Skip to content

Latest commit

 

History

History
79 lines (60 loc) · 4.7 KB

README.md

File metadata and controls

79 lines (60 loc) · 4.7 KB
Raw

pynasapower

nasa

Build Status Documentation Status Code coverage Supported Python versions Overall downloads Last month downloads

Download meteorological data from NASA POWER restful API (https://power.larc.nasa.gov/) using pynasapower API client.

The NASA POWER database is a global database of daily meteorological data designed for agrometeorological applications and more. Data are retrieced from in-situ observations in combination with satellite data. For more information on the NASA POWER database see the documentation at: https://power.larc.nasa.gov/.

Installation from source

git clone https://github.com/alekfal/pynasapower.git
cd pynasapower/
pip install .

Installation from PyPI

pip install pynasapower

NASA POWER API client arguments

  • geometry: Single point or polygon geometry as geopandas.GeoDataFrame. User can use methods pynasapower.geometry.point() or pynasapower.geometry.bbox() to create an input geometry for this client.
  • start: Start date as datetime.date format. In the examples the value is datetime.date(2022, 1, 1).
  • end: End date as datetime.date format. In the examples the value is datetime.date(2022, 2, 1).
  • path: Local path to store the downloaded data. In the examples "./" is used.
  • to_file: Boolean argument to save data locally. By default is True.
  • community: The default POWER community is agroclimatology ("ag"). Other available communities are sustainable buildings ("sb") and renewable energy ("re"). Find more about the POWER communities here.
  • parameters: The default parameters for downloading (["TOA_SW_DWN", "ALLSKY_SFC_SW_DWN", "T2M", "T2M_MIN", "T2M_MAX", "T2MDEW", "WS2M", "PRECTOTCORR"]) are selected for downloading if an empty list ([]) is provided by the user. Find more for the POWER parameters in here.
  • temporal_api: Temporal resolution of the data. The default value is "daily". Other selections are "hourly", "monthly", "climatology". Read more about the temporal resolution of the data here.
  • spatial_api: Spatial resolution of the data. By default "point" is selected, but a user can also use "regional". Note that in order to download a region a polygon geometry must be used in the geometry argument.
  • format: Output format of the data. The default is "csv". Other selections supported by the API client are: "netcdf", "json" and "ascii".

Quickstart

Download meteorological data for a point in Athens, Greece and save result in *.csv format. First, create a "data" folder to hold the POWER data upon download in your current environment.

$ mkdir data

Then, run in Python the following to fetch data from NASA POWER:

from pynasapower.get_data import query_power
from pynasapower.geometry import point, bbox
import datetime

# Run for point in Athens and save the result in csv format
gpoint = point(23.727539, 37.983810, "EPSG:4326")
start = datetime.date(2022, 1, 1)
end = datetime.date(2022, 2, 1)
data = query_power(geometry = gpoint, start = start, end = end, path = "./data", to_file = True, community = "ag", parameters = [], temporal_api = "daily", spatial_api = "point", format = "csv")

Download meteorological data for a polygon in Athens, Greece and save result in *.csv format.

# Run for small bbox in Athens and save the result in csv format
gbbox = bbox(23.727539, 26.73, 37.983810, 40.99, "EPSG:4326")
start = datetime.date(2022, 1, 1)
end = datetime.date(2022, 2, 1)
data = query_power(geometry = gbbox, start = start, end = end, path = "./data", to_file = True, community = "ag", parameters = [], temporal_api = "daily", spatial_api = "point", format = "csv")

Read more about the software in project's readthedocs.