
        
        You can try using Py3DEP without installing it on you system by clicking on the binder badge
        below the Py3DEP banner. A Jupyter notebook instance with the Hydrodata software stack
        pre-installed will be launched in your web browser and you can start coding!
        
        Moreover, requests for additional functionalities can be submitted via
        `issue tracker <https://github.com/cheginit/py3dep/issues>`__.
        
        
        Installation
        ------------
        
        You can install Py3DEP using ``pip`` after installing ``libgdal`` on your system
        (for example, in Ubuntu run ``sudo apt install libgdal-dev``):
        
        .. code-block:: console
        
            $ pip install py3dep
        
        Alternatively, Py3DEP can be installed from the ``conda-forge`` repository
        using `Conda <https://docs.conda.io/en/latest/>`__:
        
        .. code-block:: console
        
            $ conda install -c conda-forge py3dep
        
        Quickstart
        ----------
        
        Py3DEP accepts `Shapely <https://shapely.readthedocs.io/en/latest/manual.html>`__'s
        Polygon or a bounding box (a tuple of length four) as an input geometry.
        We can use Hydrodata to get a watershed's geometry, then use it to get DEM and slope data
        in meters/meters from Py3DEP using ``get_map`` function.
        
        The ``get_map`` has a ``resolution`` argument that sets the target resolution
        in meters. Note that the highest available resolution throughout the CONUS is about 10 m,
        though higher resolutions are available in limited parts of the US. Note that the input
        geometry can be in any valid spatial reference (``geo_crs`` argument). The ``crs`` argument,
        however, is limited to ``CRS:84``, ``EPSG:4326``, and ``EPSG:3857`` since 3DEP only supports
        these spatial references.
        
        .. code-block:: python
        
            import py3dep
            from hydrodata import NLDI
        
            geom = NLDI().getfeature_byid("nwissite", "USGS-01031500", basin=True).geometry[0]
            dem = py3dep.get_map("DEM", geom, resolution=30, geo_crs="epsg:4326", crs="epsg:3857")
            slope = py3dep.get_map("Slope Degrees", geom, resolution=30)
            slope = py3dep.deg2mpm(slope)
        
        .. image:: https://raw.githubusercontent.com/cheginit/hydrodata/develop/docs/_static/example_plots_py3dep.png
            :target: https://raw.githubusercontent.com/cheginit/hydrodata/develop/docs/_static/example_plots_py3dep.png
            :align: center
        
        We can get the elevation for a single point within the US:
        
        .. code-block:: python
        
            elev = py3dep.elevation_byloc((-7766049.665, 5691929.739), "epsg:3857")
        
        Additionally, we can get the elevations of set of x- and y- coordinates of a grid. For example,
        let's get the minimum temperature data within the watershed from Daymet using Hydrodata then
        add the elevation as a new variable to the dataset:
        
        .. code-block:: python
        
            import hydrodata.datasets as hds
            import xarray as xr
            import numpy as np
        
            clm = hds.daymet_bygeom(geom, dates=("2005-01-01", "2005-01-31"), variables="tmin")
            gridxy = (clm.x.values, clm.y.values)
            elev = py3dep.elevation_bygrid(gridxy, clm.crs, clm.res[0] * 1000)
            clm = xr.merge([clm, elev], combine_attrs="override")
            clm["elevation"] = clm.elevation.where(~np.isnan(clm.isel(time=0).tmin), drop=True)
        
        
        Contributing
        ------------
        
        Contributions are very welcomed. Please read
        `CONTRIBUTING.rst <https://github.com/cheginit/pygeoogc/blob/master/CONTRIBUTING.rst>`__
        file for instructions.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
