Access USGS 3DEP database and get data such as elevation in the US
Project description
Package |
Description |
Status |
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Access NWIS, HCDN 2009, NLCD, and SSEBop databases |
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Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services |
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Convert responses from PyGeoOGC’s supported web services to datasets |
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Navigate and subset NHDPlus (MR and HR) using web services |
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Access topographic data through National Map’s 3DEP web service |
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Access Daymet for daily climate data both single pixel and gridded |
Py3DEP: Topographic data through 3DEP
🚨 This package is under heavy development and breaking changes are likely to happen. 🚨
Features
Py3DEP is a part of Hydrodata software stack and provides access to the 3DEP database which is a part of the National Map 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 requests as xarray 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 additional 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.
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.
Installation
You can install Py3DEP using pip after installing libgdal on your system (for example, in Ubuntu run sudo apt install libgdal-dev):
$ pip install py3dep
Alternatively, Py3DEP can be installed from the conda-forge repository using Conda:
$ conda install -c conda-forge py3dep
Quick start
Py3DEP accepts Shapely’s Polygon or a bounding box (a tuple of length four) as an input geometry. We can use PyNHD to get a watershed’s geometry, then use it to get the DEM and slope 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.
import py3dep
from pynhd 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)
We can get the elevation for a single point within the US:
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 PyDaymet then add the elevation as a new variable to the dataset:
import pydaymet as daymet
import xarray as xr
import numpy as np
clm = daymet.get_bygeom(geom, ("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 file for instructions.
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