Hkvwapory is a Python package that connects to the FAO WaPOR webservice. This package provide options to retrieve the url where the raster information is stored on the server given the parameter, level and location.
install using pypip:
pip install hkvwaporpy
hkvwaporpy depends on the following packages:
- requests
- pandas
- datetime
- json
If you have trouble installing these on Windows, you should try downloading these from https://www.lfd.uci.edu/~gohlke/pythonlibs (and use pip install path/to/package.whl to install the package).
Import the package
import hkvwaporpy as hkv
Metadata request for available products.
# request the catalogus
df = hkv.read_wapor.get_catalogus()
df.head()
# get additional info of the dataset given a code and catalogus
df_add = hkv.read_wapor.get_additional_info(df, cube_code='L2_AET_D')
A Jupyter Notebook is available in the notebook folder with a detailed example how to retrieve the url and parse and read this raster using GDAL.
HKVWAPORPY is written by
- Mattijn van Hoek m.vanhoek@hkv.nl
With contributions from:
- Bich N Tran b.tran@un-ihe.org
We at HKV provide expert advice and research in the field of water and safety. Using hkvwapory we access the WaPOR dataset to code custom-build operational apps and dashboards for river, coasts and deltas providing early-warnings and forecasts for risk and disaster management.
Interested? Head to https://www.hkv.nl/en/ or drop me a line at m.vanhoek [at] hkv.nl